JP2024018437A - Management method of driving characteristic improvement support data - Google Patents

Abstract

PROBLEM TO BE SOLVED: To support management of driving characteristic data of a driver collected in a different vehicle and takeover of the driving characteristic data of the driver between vehicles.

SOLUTION: A control method can be executed by a computer which can be linked with at least a first vehicle and a second vehicle. The computer receives input of individual characteristic data that is acquired by the first vehicle, used for improvement support of driving characteristics of a driver who drives the first vehicle and corresponds to the driver, and outputs the individual characteristic data corresponding to the driver to be usable in the second vehicle when a predetermined condition is satisfied.

SELECTED DRAWING: Figure 39

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present disclosure relates to a method for managing driving characteristic improvement support data.

2. Description of the Related Art Vehicle warning devices and driving support devices that support a driver's safety confirmation, driving operations, etc. while driving are conventionally known.

For example, Patent Document 1 discloses a driver identification system that acquires biometric information of a driver of a vehicle and identifies the driver based on the acquired biometric information. The driver identification system periodically acquires biometric information when it is determined that information from an electronic device installed in a vehicle satisfies a predetermined condition.

For example, Patent Document 2 discloses that it is determined based on the relationship between predetermined road parameters of the road on which the vehicle is traveling and the steering angle, and whether or not the driver is in a situation that requires safety confirmation. A vehicle warning device has been disclosed that gives a warning to the driver when it is determined that the vehicle is not being used. Additionally, Patent Document 3 discloses a driving support device that learns the driver's driving proficiency level based on the history of the driver's driving operations and provides driving support according to the driving support level based on the driving proficiency level. has been done. Furthermore, Patent Document 4 describes a method for estimating the driving state of a driver relative to the external environment based on the environmental difficulty level required for the driver's driving operation due to the external environment of the vehicle and the driving skill based on the driver's driving operation. , a driving support device is disclosed that provides or prohibits driving support depending on the driving skill and driver condition.

For example, Patent Document 5 discloses an information processing device having a processor that controls a process of passing learning data used for learning of a first artificial intelligence to a second artificial intelligence when an instruction to take over the artificial intelligence is received. ing. Furthermore, in Patent Document 6, an artificial intelligence model generated by user adaptive training that accepts input of user data including user biometric information and converts a base artificial intelligence model to suit the characteristics of the user data is applied. An artificial intelligence service providing method for providing an artificial intelligence service is disclosed. Further, Patent Document 7 describes a first artificial intelligence unit that acquires user information in a non-secure environment that is accessible from outside the artificial intelligence system and outputs learning results based on the user information to the outside; and a second artificial intelligence unit that acquires user information from the first artificial intelligence and accumulates data related to the user information in a secure environment that cannot be accessed from the outside. An artificial intelligence system is disclosed that deletes the user's information from the non-secure environment of the first artificial intelligence unit when the user's information is handed over to the intelligence unit.

JP 2015-71319 Publication Japanese Patent Application Publication No. 2007-233476 Japanese Patent Application Publication No. 2009-48307 Japanese Patent Application Publication No. 2015-110417 JP 2021-18457 Publication JP2021-529978A JP 2021-105796 Publication

However, with the above-mentioned information processing device, artificial intelligence service providing method, and artificial intelligence system, when multiple different vehicles provide driving assistance to the same driver, the driving assistance that can be realized by each vehicle is different. There was room for improvement.

The present disclosure has been devised in view of the above-mentioned conventional circumstances, and provides a control method that supports the management of driver driving characteristic data collected in different vehicles and the handing over of driver driving characteristic data between vehicles. The purpose is to provide.

The present disclosure is a control method executable by a computer that can cooperate with at least a first vehicle and a second vehicle, the control method being acquired by the first vehicle to improve driving characteristics of a driver driving the first vehicle. used for support, receives input of personal characteristic data corresponding to the driver, and outputs the personal characteristic data corresponding to the driver in order to make it available to the second vehicle if a predetermined condition is met. , provides a control method.

According to the present disclosure, it is possible to support the management of driver driving characteristic data collected in different vehicles and the handing over of driver driving characteristic data between vehicles.

A diagram showing an example use case of the driving characteristics management system according to Embodiment 1 Block diagram showing an example of internal configuration of a vehicle in Embodiment 1 Block diagram showing an example of internal configuration of the driving characteristics server in Embodiment 1 Block diagram showing an example of internal configuration of a license server in Embodiment 1 Sequence diagram showing an example of initial driver registration procedure of the driving characteristics management system according to Embodiment 1 Flowchart showing an example of the initial registration procedure for a driver in a vehicle Flowchart showing an example of vehicle ID registration procedure in a vehicle Flowchart showing an example of the procedure for registering a license ID in a vehicle Flowchart showing an example of a driver's face image registration procedure in a vehicle Flowchart showing an example of the initial registration procedure of a driver in the driving characteristics server Flowchart showing an example of vehicle ID registration procedure in the driving characteristics server Flowchart showing an example of license ID registration procedure in the driving characteristics server Flowchart showing an example of the driver's face image registration procedure in the driving characteristics server Sequence diagram showing an example of a driver's driving characteristic data collection procedure of the driving characteristic management system according to Embodiment 1 Flowchart showing an example of a procedure for acquiring driving characteristic data of a driver in a vehicle Flowchart showing an example of the procedure for collecting driver driving characteristic data on the driving characteristic server A diagram showing an example of a use case of the driving characteristic improvement support system according to Embodiment 2 Block diagram showing an example of internal configuration of a vehicle in Embodiment 2 Diagram showing an example of a driving characteristics history table Block diagram showing an example of internal configuration of the driving characteristic improvement server in Embodiment 2 Diagram showing an example of a driving characteristics improvement management table Diagram explaining an example of safety confirmation behavior when turning left Diagram explaining an example of safety confirmation behavior when turning right Diagram explaining an example of safety confirmation behavior when reversing Diagram explaining an example of safety confirmation behavior when moving forward on a long-distance straight road Diagram explaining sensing examples of driver safety confirmation behavior for each driving situation Diagram explaining an example of the arrangement of warning indicator lights Diagram explaining an example of speaker placement Diagram explaining an example of changing driving characteristic improvement support Flowchart showing an example of the operation procedure of the driving characteristic improvement support system according to Embodiment 2 Flowchart illustrating an example of the operation procedure of the driving characteristic improvement support system according to Embodiment 2 A diagram showing an example of a use case of the driving characteristic improvement support system according to Embodiment 3 Block diagram showing an example of internal configuration of a vehicle in Embodiment 3 Block diagram showing an example of internal configuration of the driving characteristic improvement server in Embodiment 3 Block diagram showing an example of internal configuration of an operating terminal in Embodiment 3 Diagram showing an example of personal information/personal characteristics data table Sequence diagram showing example 1 of handover procedure of driver handover data of the driving characteristics management system according to Embodiment 3 Sequence diagram illustrating example 2 of handover procedure of driver handover data of the driving characteristics management system according to Embodiment 3 Diagram illustrating examples 1 and 2 of handing over driver handover data Diagram illustrating modification example 1 of inter-vehicle driving characteristic improvement support operation Diagram illustrating modification example 2 of inter-vehicle driving characteristic improvement support operation Screen transition diagram explaining an example of deleting inherited data Screen transition diagram explaining an example of settings for transfer data Screen transition diagram explaining an example of searching for inherited data Screen transition diagram explaining an example of editing inherited data

(Details leading to Embodiment 1)
In recent years, eKYC (electronic know your customer), for example, is a type of system that can realize user identity verification online. eKYC is a facial image or video of the user's face sent from a user terminal (e.g., PC (Personal Computer), smartphone, tablet device, etc.) and personal information such as the user's name, address, and date of birth. and a moving image of an identification document (for example, a driver's license, residence card, passport, My Number card, etc.) on which the user's face image is written. eKYC uses pre-registered information about this user (e.g., video images, various personal information written on identity verification documents, etc.), the acquired facial image or video of the user, and video images of identity verification documents. The user's identity is verified by verifying the identity of the user.

Conventionally, the driver is identified by acquiring the driver's biometric information and information regarding the driver's driving operations from the vehicle, and the identified driver's driving characteristic information and the ID of the vehicle the driver drives. There is a driver identification system that records the information in association with each other (for example, Patent Document 1: Japanese Unexamined Patent Publication No. 2015-71319). However, if the vehicle is a rental car, shared car, or other vehicle driven by multiple different drivers, the driver identification system associates the driver's driving characteristic information with the ID of the vehicle being driven by the driver. Therefore, it was difficult to record and manage driving characteristic information for each driver.

Furthermore, in recent years, accidents caused by driving errors caused by aging of elderly drivers (elderly drivers) have been increasing. Efforts to prevent such accidents include, for example, conducting cognitive function tests for elderly drivers when renewing their driver's licenses, and recommending that elderly drivers over a certain age return their driving licenses. However, if elderly drivers surrender their driver's licenses, they could lose the means of transportation that is essential to their independent daily lives. Therefore, when determining whether or not to return a driver's license, it is possible to objectively evaluate the driving behavior of elderly drivers using the collected driving characteristic data and visualize changes in the driving behavior of elderly drivers. Although desired, the driver identification system is not intended to collect and manage driving characteristic data for the purpose of obtaining the above-mentioned driving evaluation for each driver.

Therefore, in Embodiment 1 below, an example of a driving characteristic data management method and an on-vehicle device that more efficiently collects driving characteristic data for each driver and supports management of the collected driving characteristic data will be described. .

EMBODIMENT OF THE INVENTION Hereinafter, each embodiment which specifically disclosed the management method of driving characteristic data, the on-vehicle device, and the management method of driving characteristic improvement support data according to the present disclosure will be described in detail with reference to the drawings as appropriate. However, more detailed explanation than necessary may be omitted. For example, detailed explanations of well-known matters or redundant explanations of substantially the same configurations may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. The accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter recited in the claims.

(Embodiment 1)
An example use case of the driving characteristics management system 100 according to the first embodiment will be described with reference to FIG. 1. FIG. 1 is a diagram illustrating an example use case of the driving characteristics management system 100 according to the first embodiment. The driving characteristic management system 100 in FIG. 1 illustrates an example in which a facial image of a driver is transmitted as an example of biometric information.

The driving characteristics management system 100 includes one or more vehicles C1, . . . , a driving characteristics server S1, a license server S2, and a network NW. Note that the driving characteristic management system 100 may include a wireless terminal device P1.

The driving characteristic management system 100 acquires driving characteristic data of a driver who drives a vehicle transmitted from a communication device 11 (see FIG. 2) mounted on each of one or more vehicles C1, . . . . The driving characteristic management system 100 associates the acquired driving characteristic data with the driver's license ID (Identification), stores the data in the driving characteristic server S1, and manages the data. Further, the driving characteristic management system 100 manages the respective license IDs of a plurality of drivers registered in advance in the license server S2. The driving characteristics management system 100 executes a driving evaluation for each driver using the driving characteristics server S1 or the license server S2, and transmits the driving evaluation results to the wireless terminal device P1 or the car navigation device 12 for output.

The driving characteristic data referred to here is data indicating the driving characteristics of the driver, and includes various sensors (for example, in-vehicle camera 13, gyro sensor 14, accelerator pedal 17A, brake The information is acquired by the pedal 17B, turn lamp 17C, speed sensor 18, external sensor/camera 19, GPS sensor 20, steering wheel 17D, etc. (see FIG. 2).

For example, the driving characteristic data is data indicated by at least one of a driving characteristic parameter or a driving characteristic vector, and includes acceleration, jerk, lateral G (that is, acceleration that occurs perpendicular to the direction of travel), and steering angle when driving. , the type of road on which the vehicle is traveling, the speed exceeding the speed limit of the road on which the vehicle is traveling, and the direction of the driver's line of sight. Note that the driving characteristic data is not limited to the above-mentioned example, and may be data indicating the driver's driving characteristics obtained by combining two or more of these data.

The driving characteristic parameter is a value (parameter) for each data included in the driving characteristic data. The driving characteristic vector is an average value calculated based on the number of data included in the driving characteristic data and the value of each data. For example, when the number of driving characteristic data is N (N: an integer greater than or equal to 1), the driving characteristic vector is represented by an N-dimensional vector.

Each of the vehicles C1, . . . is connected to the driving characteristic server S1 via the network NW so as to be able to communicate wirelessly. Note that the wireless communication referred to here is, for example, a wireless LAN represented by Wi-Fi (registered trademark), and the type thereof is not particularly limited. When the driver drives the own vehicle for the first time, each of the vehicles C1, ... generates a control command requesting the initial registration of the driver, and receives the driver's license ID and biometric information for the initial registration. and the vehicle ID are linked and transmitted to the driving characteristic server S1. Further, while each of the vehicles C1,... is being driven by the driver, the driver's driving characteristic data and vehicle ID are linked and transmitted to the driving characteristic server S1, and is recorded in association with the initially registered driver's license ID.

In the initial registration, each of the vehicles C1, . . Each of the vehicles C1, ... acquires the driver's license ID and the driver's biometric information, and uses the acquired driver's license ID and biometric information with a vehicle ID that can identify the own vehicle (e.g. , license plate information), and transmits it to the driving characteristics server S1.

When collecting driving characteristic data, each of the vehicles C1, ... starts acquiring driving characteristic data using various sensors from the timing when the driver's boarding is detected, and links the acquired driving characteristic data with the vehicle ID. and transmits it to the driving characteristics server S1. In addition, each of the vehicles C1, ... starts acquiring the driver's biometric information from the timing when the driver's boarding is detected, and links the acquired driver's biometric information with the vehicle ID to determine the driving characteristics. The information is transmitted to the server S1 to request driver authentication (that is, identification of the driver) from the driving characteristics server S1. Note that each of the vehicles C1, . . . may link the driving characteristic data, the driver's biometric information, and the vehicle ID and transmit them to the driving characteristic server S1. Furthermore, each of the vehicles C1, ... has completed the driver authentication sent from the driving characteristics server S1 (that is, the sent biometric information of the driver is compared with the biological information already registered in the driving characteristics server S1). If an electric signal indicating that the vehicle has been used) is obtained, the acquisition and transmission of the driver's biometric information is terminated.

Each of the vehicles C1, . . . ends acquisition of driving characteristic data and biological information by various sensors at the timing when the end of driving by the driver is detected.

The license ID referred to here is an image of the driver's license of the driver driving the vehicle taken by the in-vehicle camera 13, or a license reader (not installed) that can read the license ID written on the driver's license. Information regarding the driver's license (for example, a facial image of the driver, information regarding the driver, various numbers assigned to enable identification of the driver, etc.) obtained by the driver's license (as shown in the figure). The license reader may be able to transmit the license ID read by near field communication such as NFC (Near Field Communication) or Bluetooth (registered trademark) to the processor 12A, or may be able to transmit the license ID to the processor 12A using a USB (Universal Serial Bus) or the like. The driver's license ID read by wire communication with the car navigation device 12 may be transmitted to the processor 12A.

Further, the license ID may be information related to the driver's license obtained by analyzing an image taken by the in-vehicle camera 13, or information provided by the driver to the input section 12D of the car navigation device 12 (see FIG. 2). The information may be information related to a driver's license input through an input operation.

Further, the biological information of the driver referred to here includes one or more facial images, irises, fingerprints, veins, voice, etc. of the driver. When the driver's biometric information is the driver's iris, fingerprint, vein, voice, etc., each of the vehicles C1,... is equipped with a device (not shown) or a sensor capable of acquiring the driver's iris, fingerprint, vein, voice, etc. (not shown).

The driver's face image is captured by the in-vehicle camera 13. In addition, it is desirable that a plurality of facial images of the driver are captured at the time of initial registration, and at least a facial image captured while the driver is facing forward (hereinafter referred to as a "frontal facial image") Contains 1 piece. If the number of face images captured at the time of initial registration is two or more, the in-vehicle camera 13 analyzes the direction of the driver's face through image analysis, and displays the front face image and other directions other than the driver's front face. One or more facial images taken while the person is facing (for example, leftward, rightward, etc.) are captured. In addition, in the following explanation, a face image captured while facing to the left will be referred to as a "left-facing face image", and a face image captured while facing to the right will be referred to as a "right-facing face image". .

The iris is determined by image analysis by an ICM (Intelligent Control Module, not shown) installed in the vehicle C1,..., the car navigation device 12, or the driving characteristic server S1 using the driver's face image captured by the in-vehicle camera 13. May be obtained.

The fingerprint may be obtained by image analysis by the ICM installed in the vehicle C1, the car navigation device 12, or the driving characteristics server S1 using one or more fingertip images of the driver captured by the in-vehicle camera 13. Alternatively, the information may be acquired by a fingerprint sensor (not shown) included in the vehicle C1, . . . or a steering wheel 17D having a fingerprint sensor function.

The veins may be obtained by image analysis by the ICM, car navigation device 12, or driving characteristic server S1 mounted on the vehicle C1, using an image of the driver's hand captured by the in-vehicle camera 13, or It may be acquired by a vein sensor (not shown) provided in C1, .

The voice is the driver's voice collected by a microphone included in the car navigation device 12 or another microphone (not shown). The audio collected here may be a predetermined keyword or the like.

The driving characteristic server S1 is connected via the network NW to each of the vehicles C1, . . . , the wireless terminal device P1, and the license server S2 so as to enable data communication. The driving characteristic server S1 performs initial registration based on a control command requesting initial registration of a driver transmitted from each of the vehicles C1, . Further, the driving characteristic server S1 collects the driving characteristic data of the driver transmitted from each of the vehicles C1, ..., and assigns the collected driving characteristic data of the driver to the initially registered driver's license ID. Link and record.

In the initial registration, the driving characteristic server S1 receives a control command requesting the initial registration of the driver sent from each of the vehicles C1, ..., biometric information of the driver who is the subject of initial registration, the license ID, and the vehicle. Get the ID. The driving characteristic server S1 collates the acquired biometric information of the driver with the license ID and determines whether the driver indicated by the biometric information and the driver indicated by the license ID are the same person (that is, (identity verification). If the driving characteristics server S1 determines that the acquired biometric information and the driver indicated by the license ID are the same person, the driving characteristic server S1 stores the driver's license ID, the driver's face image, and the vehicle ID. Link and register (initial registration). Note that the driver's face image registered here may be one front face image, or one front face image and one or more right-facing face images or left-facing face images. .

When collecting driving characteristic data, the driving characteristic server S1 acquires the driver's biometric information, driving characteristic data, and vehicle ID transmitted from each of the vehicles C1, . The biometric information of a plurality of initially registered drivers is compared with each other. If the driving characteristics server S1 determines that there is a driver to be compared among the biometric information of a plurality of drivers, the driving characteristics server S1 links the acquired driving characteristics data and the vehicle ID to the driver's license ID. Record.

The driving characteristic server S1 executes a driving evaluation using the driving characteristic data of the predetermined driver based on the control command requesting the driving evaluation result of the predetermined driver transmitted from the license server S2. The driving characteristic server S1 generates a driving evaluation result and transmits it to the wireless terminal device P1. In such a case, the wireless terminal device P1 is possessed by, for example, an employee of the National Police Agency who decides whether to renew a driver's license, an employee of an insurance company that handles insurance (products) related to automobiles, or the like. Thereby, the staff of the National Police Agency can make a decision regarding renewal of a driver's license based on the driving evaluation result of a predetermined driver displayed on the wireless terminal device P1. Similarly, an employee of the insurance company calculates the car insurance premium for a given driver based on the driving evaluation result (that is, an index indicating the degree of safe driving) of the given driver displayed on the wireless terminal device P1. can.

The driving characteristic server S1 also acquires a control command requesting driving characteristic data of a predetermined driver transmitted from the wireless terminal device P1 owned by the driver. The driving characteristics server S1 compares the license ID or biometric information included in the control command transmitted from the wireless terminal device P1 with the license IDs or biometric information of a plurality of registered drivers. Based on the verification results, the driving characteristic server S1 extracts the driving characteristic data of the driver corresponding to the license ID or biometric information included in the control command and the vehicle ID of the vehicle from which the driving characteristic data has been acquired. , to the wireless terminal device P1 or the car navigation device 12.

Note that when the driving characteristic server S1 executes a driving evaluation of this driver based on the accumulated driving characteristic data, the driving characteristic server S1 performs a driving evaluation based on the driving characteristic data that corresponds to the license ID or biometric information included in the control command. A driving evaluation result of the driver may be generated and transmitted to the wireless terminal device P1 or the car navigation device 12.

The license server S2 is connected to the driving characteristic server S1 and the wireless terminal device P1 via the network NW so as to enable data communication between them. The license server S2 records and manages license IDs of multiple drivers. Note that the information recorded and managed by the license server S2 is not limited to the license ID, and may be, for example, information regarding driver's license renewal, driving evaluation results using driving characteristic data, and the like.

The license server S2 acquires a control command requesting driving characteristic data of a predetermined driver transmitted from the wireless terminal device P1. The license server S2 collates the license ID or biometric information included in the control command transmitted from the wireless terminal device P1 with the license IDs or biometric information of multiple registered drivers, and uses the collation results as a driver's license. Send to characteristic server S1. Based on the verification results, the driving characteristic server S1 extracts the driving characteristic data of the driver corresponding to the license ID or biometric information included in the control command and the vehicle ID of the vehicle from which the driving characteristic data has been acquired. , is transmitted to the license server S2.

Note that when the driving characteristic server S1 executes a driving evaluation of this driver based on the accumulated driving characteristic data, the driving characteristic server S1 performs a driving evaluation based on the driving characteristic data that corresponds to the license ID or biometric information included in the control command. A driving evaluation result of the driver may be generated and transmitted to the license server S2.

The wireless terminal device P1 is communicably connected to the driving characteristic server S1 via the network NW. The wireless terminal device P1 is, for example, a PC (Personal Computer), a notebook PC, a tablet terminal, or a smartphone owned by a driver, a relative of the driver, a police officer, an employee of an insurance company, or the like. Note that the wireless terminal device P1 is not limited to the example described above, and may be a car navigation device 12 mounted on the vehicle C1, . . . .

The wireless terminal device P1 can accept input operations from the driver, the driver's relatives, etc., and generates a control command requesting the driver's driving evaluation result based on the input operations. The wireless terminal device P1 acquires the driver's license ID or biometric information, associates the acquired driver's license ID or biometric information with a control command, and transmits the link to the driving characteristic server S1. Further, when the wireless terminal device P1 acquires the driver's driving evaluation result transmitted from the driving characteristics server S1, the wireless terminal device P1 outputs the acquired driver's driving evaluation result to the monitor (not shown) of the wireless terminal device P1. . Note that when the wireless terminal device P1 is realized by the car navigation device 12, the wireless terminal device P1 (that is, the car navigation device 12) displays the acquired driver's driving evaluation result on the display unit 12C of the car navigation device 12. Output.

The network NW connects each of the plurality of vehicles C1, ..., the driving characteristics server S1, and the license server S2, and between the driving characteristics server S1 and the wireless terminal device P1 to enable wireless communication. .

Next, with reference to FIG. 2, an example of the internal configuration of the vehicles C1, . . . in the first embodiment will be described. FIG. 2 is a block diagram showing an example of the internal configuration of the vehicles C1, . . . in the first embodiment. The internal configuration of the vehicle C1,... shown in FIG. 2 is an example of the internal configuration when using the driver's face image as biometric information, and includes sensors for acquiring other biometric information, a driver's license reader, etc. illustration is omitted. Moreover, since each of the vehicles C1, . . . has a similar internal configuration, the internal configuration of the vehicle C1 will be described in the following description.

The vehicle C1 is configured to include at least a communication device 11, a car navigation device 12, an in-vehicle camera 13, a gyro sensor 14, a memory 15, and an ECU (Electronic Control Unit) 16. Each part inside the vehicle C1 is connected to enable data transmission and reception via a CAN (Controller Area Network) or the like.

Note that the communication device 11, car navigation device 12, in-vehicle camera 13, and gyro sensor 14 may be integrally configured as one car navigation device 10. Moreover, the sensor mounted on the vehicle C1 shown in FIG. 2 is an example, and the sensor is not limited thereto.

The communication device 11 transmits and receives data by wireless communication between the vehicle C1 and the driving characteristic server S1 via the network NW. The communication device 11 transmits the driver's license ID, biometric information (here, one or more facial images), vehicle ID, driving characteristic data, etc. to the driving characteristic server S1. The communication device 11 receives an electrical signal notifying the completion of initial registration, an electrical signal notifying the completion of driver identification, etc. transmitted from the driving characteristics server S1, and outputs them to the processor 12A.

The car navigation device 12 is a device that can accept driver operations. Furthermore, the car navigation device 12 may be an IVI (In-Vehicle Infotainment) device that can provide, for example, a car navigation function, a location information providing service function, an Internet connection function, a multimedia playback function, and the like. The car navigation device 12 includes a processor 12A, a memory 12B, a display section 12C, and an input section 12D.

The processor 12A is configured using, for example, a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or an FPGA (Field Programmable Gate Array), and controls the operation of each part. The processor 12A cooperates with the memory 12B to perform various types of processing and control in an integrated manner. Specifically, the processor 12A refers to programs and data held in the memory 12B, and executes the programs to realize the functions of each section.

The processor 12A starts the initial registration process based on the control command for starting the initial registration of the driver in the driving characteristics server S1, which is output from the input unit 12D. The processor 12A requests one or more facial images of the driver captured by the in-vehicle camera 13, a captured image of the driver's license (license ID), a vehicle ID, and initial registration of the driver. It is associated with the control command and transmitted to the driving characteristic server S1. Note that the license ID may be license information input into the input unit 12D by the driver's operation. Similarly, the information may be license plate information input into the input section 12D by the driver's operation.

The processor 12A starts acquiring the driver's driving characteristic data from the timing at which the processor 12A acquires a control command from the ECU 16 or the communication device 11 indicating that the driver's boarding is detected. The processor 12A acquires the angular velocity of the vehicle C1 as driving characteristic data based on the electric signal output from the gyro sensor 14, and acquires the angular velocity of the vehicle C1 as driving characteristic data, and acquires the angular velocity of the vehicle C1 as driving characteristic data, and acquires the angular velocity of the vehicle C1 via the ECU 16, and acquires the angular velocity of the vehicle C1 based on the electric signal output from the gyro sensor 14. , brake pedal 17B, turn lamp 17C, speed sensor 18, external sensor/camera 19, GPS sensor 20, steering wheel 17D, etc.). Note that the driving characteristic data acquired by the various sensors will be described later. The processor 12A associates the acquired driving characteristic data with the vehicle ID and transmits it to the driving characteristic server S1. Further, the processor 12A causes the in-vehicle camera 13 to capture a face image of the driver as the driver's biometric information used for registration or identification of the driver performed by the driving characteristics server S1. The processor 12A associates the driver's face image output from the in-vehicle camera 13 with the vehicle ID and transmits the linked image to the driving characteristic server S1.

The processor 12A acquires the driver's driving characteristic data and transmits the driving characteristic data to the driving characteristic server S1 at the timing when the processor 12A receives a control command from the ECU 16 or the communication device 11 indicating that the driver's alighting is detected. end. Note that the processor 12A may terminate the imaging process by the in-vehicle camera 13 based on a control command sent from the driving characteristics server S1 to the effect that initial registration or face verification of the driver has been completed.

Further, the processor 12A may perform image analysis of the driver's face image output from the in-vehicle camera 13, and perform detection of the driver's line of sight, drowsiness, emotion, etc. The processor 12A sends the detected detection result as driving characteristic data to the driving characteristic server S1 in association with the vehicle ID.

The memory 12B includes, for example, a RAM (Random Access Memory) as a work memory used when executing each process of the processor 12A, and a ROM (Read Only Memory) that stores programs and data that define the operations of the processor 12A. have Data or information generated or acquired by the processor 12A is temporarily stored in the RAM. A program that defines the operation of the processor 12A is written in the ROM. The memory 12B also stores the vehicle ID of the vehicle C1.

The display unit 12C is configured using, for example, an LCD (Liquid Crystal Display) or an organic EL (Electroluminescence).

The input section 12D is a user interface configured integrally with the display section 12C. The input unit 12D converts the received driver operation into an electrical signal (control command) and outputs it to the processor 12A. The input unit 12D accepts an input operation by the driver to start initial registration, or an input operation for a driver's license ID or vehicle ID.

The in-vehicle camera 13 includes at least a lens (not shown) and an image sensor (not shown). The image sensor is a solid-state imaging device such as a CCD (Charged-Coupled Device) or a CMOS (Complementary Metal-Oxide-Semiconductor), and converts an optical image formed on an imaging surface into an electrical signal.

The in-vehicle camera 13 images the face of the driver sitting in the driver's seat based on an input operation by the driver via the input unit 12D or detection of the driver's boarding, and outputs the image to the processor 12A. The processor 12A analyzes the captured facial image of the driver and detects the orientation of the driver's face. When the processor 12A determines that the detected driver's face orientation is the preset face orientation, the processor 12A links this face image with the vehicle ID and sends the information from the communication device 11 to the driving characteristics server S1. Let it be sent. Note that the process of detecting the direction of the driver's face from the face image may be executed by the driving characteristics server S1.

For example, if a front face image is required for driver authentication at the time of initial registration or driver identification at the time of recording driving characteristic data, the processor 12A determines that the detected face direction of the driver is front. The front face image determined as such is linked with the vehicle ID and transmitted to the driving characteristic server S1.

Further, for example, if facial images of the driver facing a plurality of different directions are required for driver authentication during initial registration or identification of the driver when recording driving characteristic data, the processor 12A may detect one or more face images of each of a front face image determined to be facing forward, a right facing face image determined to be facing right, or a left facing face image determined to be facing left. Select. The processor 12A associates the selected two or more facial images with the vehicle ID and transmits them to the driving characteristic server S1. Thereby, the vehicle C1 can more effectively suppress impersonation of the driver using the driver's front face image captured in advance.

Further, the in-vehicle camera 13 may take an image of the driver's driver's license based on an input operation by the driver via the input unit 12D. In such a case, the processor 12A outputs the captured image captured by the in-vehicle camera 13 to the processor 12A, displays it on the display section 12C, and adds the captured image area of the driver's license to the captured image displayed on the display section 12C. The indicated frame lines may be superimposed. Thereby, the car navigation device 10 can support the capturing of a facial image of a driver's license used to identify the driver, or the capturing of a driver's license that can read various information written on the driver's license.

The gyro sensor 14 is a so-called angular velocity sensor, and may be a mechanical type, an optical type, a vibration type, or the like. The gyro sensor 14 detects changes in the rotation and orientation of the vehicle C1 as angular velocity, converts it into an electrical signal, and outputs it to the processor 12A.

The memory 15 includes, for example, a RAM (Random Access Memory) as a work memory used when executing each process of the ECU 16, and a ROM (Read Only Memory) that stores programs and data that define the operation of the ECU 16. Data or information generated or acquired by the ECU 16 is temporarily stored in the RAM. A program that defines the operation of the ECU 16 is written in the ROM. Further, the memory 15 may store the vehicle ID of the vehicle C1.

The ECU 16 collectively executes processing and control of each section. The ECU 16 is configured using a so-called electronic circuit control device, refers to programs and data held in the memory 15, and implements the functions of each part by executing the programs. The ECU 16 receives various operation information (for example, sudden acceleration, sudden deceleration, lighting information, Steering (torque) information, etc.) is acquired as driving characteristic data. The ECU 16 outputs driving characteristic data based on the acquired operation information of the operation unit 17 to the processor 12A.

In addition, the ECU 16 determines conditions for detecting the presence of the driver, such as closing the door of the driver's seat, fastening the seat belt of the driver's seat, releasing the handbrake after turning on the ignition, and installing a load sensor (not shown) provided on the driver's seat. Detects whether the driver is seated or detects the torque of the steering wheel 17D. The ECU 16 detects the driver's entry based on whether one or more or two or more driver entry detection conditions are satisfied. The ECU 16 generates a control command indicating that the driver's boarding is detected, and outputs it to the processor 12A of the car navigation device 12 or the communication device 11.

In addition, the ECU 16 detects conditions for detecting the driver's exit from the vehicle, such as opening the driver's door, releasing the driver's seat belt, detecting that the ignition is turned off, or detecting that the driver is driving using a load sensor (not shown) installed in the driver's seat. Detection of people leaving their seats, etc. The ECU 16 detects the driver's exit from the vehicle based on whether one or more or two or more driver exit detection conditions are satisfied. The ECU 16 generates a control command indicating that the driver has exited the vehicle, and outputs it to the processor 12A of the car navigation device 12 or the communication device 11.

The speed sensor 18 measures the speed of the vehicle C1 based on a vehicle speed pulse generated by the rotation speed of the drive shaft inside the vehicle C1. Speed sensor 18 outputs the measured speed of vehicle C1 to processor 12A.

The external sensor/camera 19 is one or more sensors such as radar and sonar provided in the vehicle C1, and one or more cameras capable of capturing images of the surroundings of the vehicle C1 (outside the vehicle). The camera here may be a drive recorder. The external sensor/camera 19 detects the position and direction of objects around the vehicle C1 (for example, walls, obstacles, other vehicles, people, etc.), detects signs, and detects white lines on the road. Detect. The external sensor/camera 19 outputs detected detection information to the processor 12A. The processor 12A transmits the detection information output from the external sensor/camera 19 and the driving characteristic data to the driving characteristic server S1.

The GPS sensor 20 is not limited to US GPS (Global Positioning System) signals, but may also be an artificial satellite (not shown) capable of providing satellite positioning services, such as Russia's GLONASS (Global Navigation Satellite System) or European Galileo, or A satellite positioning signal transmitted from a quasi-zenith satellite (not shown) is received. GPS sensor 20 calculates information on the traveling speed and traveling position of vehicle C1 based on the received satellite positioning signal, and outputs the information to processor 12A. Note that the calculation of information on the traveling speed and traveling position of the vehicle C1 based on the satellite positioning signal or the quasi-zenith satellite may be performed by the GPS sensor 20.

Next, with reference to FIG. 3, the internal configuration of the driving characteristic server S1 in the first embodiment will be described. FIG. 3 is a block diagram showing an example of the internal configuration of the driving characteristic server S1 in the first embodiment. In the following description, in order to make the explanation easier to understand, various data or information collected (recorded) and managed by the driving characteristics server S1 will be explained using the driving characteristics table TB1 as an example. is not required and may be omitted.

The driving characteristics server S1 includes a communication section 31, a processor 32, and a memory 33.

The communication unit 31 is connected to each of the vehicles C1, . . . , the wireless terminal device P1, and the license server S2 via the network NW so as to be able to transmit and receive data.

The processor 32 is configured using, for example, a CPU, a DSP, or an FPGA, and controls the operations of each section. The processor 32 cooperates with the memory 33 to perform various types of processing and control in an integrated manner. Specifically, the processor 32 references programs and data held in the memory 33 and executes the programs to realize the functions of each part. The processor 32 generates a driving characteristic table TB1 and stores it in the memory 33.

The driving characteristic table TB1 records and manages a vehicle ID, driving characteristic data, and biometric information (in the example shown in FIG. 3, a driver's face image) in association with a license ID. In addition, the driving characteristic table TB1 shown in FIG. 3 is assigned to each driver as an example, and further records a user ID that can identify the driver in association with the license ID. Furthermore, the biometric information recorded in the driving characteristic table TB1 is the biometric information registered (stored) at the time of initial registration.

For example, the driving characteristics table TB1 shown in FIG. Link the license ID "YYY" with the vehicle ID "KKK", the user ID "BBB", the facial image data, and the driving characteristics data, and link the license ID "ZZZ" with the vehicle ID "MMM". , the user ID "CCC", the facial image data, and the driving characteristic data are linked and recorded. As a result, the driving characteristic table TB1 is configured such that when a plurality of different drivers (for example, two users "AAA" and "BBB" each) drive a vehicle having the same vehicle ID "KKK", However, since driving characteristic data can be recorded for each license ID, driving characteristic data can be managed for each driver.

The processor 32 starts the initial registration process based on a control command requesting initial registration transmitted from each of the vehicles C1, . The processor 32 associates the driver's license ID, the driver's biometric information, and the vehicle ID transmitted from each of the vehicles C1, . . . with the vehicle ID, and registers (stores) them in the driving characteristic table TB1. Note that when the processor 32 determines that the acquired license ID has been registered in the driving characteristic table TB1, the processor 32 stores the driver's biometric information linked to the registered license ID and the acquired biometric information. Check the information. If the processor 32 determines that the biometric information of the driver linked to the registered license ID matches the acquired biometric information, the processor 32 selects the acquired biometric information from the registered license ID in the driving characteristic table TB1. The vehicle ID is further linked and recorded.

When the processor 32 acquires the vehicle ID and driving characteristic data transmitted from each of the vehicles C1, . . . , the processor 32 temporarily stores the driving characteristic data for each acquired vehicle ID in the memory 33. Further, when the processor 32 acquires the vehicle ID and the driver's biometric information transmitted from each of the vehicles C1,..., the processor 32 registers (stores) the acquired driver's biometric information in the driving characteristic table TB1. It is determined whether or not the driver corresponding to the obtained biometric information has been registered.

The processor 32 has already registered the driver corresponding to the acquired biometric information (that is, the acquired biometric information of the driver is compared with the biometric information registered (stored) in the driving characteristics table TB1). If it is determined that this biometric information is determined, the driver's license ID linked to this biometric information is specified. The processor 32 associates the specified license ID with the acquired vehicle ID and driving characteristic data and records them in the driving characteristic table TB1. Thereby, the processor 32 can record and manage driving characteristic data for each license ID (that is, driver).

Further, the processor 32 acquires a control command requesting a driving evaluation for a predetermined driver and the license ID or biometric information corresponding to the predetermined driver, which are transmitted from the wireless terminal device P1. The processor 32 compares the acquired license ID or biometric information with the license IDs or biometric information of a plurality of drivers registered in the driving characteristic table TB1. Based on the verification result, the processor 32 evaluates the driver's driving using the driver's driving characteristic data corresponding to the driver's license ID or biometric information included in the control command. The processor 32 generates a driving evaluation result and transmits it to the wireless terminal device P1.

Similarly, the processor 32 acquires a control command requesting a driving evaluation for a predetermined driver sent from the license server S2, and the license ID or biometric information corresponding to the predetermined driver. The processor 32 compares the acquired license ID or biometric information with the license IDs or biometric information of a plurality of drivers registered in the memory 33. Based on the verification result, the processor 32 evaluates the driver's driving using the driver's driving characteristic data corresponding to the driver's license ID or biometric information included in the control command. The processor 32 generates a driving evaluation result and sends it to the license server S2.

The memory 33 includes, for example, a RAM as a work memory used when the processor 32 executes each process, and a ROM that stores programs and data that define the operations of the processor 32. Note that the memory 33 may have a storage device including either a storage device such as an SSD or an HDD. Data or information generated or acquired by the processor 32 is temporarily stored in the RAM. A program that defines the operation of the processor 32 is written in the ROM. The memory 33 stores the driving characteristic table TB1 generated by the processor 32.

Note that the memory 33 may store driving characteristic data of driving for a predetermined period or a predetermined number of times for each driver. Note that the predetermined period here is, for example, the most recent six months, the most recent 50 times, etc. Further, one drive is a drive performed between the timing when the driver's boarding of the vehicle C1, . . . is detected and the timing when the driver's alighting is detected.

In such a case, if the processor 32 determines that there is driving characteristic data that has been accumulated for a predetermined period or longer among a plurality of driving characteristic data that have been accumulated in association with the same license ID, the processor 32 determines that there is driving characteristic data that has been accumulated for a predetermined period or longer. Delete the driving characteristic data that is currently in use. In addition, if the processor 32 determines that there is driving characteristic data for driving the most recent predetermined number of times or more among the driving characteristic data stored in association with the same license ID, the processor 32 determines that there is driving characteristic data for driving the most recent predetermined number of times or more. Delete characteristic data. Thereby, the driving characteristic server S1 can preferentially accumulate driving characteristic data that can evaluate the most recent change in the driving skill of the driver.

Next, with reference to FIG. 4, the internal configuration of the license server S2 in the first embodiment will be described. FIG. 4 is a block diagram showing an example of the internal configuration of the license server S2 in the first embodiment. In the following explanation, in order to make the explanation easier to understand, various data or information collected (recorded) and managed by the license server S2 will be explained using the license table TB2 as an example. is not required and may be omitted.

The license server S2 includes a communication section 41, a processor 42, and a memory 43.

The communication unit 41 is connected to the driving characteristic server S1 and the wireless terminal device P1 via the network NW so as to be able to transmit and receive data, respectively. In addition, when the wireless terminal device P1 is realized by the car navigation device 12, the communication unit 41 can transmit and receive data to and from the car navigation device 12 installed in each of the vehicles C1, . . . via the network NW. May be connected.

The processor 42 is configured using, for example, a CPU, a DSP, or an FPGA, and controls the operations of each section. The processor 42 cooperates with the memory 43 to perform various types of processing and control in an integrated manner. Specifically, the processor 42 references programs and data held in the memory 43 and executes the programs to realize the functions of each part.

The processor 42 receives, for example, the license IDs of each of the plurality of drivers transmitted from each of the wireless terminal devices P1 owned by the driver, a police officer, an employee of an insurance company, etc., and information regarding the driver (for example, the driver). The person's name, address, facial image data as an example of biometric information, etc.) are acquired. The processor 42 creates a license table TB2 by linking the acquired license ID with information regarding the driver corresponding to the license ID. The processor 42 stores the generated license table TB2 in the memory 43.

The license table TB2 links information about the driver (in the example shown in FIG. 4, the driver's name and address) and the driver's biometric information (in the example shown in FIG. 4, the driver's facial image) to the license ID. Attach, record, and manage information. Note that the information linked to the license ID in the license table TB2 is not limited to the example shown in FIG. good.

For example, the license table TB2 shown in FIG. The driver's name "△△□", address "***", and facial image data are linked to the ID "BBB", and the driver's name "○△×" is linked to the driver's license ID "CCC". ”, the address “＊＊＊”, and the facial image data are linked and recorded.

Further, the processor 42 acquires a control command requesting a driving evaluation of a predetermined driver and a license ID corresponding to the predetermined driver transmitted from the wireless terminal device P1. The processor 42 generates a control command requesting a driving evaluation for a predetermined driver, links the generated control command with the acquired license ID, and transmits the link to the driving characteristics server S1. When the processor 42 acquires the driving evaluation result of a predetermined driver transmitted from the driving characteristic server S1 via the communication unit 41, the processor 42 transmits the acquired driving evaluation result to the wireless terminal device P1.

The memory 43 includes, for example, a RAM as a work memory used when the processor 42 executes each process, and a ROM that stores programs and data that define the operations of the processor 42. Note that the memory 43 may have a storage device including either a storage device such as an SSD or an HDD. Data or information generated or acquired by the processor 42 is temporarily stored in the RAM. A program that defines the operation of the processor 42 is written in the ROM. The memory 43 stores the license table TB2 generated by the processor 42.

Next, with reference to FIG. 5, a driver initial registration procedure executed by the driving characteristics management system 100 will be described. FIG. 5 is a sequence diagram illustrating an example of the initial driver registration procedure of the driving characteristic management system 100 according to the first embodiment. Note that in the following description, an example will be described in which a front face image, a left-facing face image, and a right-facing face image of the driver are used as the driver's biometric information, but it goes without saying that the present invention is not limited to this.

A driver, who is an example of a user who uses the driving characteristics management system 100, operates the car navigation device 12 and selects (presses) an initial registration button (not shown) displayed on the display unit 12C to input information. An operation for requesting initial registration is performed via the unit 12D (St101).

The car navigation device 12 causes the in-vehicle camera 13 to capture a facial image (an example of biological information) of the driver based on the driver's operation accepted by the input unit 12D. The in-vehicle camera 13 is controlled by the car navigation device 12 and captures an image of the driver's face (St102). Further, the in-vehicle camera 13 captures an image of the driver's driver's license (an example of a license ID) held up within the field of view of the in-vehicle camera 13 by the driver (St103). The in-vehicle camera 13 links the captured facial image of the driver with the driver's license ID and transmits it to the car navigation device 12 (St104).

The car navigation device 12 links the driver's facial image, license ID, and vehicle ID of the own vehicle (St105). Note that the vehicle ID linked here may be vehicle license plate information input by the driver into the input unit 12D or stored in the car navigation device 12, information by which the own vehicle can be identified, or the like. The car navigation device 12 transmits the linked driver's face image, license ID, and own vehicle ID (initial registration data), and a control command requesting initial registration (initial registration request) to a communication device. 11 to the driving characteristics server S1 (St106).

The driving characteristics server S1 receives the initial registration data transmitted from the car navigation device 12 and a control command requesting initial registration (St107).

Based on the control command requesting initial registration, the driving characteristic server S1 compares the front face image of the driver reflected in the acquired license ID with the registered face image (St108). If the driving characteristics server S1 determines that the front face image of the driver reflected in the license ID matches the registered face image (that is, they are the same driver), the driver's face image and The driver's license ID and vehicle ID are linked and registered (stored) in the memory 33, thereby completing the initial registration of the driver (St109). After completing the initial registration, the driving characteristic server S1 generates an initial registration completion notification indicating that the initial registration has been completed, and transmits it to the communication device 11 via the network NW (St110).

The car navigation device 12 outputs the initial registration completion notification transmitted from the driving characteristic server S1 to the display unit 12C via the communication device 11, and notifies the driver of the completion of the initial registration (St111).

Note that the driving characteristics server S1 compares the license IDs of the multiple registered drivers with the acquired license ID or face image, and as a result of the collation, the license IDs of the multiple registered drivers. Only when it is determined that the obtained driver's license ID or face image does not match (that is, the same driver is not registered), the process of step St108 may be executed to perform initial registration. . When the driving characteristics server S1 determines that the license IDs of multiple registered drivers are matched with the acquired license ID or face image (that is, the same driver is registered), The initial registration may be completed by recording the acquired vehicle ID in association with the registered license ID.

As described above, the driving characteristic management system 100 according to the first embodiment can manage the registration (storage) of the driver's license ID and the vehicle ID in association with each other.

Next, with reference to FIG. 6, the initial driver registration procedure executed in each of the vehicles C1, . . . will be described. FIG. 6 is a flowchart illustrating an example of the initial registration procedure for the driver in the vehicle C1, .

Each of the vehicles C1, . . . determines whether there is an operation on the input unit 12D of the car navigation device 12 to request initial registration of the driver (St11).

If each of the vehicles C1,... determines in the process of step St11 that there is an operation requesting initial registration of the driver (St11, YES), each of the vehicles C1,... generates a screen showing the initial registration procedure and displays the car navigation device 12. It is output and displayed on the display section 12C (St12). The screen showing the initial registration procedure here shows the procedure for acquiring the vehicle ID driven by the driver, the driver's license ID, and the driver's biometric information, which are examples of initial registration data. 1 or more screens.

On the other hand, in the process of step St11, each of the vehicles C1, .

Each of the vehicles C1, . . . registers a vehicle ID (St13), registers a license ID (St14), and registers a face image (St15). Each of the vehicles C1, . . . determines whether or not the respective processes of steps St13 to St15 (that is, initial registration) are all completed (St16).

If each of the vehicles C1,... determines in the process of step St16 that the processes of steps St13 to St15 (that is, initial registration) are all completed (St16, YES), the initial registration procedure shown in FIG. 6 is performed. end.

On the other hand, in the process of step St16, each of the vehicles C1, ..., if it is determined that the processes of steps St13 to St15 (that is, initial registration) are not all completed (St16, NO), the process of step St12 is performed. The process moves to display the initial registration procedure corresponding to the uncompleted steps St13 to St15, and only the uncompleted processes corresponding to steps St13 to St15 are executed again. For example, if the process of step St13 is not completed for each of the vehicles C1,..., the initial registration procedure corresponding to the process of step St13 (vehicle ID registration process) is displayed, and the process of step St13 (vehicle ID registration process) is displayed. ID registration process) is executed again.

Next, with reference to FIG. 7, the initial driver registration procedure executed in each of the vehicles C1, . . . will be described. FIG. 7 is a flowchart showing an example of a vehicle ID registration procedure for vehicles C1, . Specifically, FIG. 7 is a flowchart showing the process of step St13 shown in FIG.

The car navigation device 12 outputs images, videos, audio, etc. corresponding to the vehicle ID registration procedure recorded in the memory 12B to the display unit 12C (St131).

Each of the vehicles C1, . . . acquires the vehicle ID of its own vehicle by performing any one of steps St132A, St132B, and St132C shown below (St132).

The car navigation device 12 accepts input of a vehicle ID (for example, vehicle license plate information, etc.) to the input unit 12D by the driver's operation (St132A).

The ECU 16 acquires the vehicle ID of the host vehicle recorded in the memory 15 (St132B).

The in-vehicle camera 13 captures an image of the vehicle inspection certificate of the own vehicle that is held within the field of view by the driver, and outputs the captured image of the vehicle inspection certificate to the processor 12A of the car navigation device 12. The car navigation device 12 analyzes the output captured image of the vehicle inspection certificate and acquires the vehicle ID shown in the captured image (St132C).

The acquired vehicle ID is output to the communication device 11. The communication device 11 transmits the output vehicle ID to the driving characteristic server S1 via the network NW (St133).

Next, with reference to FIG. 8, the initial driver registration procedure executed in each of the vehicles C1, . . . will be described. FIG. 8 is a flowchart showing an example of a procedure for registering a driver's license ID in the vehicle C1, . Specifically, FIG. 8 is a flowchart showing the process of step St14 shown in FIG.

The car navigation device 12 outputs images, videos, audio, etc. corresponding to the license ID registration procedure recorded in the memory 12B to the display unit 12C (St141).

The car navigation device 12 receives an input of a license ID (for example, vehicle license plate information, etc.) to the input unit 12D by the driver's operation (St142). Note that the process of step St142 is not essential and may be omitted. In such a case, the processor 12A of the car navigation device 12 or the driving characteristics server S1 acquires the license ID by analyzing the captured image of the driver's license captured in the process of step St143.

The in-vehicle camera 13 captures an image of the driver's driver's license held up within the viewing angle by the driver (St143). The in-vehicle camera 13 outputs the captured image of the driver's license to the processor 12A of the car navigation device 12. The car navigation device 12 associates the output captured image of the driver's license with the input license ID and outputs it to the communication device 11. The communication device 11 transmits the captured image of the driver's license output from the car navigation device 12 and the license ID to the driving characteristics server S1 (St144). Note that if the process in step St142 is omitted, the communication device 11 transmits the captured image of the driver's license output from the car navigation device 12 to the driving characteristics server S1.

Next, with reference to FIG. 9, the initial driver registration procedure executed in each of the vehicles C1, . . . will be described. FIG. 9 is a flowchart showing an example of a procedure for registering a driver's face image in the vehicle C1, . Specifically, FIG. 9 is a flowchart showing the process of step St15 shown in FIG.

The car navigation device 12 outputs images, video, audio, etc. corresponding to the facial image registration procedure recorded in the memory 12B to the display unit 12C (St151). The car navigation device 12 controls the in-vehicle camera 13 to start capturing images.

The in-vehicle camera 13 captures an image of the driver's driver's license presented by the driver within the field of view of the in-vehicle camera 13. Here, the in-vehicle camera 13 captures the entire area of the driver's license, for example, the face image of the driver written on the driver's license and various information written on the driver's license (for example, the driver's name information). , address information, nationality information, effective date information, number information, type information, etc.) are captured within the angle of view (St152). The in-vehicle camera 13 outputs the captured image of the driver's license to the processor 12A.

Note that when the driver's license ID is input in step St142, only the driver's face image that appears on the driver's license may be captured, or the driver's face image and the driver's face image in the process of step St143 may be captured. When capturing images of various information written on a driver's license, the process of step St152 may be omitted. Further, the determination as to whether or not the driver's face image and various information written on the driver's license are reflected in the captured image of the driver's license may be executed by the driving characteristic server S1. , may be executed by the processor 12A of the car navigation device 12.

The in-vehicle camera 13 captures an image of the driver's face facing forward (St153), and outputs the captured front face image F11 to the processor 12A. The in-vehicle camera 13 captures an image of the driver's face facing to the right with respect to the in-vehicle camera 13 located in front of the driver (St154), and outputs the captured right-facing face image F12 to the processor 12A. . The in-vehicle camera 13 captures an image of the driver's face facing to the left with respect to the in-vehicle camera 13 located in front of the driver (St154), and outputs the captured left-facing face image F13 to the processor 12A. .

The car navigation device 12 outputs each of the captured image of the driver's license, the front face image F11, the right face image F12, and the left face image F13 output from the in-vehicle camera 13 to the communication device 11, and sends them to the driving characteristic server S1. It is transmitted (St155).

Next, with reference to FIG. 10, a driver initial registration procedure executed by the driving characteristics server S1 will be described. FIG. 10 is a flowchart illustrating an example of an initial registration procedure for a driver in the driving characteristic server S1.

The driving characteristic server S1 in the driving characteristic management system 100 determines whether a control command requesting initial registration has been obtained from each of the vehicles C1, . . . (St21).

If the driving characteristic server S1 determines in the process of step St21 that a control command requesting initial registration has been acquired from each of the vehicles C1,... (St21, YES), the driving characteristics server S1 acquires the initial registration data linked to the control command. Execute the registration process. Note that the initial registration data here includes, for example, the vehicle ID of the vehicle, the driver's license ID, and the driver's biometric information (here, multiple facial images of the driver in three different directions). (3 face images taken from each of the above), but it goes without saying that the data is not limited to this.

On the other hand, if the driving characteristic server S1 determines in the process of step St21 that the control command requesting initial registration has not been acquired from each of the vehicles C1,... (St21, NO), the driving characteristic server S1 performs the initial registration procedure shown in FIG. end.

The driving characteristics server S1 executes vehicle ID registration (St22), license ID registration (St23), and facial image registration (St24). The driving characteristic server S1 determines whether all the processes (ie, initial registration) of steps St22 to St24 have been completed (St25).

If the driving characteristics server S1 determines in the process of step St25 that each process of steps St22 to St24 (that is, initial registration) has been completed (St25, YES), the driving characteristics server S1 ends the initial registration procedure shown in FIG. do.

On the other hand, if the driving characteristics server S1 determines in the process of step St25 that each process of steps St22 to St24 (that is, initial registration) has not been completed (St25, NO), the driving characteristic server S1 performs the process of step St21. The initial registration procedure corresponding to the uncompleted steps St22 to St24 is displayed, and only the uncompleted processes corresponding to steps St22 to St24 are executed again. For example, if the process of step St22 is not completed, each of the vehicles C1,... displays the initial registration procedure corresponding to the process of step St22, and repeats the vehicle ID registration process of step St22. Execute.

Next, with reference to FIG. 11, a driver initial registration procedure executed by the driving characteristics server S1 will be described. FIG. 11 is a flowchart showing an example of a vehicle ID registration procedure in the driving characteristics server S1. Specifically, FIG. 11 is a flowchart showing the process of step St22 shown in FIG.

The driving characteristic server S1 receives and acquires the vehicle ID transmitted from each of the vehicles C1, . . . (St221).

The driving characteristic server S1 analyzes the acquired vehicle ID (St222), and determines whether the analyzed vehicle ID is valid as the initially registered vehicle ID (St223). For example, when the acquired vehicle ID is a captured image, the driving characteristics server S1 performs image analysis to analyze whether the vehicle ID is based on the vehicle inspection certificate or the license plate, or If the vehicle ID is character information input by the driver's operation, it is analyzed whether the character information is included in the vehicle inspection certificate or the license plate. If the driving characteristic server S1 determines that the analysis result is information that can be used as a vehicle ID, it determines that the vehicle ID is valid.

If the driving characteristic server S1 determines in the process of step St223 that the analyzed vehicle ID is valid as the initially registered vehicle ID (St223, YES), it generates a new user ID and The user ID and vehicle ID are linked and registered or temporarily stored (St224). Note that in the process of step St224, generation of the user ID is not essential and may be omitted.

On the other hand, if the driving characteristic server S1 determines in the process of step St223 that the analyzed vehicle ID is not valid as the initially registered vehicle ID (St223, NO), it issues a control command requesting retransmission of the vehicle ID. It is generated and transmitted (notified) to the vehicle via the network NW (St225).

After registering the vehicle ID, the driving characteristics server S1 generates a control command to notify the completion of registration of the vehicle ID, and transmits it to the vehicle via the network NW (St226). Note that the process of step St226 may be executed simultaneously with the processes of step St234 (see FIG. 12) and step St249 (see FIG. 13).

Next, with reference to FIG. 12, a driver initial registration procedure executed by the driving characteristics server S1 will be described. FIG. 12 is a flowchart showing an example of a license ID registration procedure in the driving characteristic server S1. Specifically, FIG. 12 is a flowchart showing the process of step St23 shown in FIG.

The driving characteristic server S1 receives and acquires the driver's license ID transmitted from each of the vehicles C1, . . . (St231).

The driving characteristics server S1 stores various information about the driver's license corresponding to the acquired license ID (for example, the driver's face image, name information, address information, nationality information, and expiration date written on the driver's license). information, number information, type information, etc.) and sends it to the license server S2. The driving characteristics server S1 acquires various information on the driver's license corresponding to the license ID transmitted from the license server S2 (St232A). Note that the process in step St232A is performed when it is not possible to acquire the facial images written on the driver's license from each of the vehicles C1, ..., or when the acquired facial images and the facial images of the drivers registered in the driving characteristics table TB1 are combined. This may be executed when, for example, there is no match.

The driving characteristic server S1 determines whether the acquired license ID is valid (St232B). Specifically, when the acquired license ID is a captured image of a driver's license, the driving characteristics server S1 checks whether various information can be read from the captured image or whether the driver's license is recognized by character recognition. The driver is identified by determining whether or not the expiration date has expired, and by comparing the driver's facial image included in the acquired license ID with the driver's facial image registered in the driving characteristics table TB1. Determine whether or not it is possible.

If the driving characteristics server S1 determines that the acquired license ID is valid after the process of step St232A or in the process of step St232B (St232B, YES), the driving characteristics server S1 registers the acquired license ID ( St233). Note that if the driving characteristic server S1 determines that the license ID is already registered in the driving characteristic table TB1, the driving characteristic server S1 may omit the license ID registration process in step St233.

On the other hand, if the driving characteristic server S1 determines in the process of step St232B that the acquired license ID is not valid (St232B, NO), it generates a control command requesting retransmission of the license ID, and connects the network NW. The information is transmitted (notified) to the vehicle via the vehicle (St232C). In addition, in the process of step St232A, the driving characteristic server S1 may similarly execute the process of step St232C even if various information on the driver's license cannot be acquired from the license server S2.

After registering the license ID, the driving characteristic server S1 generates a control command to notify the completion of registration of the license ID, and transmits (notifies) the control command to the vehicle via the network NW (St234). Note that the process in step St234 may be executed simultaneously with the processes in step St226 (see FIG. 11) and step St249 (see FIG. 13).

Next, with reference to FIG. 13, a driver initial registration procedure executed by the driving characteristics server S1 will be described. FIG. 13 is a flowchart showing an example of a facial image registration procedure in the driving characteristics server S1. Specifically, FIG. 13 is a flowchart showing the process of step St24 shown in FIG.

The driving characteristic server S1 receives and acquires the captured image of the driver's license transmitted from each of the vehicles C1, . . . (St241). Further, the driving characteristics server S1 receives and acquires each of the front face image, the left-facing face image, and the right-facing face image (an example of biological information) transmitted from each of the vehicles C1, . . . (St242).

The driving characteristic server S1 performs face matching between the driver's face image shown in the captured image of the driver's license and the front face image, and compares the driver's face image shown in the captured image of the driver's license with the front face image. , it is determined whether the acquired front face image is the same or similar (that is, whether they are the same person) (St243).

In the process of step St243, the driving characteristic server S1 determines that the driver's face image reflected in the captured image of the driver's license and the acquired front face image are the same or similar (that is, they are the same person). If so (St243, YES), face verification is performed using this frontal face image and each of the left-facing face image and the right-facing face image (St244).

On the other hand, if the driving characteristic server S1 determines in the process of step St243 that the driver's face image and the frontal face image reflected in the captured image of the driver's license are the same or similar (that is, they are not the same person) (St243 , NO), a control command requesting re-imaging (that is, re-imaging) of the driver's license image or front face image is generated and transmitted (notified) to the vehicle via the network NW (St245).

The driving characteristics server S1 determines whether the face shown in the frontal face image and the faces shown in each of the left-facing face image and the right-facing face image are the same or similar (that is, they are the same person) (St246).

When the driving characteristic server S1 determines in the process of step St246 that the face shown in the frontal face image and the faces shown in each of the left-facing face image and the right-facing face image are the same or similar (that is, they are the same person). (St246, YES), in the process of step St232B, the captured image of the driver's license and each of the frontal face image, left-facing face image, and right-facing face image are linked to the license ID determined to be valid. and record it (St247).

On the other hand, in the process of step St246, the driving characteristic server S1 determines that the face shown in the frontal face image and the faces shown in each of the left-facing face image and the right-facing face image are the same or not similar (that is, they are not the same person). (St246, NO), generates a control command requesting re-imaging (that is, re-imaging) of each of the captured image of the driver's license, the frontal face image, the left-facing face image, and the right-facing face image, and sends the captured image via the network NW. and transmits (notifies) the vehicle (St248).

The driving characteristics server S1 registers each of the plurality of facial images as an example of biometric information by linking them to the driver's license ID, and then generates a control command to notify the completion of registration of the facial images, and via the network NW, The information is transmitted (notified) to the vehicle (St249). Note that the process in step St249 may be executed simultaneously with the processes in step St226 (see FIG. 11) and step St234 (see FIG. 12).

Next, with reference to FIG. 14, a description will be given of a procedure for collecting the driver's driving characteristic data, which is executed by the driving characteristic management system 100. FIG. 14 is a sequence diagram illustrating an example of a driver's driving characteristic data collection procedure in the driving characteristic management system 100 according to the first embodiment. Note that in the following description, an example will be described in which a front face image, a left-facing face image, and a right-facing face image of the driver are used as the driver's biometric information, but it goes without saying that the present invention is not limited to this.

Furthermore, the driving characteristic data collection procedure described with reference to each of FIGS. 14 to 16 is a process executed after the initial registration is completed or when the driver drives the vehicle C1 that has been initially registered in advance. be. Note that the procedure for collecting driving characteristic data is the same for other vehicles.

The driver gets on the vehicle C1 (St301). The ECU 16 of the vehicle C1 detects the driver's boarding based on whether one or more or two or more driver's boarding detection conditions are satisfied (St302). The ECU 16 generates a control command indicating that the driver's boarding is detected and outputs it to the processor 12A of the car navigation device 12, and starts sensing (obtaining) the driver's driving characteristic data. The car navigation device 12 starts sensing (obtaining) the driver's driving characteristic data based on the control command output from the ECU 16 .

The driving characteristic data may be obtained from various sensors (for example, the inside camera 13, the gyro sensor 14, the accelerator pedal 17A, the brake pedal 17B, the turn lamp 17C, the steering wheel 17D, the speed sensor 18, the outside sensor/camera 19, or the GPS sensor 20, etc.). 2)) and output to the car navigation device 12 or ECU 16.

The ECU 16 outputs the acquired driving characteristic data of the driver to the car navigation device 12. The car navigation device 12 associates the acquired one or more driving characteristic data with the vehicle ID and outputs it to the communication device 11 (St304). The communication device 11 transmits one or more linked driving characteristic data and the vehicle ID to the driving characteristic server S1 via the network NW (St305).

The driving characteristics server S1 receives the driving characteristics data and vehicle ID transmitted from the communication device 11, and temporarily stores them (St306).

The vehicle C1 also captures an image of the driver's face using the in-vehicle camera 13 (St307). The in-vehicle camera 13 outputs the captured facial image to the car navigation device 12. The car navigation device 12 associates one or more facial images captured by the in-vehicle camera 13 with the vehicle ID and outputs the result to the communication device 11 (St308). The communication device 11 transmits the linked facial images of one or more drivers and the vehicle ID to the driving characteristic server S1 via the network NW (St309).

Note that the facial images captured in the process of step St307 include a plurality of facial images in which the driver's face is captured facing two or more different directions (for example, a frontal facial image, a left-facing facial image, and a right-facing facial image of the driver). Although it is desirable that the image be any two or more facial images among the facial images, it is sufficient if it is at least one frontal facial image. Further, the determination of the direction of the driver's face reflected in the face image may be executed by the driving characteristics server S1.

The driving characteristic server S1 receives and acquires the vehicle ID and the driver's face image transmitted from the communication device 11 (St310). The driving characteristic server S1 performs face matching on the acquired driver's facial images, and compares the facial images of multiple drivers registered in the driving characteristic table TB1 (for example, the facial image shown in the captured image of the driver's license). It is determined whether there is a face image that is the same as or similar to the acquired face image of the driver (St311).

The driving characteristic server S1 selects a driver corresponding to a face image that is the same as or similar to the acquired driver's face image from among the plurality of driver's face images registered in the driving characteristic table TB1. Identify the driver corresponding to the image. Further, the driving characteristic server S1 extracts, from among the temporarily stored driving characteristic data, driving characteristic data linked to the same vehicle ID as the vehicle ID linked to the driver's face image. The driving characteristic server S1 records (saves) the extracted driving characteristic data in association with the identified driver's license ID (St312).

After the driver finishes driving, the driver gets off the vehicle (St313). The ECU 16 of the vehicle C1 detects the driver's alighting based on whether one or more or two or more driver alighting detection conditions are satisfied (St314). The ECU 16 generates a control command indicating that the driver has exited the vehicle, outputs it to the processor 12A of the car navigation device 12, and ends sensing (obtaining) the driver's driving characteristic data. The car navigation device 12 finishes sensing (obtaining) the driver's driving characteristic data based on the control command output from the ECU 16.

The communication device 11 continues to transmit the driving characteristic data acquired by the car navigation device 12 or the ECU 16 to the driving characteristic server S1 over a period T1 from step St302 to step St314. The driving characteristic server S1 continues to record the driving characteristic data acquired during the period T1 from the communication device 11 in the driving characteristic table TB1 in association with the driver's license ID.

When the license server S2 acquires the control command requesting the driving evaluation of a predetermined driver transmitted from the wireless terminal device P1 (St315), the license server S2 receives the control command requesting the driving evaluation of the predetermined driver and the license ID. and is sent to the driving characteristics server S1 (St316).

The driving characteristics server S1 acquires the control command and license ID transmitted from the license server S2. Based on the acquired control command, the driving characteristic server S1 compares the license IDs of a plurality of drivers already registered in the driving characteristic table TB1 with the acquired license ID of a predetermined driver. The driving characteristic server S1 executes a driving evaluation of a predetermined driver using the driving characteristic data linked to the verified license ID (St317). The driving characteristic server S1 transmits the driving evaluation result to the license server S2 (St318).

The license server S2 acquires the driving evaluation result transmitted from the driving characteristics server S1 (St319). The license server S2 records the information in association with the license ID registered in the license table TB2 and transmits it to the wireless terminal device P1. Note that the wireless terminal device P1 may be realized by the car navigation device 12. Note that the driving evaluation process for a predetermined driver may be executed by the license server S2. In such a case, the license server S2 acquires driving characteristic data used for driving evaluation from the driving characteristic server S1.

Next, with reference to FIG. 15, a driver driving characteristic data acquisition procedure executed in each of the vehicles C1, . . . will be described. FIG. 15 is a flowchart illustrating an example of a procedure for acquiring driving characteristic data of the driver in the vehicle C1, .

Each of the vehicles C1, . . . determines whether or not a driver entering the driver's seat is detected (St31). When each of the vehicles C1,... determines that the driver's boarding is detected in the process of step St31 (St31, YES), each of the vehicles C1, . . . starts acquiring driving characteristic data of the driver using various sensors (St32).

On the other hand, if each of the vehicles C1,... determines in the process of step St31 that the driver's boarding is not detected (St31, NO), the process returns to step St31, and the driver's boarding is detected in the driver's seat. Continue detection.

Each of the vehicles C1, . . . captures an image of the driver's face using the in-vehicle camera 13 (St33). The face images captured here are preferably the front face image F21, the right face image F22, and the left face image F23, but are not limited thereto.

Each of the vehicles C1, . , is transmitted to the driving characteristic server S1 (St34).

Each of the vehicles C1, . . . determines whether or not the exit of the driver from the driver's seat is detected (St35). If each of the vehicles C1,... determines in the process of step St35 that the driver's getting out of the vehicle is detected (St35, YES), each of the vehicles C1,... finishes acquiring the driver's driving characteristic data using the various sensors, and returns to the state shown in FIG. The procedure for acquiring driving characteristic data of the driver shown in FIG. Note that when each of the vehicles C1,... detects that the driver has exited the vehicle, it generates a control command to notify that the driver has finished driving, and links the generated control command with the vehicle ID. It may also be transmitted to the driving characteristic server S1.

On the other hand, if each of the vehicles C1,... determines in the process of step St35 that the driver's alighting is not detected (St35, NO), the process returns to step St21, and the driver's driving characteristics determined by various sensors are detected. Continue data acquisition. Note that the process in step St33 may be omitted after the driver identification process (step St44) by the driving characteristics server S1 is completed.

Next, with reference to FIG. 16, a driver's driving characteristic data collection procedure executed by the driving characteristic server S1 will be described. FIG. 16 is a flowchart showing an example of a procedure for collecting driver's driving characteristic data in the driving characteristic server S1.

The driving characteristic server S1 determines whether or not the vehicle ID, one or more driving characteristic data, and one or more facial images transmitted from each of the vehicles C1, . . . are received (St41).

When the driving characteristic server S1 determines in the process of step St41 that it has received the vehicle ID, one or more driving characteristic data, and one or more face images transmitted from each of the vehicles C1,... (St41 , YES), the driving characteristic data is temporarily stored in the memory 43 for each vehicle ID (St42).

On the other hand, in the process of step St41, the driving characteristic server S1 determines that it has not received the vehicle ID, one or more driving characteristic data, and one or more facial images transmitted from each of the vehicles C1,... If so (St41, NO), the process returns to step St41.

The driving characteristic server S1 performs face verification of the acquired face image of the driver (St43). The driving characteristic server S1 selects a facial image that is the same or similar to the acquired driver's facial image from among the plurality of facial images of drivers registered in the driving characteristic table TB1 (for example, facial images reflected in a captured image of a driver's license). Based on whether or not there is a face image that is the same as or similar to the acquired face image of the driver, the driver's license ID associated with the face image that is the same as or similar to the acquired face image of the driver is specified (St44).

Note that, before the process in step St43, the driving characteristic server S1 compares the vehicle ID transmitted from each of the vehicles C1, . . . with each of the plurality of vehicle IDs registered in the driving characteristic table TB1. , one or more driver's license IDs linked to the verified vehicle ID may be extracted. As a result, in the process of step St44, the driving characteristic server S1 reduces the number of driver's face images that have been registered in the driving characteristic table TB1 and is compared with the acquired driver's face image, and The matching accuracy of matching can be improved.

If the driving characteristic server S1 determines in the process of step St44 that there is a face image that is the same as or similar to the acquired face image of the driver, the driving characteristics server S1 performs a search based on the driver's license ID linked to this face image. Then, it is determined that the driver corresponding to the acquired face image has been identified (St44, YES). The driving characteristic server S1 records (accumulates) the acquired driving characteristic data in association with the specified license ID in the driving characteristic table TB1 (St45).

On the other hand, if the driving characteristic server S1 determines in the process of step St44 that there is no face image that is the same as or similar to the acquired face image of the driver, the driving characteristic server S1 identifies the driver's license ID linked to this face image. Based on this, it is determined that the driver corresponding to the acquired face image cannot be identified (St44, NO). The driving characteristic server S1 determines whether a control command to notify the end of driving has been received from each of the vehicles C1, . . . (St46).

If the driving characteristic server S1 determines in the process of step St46 that a control command to notify the end of driving has been received from each of the vehicles C1,... (St46, YES), the driving characteristic server S1 stores the acquired facial image and one or more and the driving characteristic data of the vehicle, and are temporarily stored for each vehicle ID (St47A). The driving characteristic server S1 executes the process of step St44 again on the same day or at a later date using the newly acquired facial image. If the driving characteristics server S1 determines that the driver's license ID has been identified, the driving characteristics server S1 records the temporarily stored driving characteristics data associated with the same vehicle ID in association with the identified license ID ( accumulation) (St47A). Thereby, the driving characteristic server S1 can accumulate temporarily saved driving characteristic data even if the initial registration of the license ID is not completed.

In addition, in the process of step St46, if the driving characteristics server S1 determines that a control command to notify the end of driving has been received from each of the vehicles C1,... (St46, YES), the driving characteristic server S1 links the driving characteristics to the same vehicle ID. The generated driving characteristic data is discarded (deleted) (St47B).

The driving characteristic server S1 determines whether or not it has received one or more driving characteristic data and one or more facial images linked to the vehicle ID whose license ID has been specified from each of the vehicles C1,... (St48).

If the driving characteristic server S1 determines in the process of step St48 that the license ID has received one or more driving characteristic data linked to the specified vehicle ID and one or more facial images (St48 , YES), the acquired driving characteristic data is linked to the specified license ID and recorded (accumulated) in the driving characteristic table TB1 (St45).

On the other hand, if the driving characteristic server S1 determines in the process of step St48 that the driver's license ID does not receive one or more driving characteristic data linked to the specified vehicle ID and one or more facial images. (St48, NO), the driving characteristic server S1 determines whether or not a control command to notify the end of driving has been received from each of the vehicles C1, . . . (St49).

If the driving characteristic server S1 determines in the process of step St49 that a control command to notify the end of driving has been received from each of the vehicles C1, . Finish the data collection procedure.

On the other hand, if the driving characteristic server S1 determines in the process of step St49 that it has not received a control command to notify the end of driving from each of the vehicles C1,... (St49, NO), the driving characteristic server S1 performs the process of step St48. return.

As described above, the method for managing driving characteristic data executed by the driving characteristic server S1, which is an example of one or more computers according to the first embodiment, is based on the biological information (an example of biological information) of a plurality of drivers. Biometric information registered in the characteristic table TB1) and driver's license ID are linked and registered, and driving characteristic data indicating the biological information of the driver who drives the vehicle C1, ... and the driving characteristics of the driver. and if it is determined that there is the same or similar biometric information among the biometric information of multiple registered drivers (biometric information sent from each of the vehicles C1,...), the biometric information is the same or similar. The driver's license ID linked to the biometric information and the driving characteristic data are linked and recorded.

As a result, the driving characteristic server S1 according to the first embodiment can record the driver's driving characteristic data transmitted from each of the vehicles C1,... with the specified license ID in association with the driver's driving characteristic data. Even when driving a plurality of different vehicles, the driver's driving characteristic data can be managed more efficiently. Therefore, in collecting and managing (recording) driving characteristic data used for driving evaluation to determine whether or not to return a driver's license when the driver is elderly, the driving characteristic server S1 uses the driver's license ID. It is possible to more effectively collect and manage (record) driving characteristic data for objectively evaluating the driving operations of corresponding elderly drivers.

Furthermore, as described above, the driving characteristic server S1 according to the first embodiment further acquires biological information, driving characteristic data, and vehicle IDs (an example of vehicle identification information) that can identify each of the vehicles C1, . , If it is determined that there is the same or similar biometric information among the biometric information of multiple registered drivers (biometric information sent from each of the vehicles C1,...), the biometric information that is the same or similar is The linked license ID, driving characteristic data, and vehicle ID are linked and recorded. Thereby, the driving characteristic server S1 according to the first embodiment can identify the vehicle for which the driving characteristic data has been acquired, and objectively evaluate the driving operation of each vehicle of the elderly driver corresponding to the license ID. can collect and manage (record) driving characteristic data more effectively.

In addition, as described above, the driving characteristic server S1 according to the first embodiment is configured to identify biological information that is the same as or similar to the biological information (biometric information transmitted from each of the vehicles C1, ...) among the registered biological information of a plurality of drivers. If it is determined that there is no biometric information, the driving characteristic data and vehicle ID are linked and temporarily stored. As a result, the driving characteristic server S1 according to the first embodiment can link the driving characteristic data transmitted from each of the vehicles C1, ... with the vehicle ID even if the driver cannot be identified using biometric information. By adding this feature, driving characteristic data can be temporarily stored until the driver is identified.

Furthermore, as described above, the driving characteristics server S1 according to the first embodiment further acquires the driving end information of the vehicles C1, . . . , and at the timing of acquiring the driving end information, the driving characteristic server S1 according to the first embodiment If it is determined that there is no biometric information that is the same or similar to the biometric information (biometric information transmitted from each of the vehicles C1, . . . ), the driving characteristic data and the vehicle ID are linked and temporarily stored. As a result, the driving characteristics server S1 according to the first embodiment is able to identify each of the vehicles C1, ... even if identification of the driver using biometric information is not completed at the timing when the driver has finished driving. By linking the transmitted driving characteristic data with the vehicle ID, the driving characteristic data can be temporarily stored until the driver is identified.

In addition, as described above, the driving characteristic server S1 according to the first embodiment is configured to identify biological information that is the same as or similar to the biological information (biometric information transmitted from each of the vehicles C1, ...) among the registered biological information of a plurality of drivers. If it is determined that there is no biometric information, new biometric information of the driver driving the vehicle (new biometric information sent from each vehicle C1,...) is acquired, and biometric information of multiple registered drivers is collected. If it is determined that the new biometric information has the same or similar biometric information, the license ID linked to the same or similar biometric information, the temporarily saved driving characteristics data, and the vehicle ID are linked. and record it. As a result, the driving characteristic server S1 according to the first embodiment acquires new biometric information of the driver from each of the vehicles C1, ... until the driver is identified, and uses the acquired new biometric information. Based on this information, driver identification processing can be repeatedly executed. Therefore, at the timing when the driver corresponding to the driving characteristic data transmitted from each of the vehicles C1, . . . and the vehicle ID can be linked and recorded.

In addition, as described above, the driving characteristic server S1 according to the first embodiment is configured to identify biological information that is the same as or similar to the biological information (biometric information transmitted from each of the vehicles C1, ...) among the registered biological information of a plurality of drivers. If it is determined that there is no biological information, the driving characteristic data is deleted. As a result, the driving characteristic server S1 according to the first embodiment does not record driving characteristic data determined to be unidentifiable by the driver in the memory 33, so that the occurrence of memory shortage in the memory 33 can be more effectively suppressed. .

Furthermore, as described above, the driving characteristics server S1 according to the first embodiment further acquires the driving end information of the vehicles C1, . . . , and at the timing of acquiring the driving end information, the driving characteristic server S1 according to the first embodiment If it is determined that there is no biometric information that is the same or similar to the biometric information (biometric information transmitted from each of the vehicles C1, . . . ), the driving characteristic data is deleted. As a result, the driving characteristic server S1 according to the first embodiment does not record, in the memory 33, the driving characteristic data determined to be unidentifiable at the timing when the driver finishes driving, and therefore the memory 33 is insufficient. The occurrence of can be suppressed more effectively.

Further, as described above, the driving characteristics server S1 according to the first embodiment acquires the biometric information of the driver and the driver's license ID corresponding to the biometric information, and If it is determined that the facial image of the person matches, the biometric information and the driver's license ID are linked and registered. As a result, the driving characteristics server S1 according to the first embodiment uses the driver's biometric information (e.g., face image, iris, etc.) transmitted from each of the vehicles C1... and the driver's face included in the license ID. By registering a new driver's license ID based on the results of matching with the image, it is possible to more effectively prevent impersonation by others.

Furthermore, as described above, the biometric information (registered biometric information) registered in the driving characteristic server S1 according to the first embodiment is facial images of a plurality of drivers. Further, the biometric information (biometric information transmitted from each of the vehicles C1, . . . ) is a facial image of the driver driving the vehicle. As a result, the driving characteristic server S1 according to the first embodiment uses the facial images of the drivers captured and transmitted by each of the vehicles C1,... and the facial images of the drivers registered in advance in the driving characteristic table TB1. The driver can be identified by comparing the face with the facial image. In addition, by using facial images as biometric information, each of the vehicles C1, ... images the driver while driving using the in-vehicle camera 13 without driver operation, and uses the captured facial image of the driver while driving. It can be sent to the characteristic server S1. Therefore, the driving characteristic server S1 repeatedly requests each of the vehicles C1, . Can be executed repeatedly for a period of time.

Further, as described above, the driving characteristics server S1 according to the first embodiment can generate a front face image (an example of a first registered face image) in which the driver's face is facing the front (an example of a first direction), and a driving characteristic server S1 according to the first embodiment. A right-facing face image or a left-facing face image (an example of a second registered face image) in which the person's face is facing right or left (an example of a second direction), which is different from the front, and the driver's license ID are registered in association with each other. , vehicle C1,... A front face image in which the driver's face is facing forward (an example of a first face image), and a right-facing face image (an example of a second face image) in which the driver's face is facing right or left (an example of a second face image) or left-facing. A facial image (an example of a second facial image) and driving characteristic data are acquired, and among the registered frontal facial images (an example of a first registered facial image) of a plurality of drivers, those transmitted from vehicles C1,... A front face image that is the same as or similar to the front face image, and a right face image transmitted from the vehicle C1, among the registered right face images or left face images (an example of a second registered face image) of a plurality of registered drivers. Alternatively, the left-facing face image is compared with a right-facing face image or a left-facing face image that is the same or similar, and there is a front face image that is the same or similar to the front face image transmitted from the vehicle C1,..., and the vehicle C1,... If it is determined that there is a right-facing face image or a left-facing face image that is the same as or similar to the right-facing face image or left-facing face image sent from The linked license ID and driving characteristic data are linked and recorded. As a result, the driving characteristics server S1 according to the first embodiment can receive the front face images of the drivers captured and transmitted by each of the vehicles C1, ... and the front face images of the drivers registered in advance in the driving characteristics table TB1. The driver can be identified by comparing the front face image of the driver. In addition, the driving characteristics server S1 repeatedly requests each of the vehicles C1,... It can be executed repeatedly until then.

Further, as described above, when the driving characteristic server S1 according to the first embodiment determines that there is no front face image that is the same as or similar to the front face image transmitted from the vehicle C1, . A new front face image is acquired, and it is again determined whether there is a front face image that is the same as or similar to the new front face image among the registered front face images of the plurality of drivers. If the driving characteristics server S1 determines that there is no right-facing face image or left-facing face image that is the same as or similar to the right-facing face image or left-facing face image transmitted from the vehicle C1, . Obtain a new right-facing face image or left-facing face image, and select a right-facing face image or a left-facing face image that is the same as or similar to the new right-facing face image or left-facing face image among the registered right-facing face images or left-facing face images of a plurality of registered drivers. It is determined again whether or not there is a face image. As a result, the driving characteristics server S1 according to the first embodiment receives the driver's right-facing face image or left-facing face image that has been captured and transmitted by each of the vehicles C1, . . . The driver can be identified by face-matching images of right-facing faces or left-facing faces of multiple drivers. In addition, the driving characteristics server S1 repeatedly requests each of the vehicles C1, . can be executed repeatedly until the driver is identified. Furthermore, the driving characteristics server S1 according to the first embodiment not only performs face verification using a frontal face image but also performs face verification using a right-facing face image or a left-facing face image. impersonation activities can be more effectively suppressed.

As described above, the car navigation device 10 according to the first embodiment is an on-vehicle device installed in the vehicle C1, and is a communication device 11 that performs data communication with the driving characteristics server S1 (an example of an external device). (an example of a communication unit), an in-vehicle camera 13 (an example of a first acquisition unit) that acquires biometric information of a driver driving the vehicle C1, etc., and a gyro that acquires driving characteristic data indicating the driving characteristics of the driver. It includes a sensor 14 or various sensors (an example of a second acquisition unit), and a processor 12A (an example of a control unit) that connects and outputs biological information and driving characteristic data. The processor 12A outputs the linked biological information and driving characteristic data to the communication device 11, and causes them to be transmitted to the driving characteristic server S1. The various sensors mentioned here include, for example, the in-vehicle camera 13, the accelerator pedal 17A, the brake pedal 17B, the turn lamp 17C, the steering wheel 17D, the speed sensor 18, the out-of-vehicle sensor/camera 19, or the GPS sensor 20 (see FIG. 2). .

Thereby, the car navigation device 10 according to the first embodiment acquires biological information for identifying the driver and driving characteristic data used for driving evaluation, and combines the acquired biological information and driving characteristic data. Since the information is linked and transmitted to the driving characteristic server S1, it is possible to support the management of driving characteristic data for each driver by the driving characteristic server S1 to more effectively collect and manage (record) the driving characteristic data.

Further, as described above, the car navigation device 10 according to the first embodiment further includes the memory 12B (an example of a recording unit) that records a vehicle ID (an example of vehicle identification information) that can identify the vehicles C1, . The processor 12A associates the acquired biometric information, driving characteristic data, and vehicle ID, outputs the linked information to the communication device 11, and causes the communication device 11 to transmit it to the driving characteristic server S1. Thereby, the car navigation device 10 according to the first embodiment acquires biometric information for identifying the driver, driving characteristic data used for driving evaluation, and vehicle ID, and uses the acquired biometric information and driving Since the characteristic data and the vehicle ID are linked and transmitted to the driving characteristics server S1, even if one vehicle C1,... is driven by multiple drivers, the driving characteristics server S1 can identify the driver. This allows for more effective collection and management (recording) of driving characteristic data for each vehicle.

In addition, as described above, the car navigation device 10 according to the first embodiment further includes the processor 12A (an example of a third acquisition unit) that acquires information about the driver getting on or getting off the vehicle C1, . The processor 12A causes the in-vehicle camera 13 to start acquiring biological information and the gyro sensor 14 or various sensors to start acquiring driving characteristic data from the timing when the driver's boarding information is acquired. As a result, the car navigation device 10 according to the first embodiment automatically performs biometric information acquisition processing and driving characteristics from the timing when the driver's boarding information is acquired (that is, the timing at which the driver's boarding is detected). Data acquisition processing can be started. Therefore, the car navigation device 10 can start acquiring driving characteristic data without any operation by the driver, so it is possible to suppress failure to acquire driving characteristic data due to the driver forgetting to perform an operation to start acquiring driving characteristic data. .

Further, as described above, the processor 12A in the car navigation device 10 according to the first embodiment acquires biological information using the in-vehicle camera 13 and driving characteristics using the gyro sensor 14 or various sensors at the timing when the driver's exit information is obtained. Terminate data acquisition. As a result, the car navigation device 10 according to the first embodiment automatically performs biometric information acquisition processing and driving operation at the timing when the driver's alighting information is acquired (that is, at the timing when the driver's alighting is detected). The characteristic data acquisition process can be completed.

Further, as described above, the in-vehicle camera 13 in the car navigation device 10 according to the first embodiment is a camera that captures an image of the driver's face. The biometric information is a facial image of the driver captured by the in-vehicle camera 13. Thereby, the car navigation device 10 according to the first embodiment can image the driver's face using the in-vehicle camera 13 even when the driver is driving, and can acquire the captured image as biological information.

Further, as described above, the processor 12A in the car navigation device 10 according to the first embodiment is configured such that the orientation of the driver's face reflected in the face image captured by the in-vehicle camera 13 is a predetermined orientation (for example, front, right, left, etc.). ), the face image and the driving characteristic data are linked together, outputted to the communication device 11, and transmitted to the driving characteristic server S1. Thereby, the car navigation device 10 according to the first embodiment can select a facial image, and can more effectively suppress an increase in the amount of data communication required for transmitting the facial image to the driving characteristic server S1.

Further, as described above, the communication device 11 in the car navigation device 10 according to the first embodiment receives the designation of the direction of the driver's face shown in the face image from the driving characteristics server S1. When the processor 12A determines that the direction of the driver's face reflected in the face image is the direction of the specified driver's face, the processor 12A associates the face image with the driving characteristic data and outputs it to the communication device 11. , to be transmitted to the driving characteristic server S1. Thereby, the car navigation device 10 according to the first embodiment can select a face image to be used for face verification, and can more effectively suppress an increase in the amount of data communication required for transmitting the face image to the driving characteristics server S1. .

Further, as described above, the car navigation device 10 according to the first embodiment further includes the input unit 12D or the in-vehicle camera 13 (an example of a fourth acquisition unit) that acquires the driver's license ID. The processor 12A associates the acquired biometric information with the vehicle ID and license ID, outputs the linked information to the communication device 11, and causes the communication device 11 to transmit the information to the driving characteristic server S1. As a result, the car navigation device 10 according to the first embodiment links the driver's biometric information, which is the initial registration data necessary for the driver's initial registration process, the vehicle ID, and the license ID, to determine driving characteristics. Can be sent to server S1. Therefore, the driving characteristics server S1 can perform face verification of the driver based on the driver's biometric information and the driver's license ID transmitted from the car navigation device 10 in the vehicle C1, and determines that the face verification has been performed. In this case, the initial registration can be completed by linking the driver's biometric information, vehicle ID, and license ID and registering (storing) them in the driving characteristic table TB1. After this initial registration process, if the driving characteristics server S1 determines that the biometric information sent from the same or another vehicle is the same or similar to the initially registered biometric information, the driving characteristics server S1 determines that the biometric information sent from the same or other vehicle is the same or similar to the initially registered biometric information. The driver corresponding to the biometric information can be identified as the driver corresponding to the license ID linked to the biometric information determined to be the same or similar, and the driving characteristic data transmitted from the same or other vehicles can be identified. By recording the information in association with the driver's license ID, it is possible to collect and manage (record) driving characteristic data for each driver.

(Details leading to Embodiment 2)
In recent years, driving a vehicle has been shown to be effective in reducing the risk of dementia and extending healthy life expectancy among elderly people. This has been shown to help people maintain healthy social participation. Therefore, there is a need for technology that can suppress the increase in accidents caused by driving errors and forgetting to check safety as elderly drivers age, and extend the driving life of elderly drivers.

Conventionally, Patent Document 2 discloses, as a technology for providing driving assistance, whether or not the driver is in a situation that requires safety confirmation based on the relationship between predetermined road parameters of the road on which the vehicle is traveling and the steering angle. A vehicle warning device has been disclosed that determines whether safety confirmation has been carried out and issues a warning to the driver when it is determined that safety confirmation has not been performed. Furthermore, Patent Document 3 states that a driving support device that provides driving support for a driver learns the driving proficiency level of the driver based on the history of the driver's driving operations, and adjusts the degree of driving support based on the driving proficiency level. Driving assistance will be provided as required. However, it is desirable for such a driving support device to perform dynamic driving support corresponding to the driving situation and the driver's condition.

In addition, the driving support device that supports the driver through automatic driving disclosed in Patent Document 4 is based on the environmental difficulty required for the driver's driving operation due to the external environment of the vehicle and the driver's driving operation. Estimates the driver's driving condition relative to the external environment based on driving skill, and determines driving support content (e.g., automatic steering, automatic braking, etc.) based on driving skill and driver's condition (e.g., emotions, psychology, etc.). Select and execute. However, the driving support provided by automated driving has not been able to support the improvement of the driver's own driving characteristics (driving skills, safety checks, etc.).

Therefore, in Embodiment 2 below, an example of a method for managing driving characteristic improvement support data that can more efficiently collect driving characteristic data for each driver and support management of the collected driving characteristic data will be described. In the following description, the same reference numerals are used for the same components as in Embodiment 1, and the description thereof will be omitted.

Note that an example will be described in which the driving characteristic data in the second embodiment includes data indicating the driving characteristics of the driver and data indicating behavioral characteristics (for example, behavioral information such as the driver's body, face, line of sight, etc.). . Further, the driving characteristic evaluation result in the second embodiment indicates the driving skill of the driver, including the safety confirmation actions performed by the driver.

(Embodiment 2)
An example use case of the driving characteristic improvement support system 200 according to the second embodiment will be described with reference to FIG. 17. FIG. 17 is a diagram illustrating an example use case of the driving characteristic improvement support system 200 according to the second embodiment.

The driving characteristic improvement support system 200 is configured to include each of one or more vehicles C1A, . . . , a driving characteristic improvement server S3, and a network NWA. Note that the driving characteristic improvement support system 200 may include a wireless terminal device P1A.

The driving characteristic improvement support system 200 receives driving characteristic data of a driver who drives a vehicle and safety confirmation behavior data transmitted from a communication device 11A (see FIG. 18) mounted on each of one or more vehicles C1A, . . . and get. The driving characteristic improvement support system 200 transmits the acquired driving characteristic data and safety confirmation behavior data to the driving characteristic improvement server S3. The driving characteristic improvement support system 200 determines whether or not the driver's driving characteristics have improved based on the driver's driving skill indicated by the driving characteristic data and the driver's safety confirmation behavior while driving indicated by the safety confirmation behavior data. The determination is made and the driving characteristic improvement evaluation results are transmitted to the vehicles C1A, . . . . Based on the driving characteristic improvement evaluation results, the driving characteristic improvement support system 200 updates and updates improvement effect data (an example of new improvement effect data) indicating the content of driving support for the driver for each of the vehicles C1A,... The driving characteristic improvement support is executed based on the improvement effect data obtained.

The driving characteristic data in the second embodiment is data indicating the driving characteristics of the driver, and includes various sensors (for example, in-vehicle camera 13A, gyro sensor 14, accelerator pedal 17A, brake The information may be acquired by the pedal 17B, the turn lamp 17C, the steering wheel 17D, the speed sensor 18, the vehicle exterior sensor/camera 19A, the vehicle interior sensor 24, etc. (see FIG. 18).

The improvement effect data referred to here is data generated by the driving characteristic improvement server S3, and includes driving characteristic data of each driver of the vehicle C1A, ... and the driver in the time period before and after the driving characteristic improvement support. Driving characteristics are determined based on data indicating the driver's reactions (e.g., driver's emotions, facial expressions, heartbeat, etc.) (hereinafter referred to as "emotional data") and driving scene information indicating the driving scene in which the driving characteristics were acquired. This is data that determines support methods for improvement.

In addition, the driving scenes mentioned here include not only arbitrary scenes while driving (for example, changing lanes, turning left or right, moving forward or backward, etc.), but also scenes before driving when the driver gets into the vehicle, after driving, or when the driver gets into the vehicle. Scenes before and after driving, such as when the driver or passenger exits the vehicle while the vehicle is temporarily stopped, and include scenes where safety confirmation is required. In addition, the driving scene includes the road environment while driving (e.g., T-junction, crossroads, downhill slope, etc.) or the road condition (e.g., traffic jam, etc.), and environmental information of the road while driving (e.g., time of day, weather, etc.) , the degree of risk (score) may be set in advance based on the likelihood of an accident occurring, the importance of safety confirmation, etc., based on the number and frequency of accidents that have occurred on the road the vehicle is traveling on.

Furthermore, for each driving scene, a threshold value regarding the frequency with which safety confirmation actions are performed may be set in accordance with the degree of risk (score). In such a case, each of the vehicles C1A, . good.

Each of the vehicles C1A, . . . is connected to the driving characteristic improvement server S3 and the wireless terminal device P1A via the network NWA so as to be able to communicate wirelessly. Note that the wireless communication referred to here includes, for example, a wireless LAN represented by Wi-Fi (registered trademark), a cellular communication system (mobile communication system), and the type thereof is not particularly limited.

Each of the vehicles C1A, . The acquisition of driving characteristic data and the determination (identification) of driving situations are started. Each of the vehicles C1A, ... executes driving characteristic improvement support (that is, support for safety confirmation behavior) for the driver based on the improvement support data corresponding to the driving scene information of the specified driving scene, and also performs this support. Obtain driver emotional data regarding driving characteristic improvement support.

Each of the vehicles C1A, . . . determines whether the driver has performed a safety confirmation action corresponding to the current driving scene information, based on the acquired driving characteristic data (specifically, behavioral characteristics). In addition, each of the vehicles C1A, . The data and a user ID that can identify the driver are linked and transmitted to the driving characteristic improvement server S3.

Each of the vehicles C1A, . A driving characteristic learning model for determining whether or not the driving characteristics have improved is stored in the driving characteristic learning device 23. Each of the vehicles C1A, . Update data such as data. Each of the vehicles C1A, . . . sets a driving characteristic improvement support method for supporting the driver's safety confirmation behavior in a predetermined driving scene, based on the improvement effect data transmitted from the driving characteristic improvement server S3. Each of the vehicles C1A, . . . finishes acquiring driving characteristic data at the timing when it detects that the driver has finished driving the own vehicle.

In addition, each of the vehicles C1A, . The driver's driving characteristic data is extracted and transmitted to the wireless terminal device P1A, or a driving characteristic evaluation result is generated by evaluating the driving characteristic using the extracted driving characteristic data and transmitted to the wireless terminal device P1A.

The driving characteristic improvement server S3 is connected to each of the vehicles C1A, . . . and the wireless terminal device P1A via the network NWA so as to enable data communication. The driving characteristic improvement server S3 acquires the driver's user ID, driving characteristic data, emotion data, and driving scene information transmitted from each of the vehicles C1A, . . . .

The driving characteristics improvement server S3 compares the acquired user ID with each of the user IDs of a plurality of drivers registered (stored) in the user database DB1, and identifies the driver with the acquired user ID. Identify. The driving characteristic improvement server S3 is configured to link the acquired driving characteristic data to the driving characteristic data of the specified driver's user ID and the same driving scene information as the acquired driving scene information. It is determined whether or not the driving characteristics of this driver have improved by comparing the driving characteristics data obtained with the acquired driving characteristics data. It is determined whether the driving characteristic improvement support method (improvement effect data) is a support method suitable for this driver. Note that the user ID here may be the driver's license ID, biometric information, etc. used to identify the driver in the first embodiment.

The driving characteristics improvement server S3 makes new improvements based on the determination result of whether the driver's driving characteristics have improved and the driver's emotional data regarding the driving characteristics improvement support method indicated by the current improvement effect data. Effect data is generated, updated, and transmitted to each of the vehicles C1A, .

Further, the driving characteristic improvement server S3 uses the driver's driving characteristic data or the control command requesting the driving characteristic evaluation result transmitted from the wireless terminal device P1A to improve the driver's driving characteristic data stored in the database 54 (see FIG. 20). The driving characteristic data is extracted and transmitted to the wireless terminal device P1A, or a driving characteristic evaluation result is generated by evaluating the driving characteristics using the extracted driving characteristic data and transmitted to the wireless terminal device P1A.

The network NWA connects each of the plurality of vehicles C1A, . . . , the driving characteristic improvement server S3, and the wireless terminal device P1A to enable wireless or wired communication.

Next, an example of the internal configuration of the vehicles C1A, . . . in the second embodiment will be described with reference to FIG. 18. FIG. 18 is a block diagram showing an example of the internal configuration of vehicles C1A, . . . in the second embodiment. The internal configuration of the vehicle C1A,... shown in FIG. 18 is an example of the internal configuration when using the driver's face image as biometric information, and includes sensors for acquiring other biometric information, a driver's license reader, etc. illustration is omitted. Furthermore, since each of the vehicles C1A, . . . has a similar internal configuration, the internal configuration of the vehicle C1A will be described in the following description.

The vehicle C1A is configured to include at least a communication device 11A, a terminal device 22, an in-vehicle camera 13A, a gyro sensor 14, a memory 15A, and an ECU 16A. Each part inside the vehicle C1A is connected to enable data transmission and reception via CAN or the like.

Note that the communication device 11A, the terminal device 22, the in-vehicle camera 13A, and the gyro sensor 14 may be integrally configured as one terminal device 22. Moreover, the sensor mounted on the vehicle C1A shown in FIG. 2 is an example, and the sensor is not limited thereto.

The communication device 11A transmits and receives data by wireless communication between the vehicle C1A and the driving characteristic improvement server S3 via the network NW.

The terminal device 22 is, for example, a car navigation device, a tablet terminal owned by the driver, a smartphone, etc., and is a device that can accept operations by the driver. Furthermore, the terminal device 22 may be an IVI device that can provide, for example, a car navigation function, a location information providing service function, an Internet connection function, a multimedia playback function, and the like. The terminal device 22 includes a processor 22A, a memory 22B, a display section 22C, and an input section 22D.

The processor 22A is configured using, for example, a CPU, a DSP, or an FPGA, and controls the operations of each section. The processor 22A cooperates with the memory 22B to perform various types of processing and control in an integrated manner. Specifically, the processor 22A refers to programs and data held in the memory 22B, and executes the programs to realize the functions of each part.

The processor 22A starts the process of acquiring driving characteristics and behavior characteristics (driving characteristic data) and the process of determining the driving situation at the timing when the processor 22A receives a control command indicating that the approach of the driver has been detected from the in-vehicle sensor 24 or the communication device 11A. do. After specifying the driving scene, the processor 22A executes driving characteristic improvement support based on the improvement effect data corresponding to the driving scene information of this driving characteristic. The processor 22A starts various processes such as acquisition of driving characteristics, behavioral characteristics, and emotional data of the driver for the executed driving characteristic improvement support.

The processor 22A controls various sensors (for example, an in-vehicle camera 13A, a gyro sensor 14, an accelerator pedal 17A, a brake pedal 17B, a turn lamp 17C, a steering wheel 17D, a speed sensor 18, an external sensor/camera 19A, an in-vehicle sensor 24, etc.) via the ECU 16A. ) to obtain various driving characteristic data.

The processor 22A identifies the driver based on the user ID output from the input section 22D. The processor 22A determines the driving scene based on captured images or information acquired by the in-vehicle camera 13A, the out-of-vehicle sensor/camera 19A, the GPS sensor 20, the in-vehicle sensor 24, or the like.

Based on the driving scene information of the determined driving scene, the processor 22A controls the speaker 25 or the warning indicator light 26 based on the improvement effect data corresponding to the driving scene information, and provides driving characteristic improvement support to the driver. (Safety confirmation behavior support).

The processor 22A acquires an image taken by the in-vehicle camera 13A, detects the driver's face reflected in the acquired image, and based on the detected facial expression of the driver, performs driving characteristic improvement support before and after driving characteristic improvement support. analyzes the emotions of drivers and generates emotional data.

The processor 22A also acquires an image taken by the in-vehicle camera 13A or the outside sensor/camera 19A, analyzes the body and eye movements of the driver reflected in the acquired image, and analyzes the driver's body and eyes based on the analysis results. Driving characteristic data including behavioral characteristics of the driver and driving characteristics acquired by various sensors is generated.

The processor 22A links the driving scene information in which the driving characteristic improvement support was executed, the driver's emotional data regarding the driving characteristic improvement support, the driving characteristic data acquired by various sensors, and the driver's user ID. The information is stored in the memory 15A, and is output to the communication device 11A to be transmitted to the driving characteristic improvement server S3. Note that the processor 22A may further link and transmit the determination result of whether the driver has performed the safety confirmation behavior based on the acquired behavior data to the driving characteristic improvement server S3.

The processor 22A also acquires driving scene information and improvement effect data transmitted from the driving characteristic improvement server S3. The processor 22A updates the improvement effect data corresponding to the acquired driving scene information to the newly acquired improvement effect data.

The processor 22A performs processing for acquiring driving characteristic data of the driver, processing for determining driving situations, processing for supporting improvement of driving characteristics, or processing for acquiring emotional data at the timing when it is determined that the driver gets off the vehicle or that the driver leaves the own vehicle. Finish various processes such as.

The memory 22B includes, for example, a RAM as a work memory used when executing each process of the processor 22A, and a ROM that stores programs and data that define the operations of the processor 22A. Data or information generated or acquired by the processor 22A is temporarily stored in the RAM. A program that defines the operation of the processor 22A is written in the ROM. The memory 22B also stores one or more user IDs who drive the vehicle C1A and a driving characteristic history table TB3.

The display section 22C is configured using, for example, an LCD or an organic EL. The display unit 22C displays a driving characteristic evaluation result screen (not shown) generated by the processor 22A.

The input section 22D is a user interface configured integrally with the display section 22C. The input unit 22D converts the received driver operation into an electrical signal (control command) and outputs it to the processor 22A. The input unit 22D receives an input operation of a user ID by the driver, an input operation requesting generation of a driving characteristic evaluation screen, a setting for enabling/invalidating driving characteristic improvement support, and the like.

The in-vehicle camera 13A includes at least a lens (not shown) and an image sensor (not shown). The image sensor is, for example, a solid-state imaging device such as a CCD or CMOS, and converts an optical image formed on an imaging surface into an electrical signal.

The in-vehicle camera 13A is controlled by the processor 22A, captures an image of the driver sitting in the driver's seat, and outputs the captured image to the processor 22A. The processor 22A analyzes the captured image output from the in-vehicle camera 13A, and generates behavior characteristic data indicating the movement of the driver's face, eyes, or body. The processor 22A compares the generated behavior characteristic data with one or more safe driving behaviors corresponding to the driving scene, and determines whether the driver has executed the safety confirmation behavior that should be performed in the current driving scene. Determine. Note that the process of analyzing the behavioral characteristic data of the driver and the process of determining whether or not the driver has executed the safety confirmation behavior that should be executed in the current driving situation are carried out by the processor 52 of the driving characteristic improvement server S3. It may be executed by

Further, the in-vehicle camera 13A is controlled by the processor 22A, captures an image of the driver sitting in the driver's seat, and outputs the captured image to the processor 22A. The processor 22A analyzes the captured image output from the in-vehicle camera 13A, analyzes the driver's emotions, and generates emotional data. Note that the emotion data generation process may be executed by the processor 52 of the driving characteristic improvement server S3.

The memory 15A includes, for example, a RAM as a work memory used when executing each process of the ECU 16A, and a ROM that stores programs and data that define the operations of the ECU 16A. Data or information generated or acquired by the ECU 16A is temporarily stored in the RAM. A program that defines the operation of the ECU 16A is written in the ROM. Further, the memory 15A may store one or more user IDs who drive the vehicle C1A and a driving characteristic history table TB3.

The ECU 16A collectively executes processing and control of each part. The ECU 16A is configured using a so-called electronic circuit control device, and realizes the functions of each part by referring to programs and data held in the memory 15A and executing the programs. The ECU 16A acquires information output from various sensors as driving characteristic data. ECU 16A outputs driving characteristic data to processor 22A.

Furthermore, the ECU 16A detects the approach of the driver to the own vehicle or the departure of the driver from the own vehicle (in other words, the end of driving) based on the electrical signal output from the in-vehicle sensor 24. The detected information is output to the processor 22A. Although the description will be omitted here, the ECU 16A may be capable of implementing various functions executed by the processor 22A, such as various processes required for driving characteristic improvement support and driver's driving characteristic evaluation.

The external sensor/camera 19A is one or more sensors such as radar and sonar that are provided in the vehicle C1A, and one or more cameras that can image the surroundings (outside the vehicle) of the vehicle C1A. The camera here may be a drive recorder. The external sensor/camera 19A detects the position of objects existing around the vehicle C1A (e.g., walls, obstacles, other vehicles, people, etc.) or objects approaching the own vehicle (e.g., other vehicles, motorcycles, people, etc.). It also detects and images directions, signs, white lines on the road, a driver or passenger getting off the vehicle and leaving the vehicle, a driver or passenger approaching the vehicle, and the like. The external sensor/camera 19A outputs detected detection information or a captured image to the processor 22A.

The driving characteristic learning device 23 records the driving characteristic learning model and driving scene data transmitted from the driving characteristic improvement server S3. The processor 22A generates driving characteristic data using the driving characteristic learning model recorded in the driving characteristic learning device 23 and information acquired by various sensors. Further, the processor 22A determines the driving situation using the driving situation data recorded in the driving characteristic learning device 23 and the information acquired by various sensors, and generates driving situation data indicating the driving situation of the vehicle C1A,... do.

The in-vehicle sensor 24 includes, for example, a sensor capable of receiving radio waves emitted from the smart key of the own vehicle, an opening/closing sensor provided on the door corresponding to each seat, a weight sensor provided on each seat, a seat belt attachment sensor, etc. It is. When the in-vehicle sensor 24 receives a radio wave transmitted from the smart key, it generates an electric signal (control command) notifying the driver's approach and outputs it to the ECU 16A. When the in-vehicle sensor 24 is unable to receive radio waves transmitted from the smart key, it generates an electric signal (control command) to notify that the driver has left the own vehicle and outputs it to the ECU 16A. Furthermore, the in-vehicle sensor 24 outputs to the ECU 16A information detected by a weight sensor provided in the driver's seat, such as movement of the driver's body (weight), fastening/detaching of a seatbelt, opening/closing of the driver's seat door, etc.

At least one speaker 25, which is an example of a safe driving support device, is provided in each of the vehicles C1A, . Perform characteristic improvement support. The installation positions and numbers of the speakers 25 in the vehicle C1A, ... according to the second embodiment will be described with reference to an example in which two speakers 25 are installed in the front and rear of the vehicle, respectively, as shown in FIG. Needless to say, it is not limited to this. Further, the speaker 25 may be installed not only inside the vehicle but also outside the vehicle.

The warning indicator light 26, which is an example of a safe driving support device, is an LED (Light Emitting Diode) installed, for example, on a pillar in the vehicle, and is controlled by the processor 22A or the ECU 16A and lights up according to the driving situation. , to support the improvement of the driver's driving characteristics. It goes without saying that the installation position and number of warning indicator lights 26 in the vehicles C1A, . . . according to the second embodiment are not limited to the example shown in FIG. 29. Further, the warning indicator light 26 may be installed at a position other than the pillar (for example, a side mirror, a room mirror, etc.).

Next, with reference to FIG. 19, the driving characteristic history table TB3 recorded by each of the vehicles C1A, . . . will be described. FIG. 19 is a diagram showing an example of the driving characteristic history table TB3. In the following explanation, in order to make the explanation easier to understand, various data or information recorded by each of the vehicles C1A, ... will be explained using the driving characteristic history table TB3, but the driving characteristic history table TB3 is not essential. , may be omitted.

The driving characteristic history table TB3 records and manages driving scene information, driving characteristic data, and improvement effect data corresponding to the driving scene information in association with a user ID. Note that the user ID may be a driver's license ID.

For example, the driving characteristic history table TB3 shown in FIG. 19 associates the user ID "AAA" with the driving scene information "〇〇〇", the driving characteristic data, and the improvement effect data, , link the driving scene information "△△△", the driving characteristic data, and the improvement effect data, and add the driving scene information "XXXX", the driving characteristic data, and the improvement effect data to the user ID "BBB". and record each. As a result, the driving characteristic history table TB3 can be used even when a plurality of different drivers (for example, two users "AAA" and "BBB") drive the same vehicle. Driving characteristic data and improvement effect data can be more efficiently recorded (managed) for each user ID.

Next, an example of the internal configuration of the driving characteristic improvement server S3 will be described with reference to FIG. 20. FIG. 20 is a block diagram showing an example of the internal configuration of the driving characteristic improvement server S3 in the second embodiment.

The driving characteristic improvement server S3 includes a communication section 51, a processor 52, a memory 53, and a database 54. Note that the database 54 may be configured as a separate entity that is connected to the driving characteristic improvement server S3 so as to enable data communication.

The communication unit 51 is connected to each of the vehicles C1A, . . . and the wireless terminal device P1 via the network NW so as to be able to transmit and receive data.

The processor 52 is configured using, for example, a CPU, a DSP, or an FPGA, and controls the operations of each section. The processor 52 cooperates with the memory 53 to perform various types of processing and control in an integrated manner. Specifically, the processor 52 refers to the program and data held in the memory 53 and executes the program, thereby realizing the functions of each section such as the support method generation section 52A. When the driving characteristic learning model or driving scene data is updated, the processor 52 transmits the updated driving characteristic learning model or driving scene data to each of the vehicles C1A, . . . .

The processor 52 also generates teacher data (learning data) used to generate a driving characteristic learning model based on machine learning using driving characteristic data corresponding to each driving scene information transmitted from each of the vehicles C1A, . may be generated. The processor 52 generates training data used to generate an improvement effect learning model based on machine learning using emotional data of the driver regarding driving characteristic improvement support based on each improvement effect data transmitted from each of the vehicles C1A, . (learning data) may be generated.

Learning to generate training data may be performed using one or more statistical classification techniques. Examples of statistical classification techniques include multiple regression analysis, linear classifiers, support vector machines, quadratic classifiers, kernel density estimation, and decision trees ( Decision Trees), Artificial Neural Networks, Bayesian Techniques and/or Networks, Hidden Markov Models, Binary classifiers, multi-class classifiers ( Multi-Class Classifiers), Clustering Technique, Random Forest Technique, Logistic Regression Technique, Linear Regression (Li Examples include near regression technique, gradient boosting technique, and the like. However, the statistical classification techniques used are not limited to these.

The support method generation unit 52A acquires each of the driving characteristic data, driving scene information, emotional data, and user ID transmitted from each of the vehicles C1A, . . . . The support method generation unit 52A identifies the driver by comparing the acquired user ID with each of the plurality of user IDs registered (stored) in the user database DB1. Note that if the support method generation unit 52A determines that the same user ID as the acquired user ID is not registered in the user database DB1, the support method generation unit 52A uses the acquired user ID as a new user. may be registered (stored) in the user database DB1.

Based on the acquired driving scene information, the support method generation unit 52A determines whether the driving scene requires safe driving and the degree of risk (score) corresponding to the driving scene is equal to or higher than a predetermined value. judge. Furthermore, the support method generation unit 52A determines whether the driver is performing a safety confirmation behavior corresponding to the driving situation, based on behavioral characteristic data included in the acquired driving characteristic data.

The support method generation unit 52A further determines whether or not it is necessary to change the driving characteristic improvement method based on these determination results and emotional data. When determining that the driving characteristic improvement method needs to be changed, the support method generation unit 52A stores the acquired driving scene information in the driving scene database DB2 and the acquired driving characteristic data in the driving characteristic database DB3. The improvement effect data is registered (stored) in the improvement effect database DB4 in association with each user ID. Further, the support method generation unit 52A determines whether or not the driver's driving characteristics have improved based on the acquired driving characteristics and the driver's driving characteristics registered in the driving characteristics database DB3. The support method generation unit 52A determines the changed driving characteristic improvement method based on the determination result as to whether the driving characteristics have improved and the acquired emotional data. The support method generation unit 52A generates improvement effect data indicating the changed driving characteristic improvement method, and transmits it to the vehicles C1A, . . . .

On the other hand, if the support method generation unit 52A determines that there is no need to change the driving characteristic improvement method, it omits the generation and update process of new improvement effect data, and stores the acquired driving scene information in the driving scene database DB2. The acquired driving characteristic data is registered (stored) in the driving characteristic database DB3 in association with each user ID.

The memory 53 includes, for example, a RAM as a work memory used when the processor 52 executes each process, and a ROM that stores programs and data that define the operations of the processor 52. Data or information generated or acquired by the processor 52 is temporarily stored in the RAM. A program that defines the operation of the processor 52 is written in the ROM. The memory 53 also stores a driving characteristic learning model 53A and an improvement effect learning model 53B.

The database 54 records a user database DB1, a driving scene database DB2, a driving characteristic database DB3, and an improvement effect database DB4. Each of the user database DB1, driving scene database DB2, driving characteristic database DB3, and improvement effect database DB4 includes one set of data (user ID, driving scene information, driving scene information) transmitted from each of the vehicles C1A,... (the driving characteristic data corresponding to the driving situation information and the improvement effect data corresponding to the driving scene information) are recorded in a state where they are linked to each other. Note that each of the user database DB1, driving scene database DB2, driving characteristic database DB3, and improvement effect database DB4 stores the acquisition date and time information acquired from each of the vehicles C1A, . . . One set of data transmitted from each of C1A, . . . may be linked.

The user database DB1 registers (stores) each user ID of a plurality of drivers. Note that the user ID may be a driver's license ID.

The driving scene database DB2 registers (stores) driving scene information acquired from each of the plurality of vehicles C1A, . . . for each user ID.

The driving characteristic database DB3 registers (stores) driving characteristic data acquired from each of the plurality of vehicles C1A, . . . for each driving situation of the user ID.

The improvement effect database DB4 registers (stores) the improvement effect data generated by the support method generation unit 52A for each driving scene information of the user ID. Note that the improvement effect database DB4 may register (store) the changed driving improvement data when the changed driving improvement data is generated. In addition, when new improvement effect data is generated by the vehicles C1A,..., the improvement effect database DB4 stores the improvement effect data linked to the driving scene information in the new improvement effect data acquired from each of the plurality of vehicles C1A,... Update the improvement effect data.

Next, with reference to FIG. 21, the driving characteristic improvement management table TB4 recorded by each of the vehicles C1A, . . . will be described. FIG. 19 is a diagram showing an example of the driving characteristic improvement management table TB4. In the following explanation, in order to make the explanation easier to understand, the driving characteristic improvement management table TB4 is used to describe the database 54 (that is, the user database DB1, the driving scene database DB2, the driving characteristic database DB3, and the improvement effect database DB4). The various data or information recorded by each) will be explained, but the driving characteristic improvement management table TB4 is not essential and may be omitted.

The driving characteristic improvement management table TB4 records and manages the driving scene information by linking the driving characteristic data corresponding to the driving scene and the improvement effect data corresponding to the driving scene information for each user ID. Note that the user ID may be a driver's license ID.

For example, the driving characteristic improvement management table TB4 shown in FIG. The characteristic data and the improvement effect data are recorded by being associated with the driving scene information "XXXX". The driving characteristic improvement management table TB4 records the driving scene information "XXXX" of the user ID "BBB" by linking the driving characteristic data and the improvement effect data, and records the driving scene information "XXXX" of the user ID "CCC" by linking the driving characteristic data and the improvement effect data. Driving characteristic data and improvement effect data are linked and recorded in △△△.

With reference to FIG. 22, a specific example of the process of determining whether or not the safety confirmation behavior is being executed by the vehicle C1A, . . . or the driving characteristic improvement server S3 will be described. FIG. 22 is a diagram illustrating an example of safety confirmation behavior when turning left. Note that the safe behavior confirmation example shown in FIG. 22 is just an example, and it goes without saying that the present invention is not limited to this. Further, in FIG. 22, an example will be described in which the determination process of whether or not the safety confirmation behavior is executed is executed by the vehicle C1A, but the process is not limited to this, and is executed by the processor 52 of the driving characteristic improvement server S3. It's okay to be.

FIG. 22 is a diagram showing the vehicle C1A in a driving scene "when turning left", and is a diagram showing the vehicle C1A just before turning left in the traveling direction D1 and the inside of the vehicle C1A at that time. Note that each process executed by the terminal device 22 described below may be executed by the ECU 16A.

The terminal device 22 shown in FIG. 22 uses the driving scene data recorded in the driving characteristic learning device 23 and information acquired by various sensors to determine that the driving scene of the vehicle C1A is "when turning left." For example, the terminal device 22 receives driving scene data, a captured image of the surroundings of the vehicle C1A captured by the external sensor/camera 19A, an image obtained by the accelerator pedal 17A, brake pedal 17B, turn lamp 17C, or steering wheel 17D. The vehicle C1A uses various information regarding the driving operation of the driver, destination information set in advance on the terminal device 22, current position information of the vehicle C1A acquired by the GPS sensor 20, etc. It is determined that the driving situation is "when turning left."

The terminal device 22 links the user ID corresponding to this driver stored in the driving characteristic history table TB3 based on the determined driving scene information "when turning left" of the vehicle C1A, and also displays the driving scene information. The improvement effect data (that is, the driving characteristic improvement support method) corresponding to "when turning left" is referred to. The terminal device 22 generates a control command to control the speaker 25 or the warning indicator light 26, respectively, based on the referenced improvement effect data, and outputs the control command to the speaker 25 or the warning indicator light 26, respectively. Note that when the terminal device 22 determines that driving characteristic improvement support is not necessary based on the referenced improvement effect data, it omits the control of the speaker 25 or the warning indicator light 26 described above.

Further, the terminal device 22 refers to information on one or more safety confirmation actions to be performed by the driver, corresponding to the determined driving scene information "when turning left" of the vehicle C1A. The terminal device 22 determines whether or not the driver has executed the safety confirmation behavior corresponding to the driving scene information, based on the information on one or more safety confirmation behaviors and the behavioral characteristic data of the driver acquired by various sensors. Determine whether In the example shown in FIG. 22, an example will be described in which the vehicle C1A determines whether the driver has performed each of three safety confirmation actions corresponding to the driving scene information "when turning left."

For example, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to execute driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A through the rearview mirror RM, and also performs driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A through the rearview mirror RM. Based on the captured image, it is determined whether the driver's face or line of sight has turned in the direction AC11 (that is, whether the driver visually confirmed the rear of the vehicle C1A through the rearview mirror RM) (1 (second judgment).

The terminal device 22 also controls the speaker 25 or warning indicator light 26 to provide driving characteristic improvement support that urges the driver to visually check the left side and left rear of the vehicle C1A through the left side mirror SM1 corresponding to the traveling direction D1. At the same time, based on the captured image output from the in-vehicle camera 13A, it is determined whether or not the driver's face or line of sight is directed in the direction AC12 (that is, whether the driver's face or line of sight is directed toward the direction AC12 (second determination) whether the left side and rear of the vehicle C1A were visually confirmed.

Furthermore, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to execute driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A, and also performs driving characteristic improvement support based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether the driver's body, face, or line of sight has turned in direction AC13 (that is, whether the driver visually confirmed the rear of the vehicle C1A) (third determination).

Note that in the case where execution determination is made for each of two or more safety confirmation actions, and a determination order is set in advance for each of these safety confirmation actions, the terminal device 22 determines whether or not to execute each safety confirmation action. In addition to making the determination, it may also be determined whether each safety confirmation action has been executed in the set order.

The terminal device 22 calculates the driver's emotions based on the image captured by the in-vehicle camera 13A from the timing when driving characteristic improvement support is started until the timing when execution determination processing for each of the three safety confirmation actions is completed. Analyze. The terminal device 22 generates emotional data based on the analysis results. Note that the terminal device 22 may generate emotional data for each driving characteristic improvement support corresponding to each safety confirmation action, or may generate emotional data for each driving characteristic improvement support executed in the driving scene "when turning left." Emotion data may also be generated.

The terminal device 22 stores driving characteristic data, driving scene information, and the three safety confirmation actions acquired from the timing when the judgment of the driving situation is started until the timing when the execution judgment of each of the three safety confirmation actions is completed. Safety confirmation action data indicating the respective judgment results and emotional data corresponding to driving characteristic improvement support are generated respectively, and are recorded in the memory 15A in association with the user ID, and transmitted to the driving characteristic improvement server S3. and record it in the database 54.

With reference to FIG. 23, a specific example of the process of determining whether or not the safety confirmation behavior is being executed by the vehicle C1A, . . . or the driving characteristic improvement server S3 will be described. FIG. 23 is a diagram illustrating an example of safety confirmation behavior when turning right. Note that the safe behavior confirmation example shown in FIG. 23 is just an example, and it goes without saying that the present invention is not limited thereto. Further, in FIG. 23, an example will be described in which the determination process of whether or not the safety confirmation behavior is executed is executed by the vehicle C1A, but the process is not limited to this, and is executed by the processor 52 of the driving characteristic improvement server S3. It's okay to be.

FIG. 23 is a diagram showing the vehicle C1A in a driving scene "when turning right", and is a diagram showing the vehicle C1A just before turning right in the traveling direction D2 and the inside of the vehicle C1A at that time.

The terminal device 22 shown in FIG. 23 uses the driving scene data recorded in the driving characteristic learning device 23 and the information acquired by various sensors to determine that the driving scene of the vehicle C1A is "right turn".

The terminal device 22 links the user ID corresponding to this driver stored in the driving characteristic history table TB3 based on the determined driving scene information "when turning right" of the vehicle C1A, and also displays the driving scene information. The improvement effect data (that is, the driving characteristic improvement support method) corresponding to "right turn" is referred to. The terminal device 22 generates a control command to control the speaker 25 or the warning indicator light 26, respectively, based on the referenced improvement effect data, and outputs the control command to the speaker 25 or the warning indicator light 26, respectively. Note that when the terminal device 22 determines that driving characteristic improvement support is not necessary based on the referenced improvement effect data, it omits the control of the speaker 25 or the warning indicator light 26 described above.

Further, the terminal device 22 refers to information on one or more safety confirmation actions to be performed by the driver, corresponding to the determined driving scene information "right turn" of the vehicle C1A. The terminal device 22 determines whether or not the driver has executed the safety confirmation behavior corresponding to the driving scene information, based on the information on one or more safety confirmation behaviors and the behavioral characteristic data of the driver acquired by various sensors. Determine whether In the example shown in FIG. 23, an example will be described in which the vehicle C1A determines whether the driver has performed each of three safety confirmation actions corresponding to the driving scene information "right turn".

For example, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to execute driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A through the rearview mirror RM, and also performs driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A through the rearview mirror RM. Based on the captured image, it is determined whether the driver's face or line of sight has turned in the direction AC21 (that is, whether the driver has visually confirmed the rear of the vehicle C1A through the rearview mirror RM) (1 (second judgment).

The terminal device 22 also controls the speaker 25 or the warning indicator light 26 to provide driving characteristic improvement support that urges the driver to visually check the right side and right rear of the vehicle C1A through the right side mirror SM2 corresponding to the traveling direction D2. At the same time, based on the captured image output from the in-vehicle camera 13A, it is determined whether or not the driver's face or line of sight is directed in the direction AC22 (that is, whether the driver is looking through the right side mirror SM2 corresponding to the direction of travel D2). (Second determination) (second determination).

Furthermore, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to execute driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A, and also performs driving characteristic improvement support based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether the driver's body, face, or line of sight has turned in the direction AC23 (that is, whether the driver has visually confirmed the rear of the vehicle C1A) (third determination). Note that, as shown in FIG. 23, when the vehicle C1A is a vehicle with a driver's seat on the right side (that is, a right-hand steering vehicle), the driver's right side and right rear side of the vehicle C1A are blocked by the door of the driver's seat. In such a case, the terminal device 22 determines whether the driver's head has turned from the direction of travel D2 to the right side of the vehicle C1A by 90 degrees or more, based on the behavioral characteristic data of the driver. It may be determined whether the driver visually checked the rear of the vehicle C1A.

The terminal device 22 calculates the driver's emotions based on the image captured by the in-vehicle camera 13A from the timing when driving characteristic improvement support is started until the timing when execution determination processing for each of the three safety confirmation actions is completed. Analyze. The terminal device 22 generates emotional data based on the analysis results. The terminal device 22 stores driving characteristic data, driving scene information, and the three safety confirmation actions acquired from the timing when the judgment of the driving situation is started until the timing when the execution judgment of each of the three safety confirmation actions is completed. Safety confirmation action data indicating the respective judgment results and emotional data corresponding to driving characteristic improvement support are generated respectively, and are recorded in the memory 15A in association with the user ID, and transmitted to the driving characteristic improvement server S3. and record it in the database 54.

With reference to FIG. 24, a specific example of the process of determining whether or not the safety confirmation behavior is being executed by the vehicle C1A, . . . or the driving characteristic improvement server S3 will be described. FIG. 24 is a diagram illustrating an example of safety confirmation behavior when reversing. Note that the safe behavior confirmation example shown in FIG. 24 is just an example, and it goes without saying that the present invention is not limited thereto. Furthermore, in FIG. 24, an example will be described in which the process of determining whether or not the safety confirmation behavior is being executed is executed by the vehicle C1A, but the process is not limited to this, and is executed by the processor 52 of the driving characteristic improvement server S3. It's okay to be.

FIG. 24 is a diagram showing the vehicle C1A in a driving scene "when reversing", and is a diagram showing the vehicle C1A just before reversing in the traveling direction D3 and the inside of the vehicle C1A at that time.

The terminal device 22 shown in FIG. 24 uses the driving scene data recorded in the driving characteristic learning device 23 and the information acquired by various sensors to determine that the driving scene of the vehicle C1A is "reversing".

The terminal device 22 links the user ID corresponding to this driver stored in the driving characteristic history table TB3 based on the determined driving scene information "when reversing" of the vehicle C1A, and also displays the driving scene information. The improvement effect data (that is, the driving characteristic improvement support method) corresponding to "when reversing" is referred to. The terminal device 22 generates a control command for controlling the speaker 25 or the warning indicator light 26, respectively, based on the referenced improvement effect data, and outputs the control command to the speaker 25 or the warning indicator light 26, respectively. Note that if the terminal device 22 determines that driving characteristic improvement support is not required based on the referenced improvement effect data, it omits the control of the speaker 25 or the warning indicator light 26 described above.

Furthermore, the terminal device 22 refers to information on one or more safety confirmation actions to be performed by the driver, corresponding to the determined driving scene information "when reversing" of the vehicle C1A. The terminal device 22 determines whether or not the driver has executed the safety confirmation behavior corresponding to the driving scene information, based on the information on one or more safety confirmation behaviors and the behavioral characteristic data of the driver acquired by various sensors. Determine whether In addition, in the example shown in FIG. 24, an example will be described in which the vehicle C1A determines whether the driver has performed each of three safety confirmation actions corresponding to the driving scene information "when reversing".

For example, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to execute driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A through the rearview mirror RM, and also performs driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A through the rearview mirror RM. Based on the captured image, it is determined whether the driver's face or line of sight has turned in the direction AC31 (that is, whether the driver has visually confirmed the rear of the vehicle C1A through the rearview mirror RM) (1 (second judgment).

The terminal device 22 also controls the speaker 25 or the warning indicator light 26 to provide driving characteristic improvement support that urges the driver to visually check the right side and right rear of the vehicle C1A through the right side mirror SM2 corresponding to the direction of travel D3. At the same time, based on the captured image output from the in-vehicle camera 13A, it is determined whether or not the driver's face or line of sight moves toward the direction AC32 (that is, whether the driver's face or line of sight moves toward the direction AC32 (that is, when the driver looks at the right side mirror SM2 corresponding to the traveling direction D3). (Second determination) (second determination).

Furthermore, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to execute driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A, and also performs driving characteristic improvement support based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether the movement of the driver's body, face, or line of sight is directed in the direction AC33 (that is, whether the driver visually confirmed the rear of the vehicle C1A) (third determination). Note that if the seatbelt wearing sensor, which is an example of the in-vehicle sensor 24, detects that the driver has taken off the seatbelt when checking the rear, the terminal device 22 detects whether the seatbelt has been fastened again after checking the rear. It may also be possible to perform driving characteristic improvement support that urges the driver to refasten the seat belt. Note that the determination as to whether or not the driver has performed a visual check of the rear is performed based on an image captured by a back monitor (an example of the external sensor/camera 19A) that captures an image of the rear of the own vehicle. Alternatively, a surround view monitor (360° camera image, top view image, etc.) that is an overhead view of the own vehicle based on a plurality of captured images obtained using a plurality of external sensors/cameras 19A. may be executed based on the generated surround view monitor or the like.

The terminal device 22 calculates the driver's emotions based on the image captured by the in-vehicle camera 13A from the timing when driving characteristic improvement support is started until the timing when execution determination processing for each of the three safety confirmation actions is completed. Analyze. The terminal device 22 generates emotional data based on the analysis results. The terminal device 22 stores driving characteristic data, driving scene information, and the three safety confirmation actions acquired from the timing when the judgment of the driving situation is started until the timing when the execution judgment of each of the three safety confirmation actions is completed. Safety confirmation action data indicating the respective judgment results and emotional data corresponding to driving characteristic improvement support are generated respectively, and are recorded in the memory 15A in association with the user ID, and transmitted to the driving characteristic improvement server S3. and record it in the database 54.

With reference to FIG. 25, a specific example of the process of determining whether or not the safety confirmation behavior is being executed by the vehicle C1A, . . . or the driving characteristic improvement server S3 will be described. FIG. 25 is a diagram illustrating an example of safety confirmation behavior when moving forward on a long-distance straight road. Note that the safe behavior confirmation example shown in FIG. 25 is just an example, and it goes without saying that the present invention is not limited thereto. Further, in FIG. 25, an example will be described in which the process of determining whether or not the safety confirmation behavior is executed is executed by the vehicle C1A, but the process is not limited to this, and is executed by the processor 52 of the driving characteristic improvement server S3. It's okay to be.

FIG. 25 is a diagram showing the vehicle C1A in a driving scene "while moving forward on a long-distance straight road", and is a diagram showing the vehicle C1A moving forward in the traveling direction D4 and the state inside the vehicle C1A at that time.

The terminal device 22 shown in FIG. 25 uses the driving scene data recorded in the driving characteristic learning device 23 and the information acquired by various sensors to determine that the driving scene of the vehicle C1A is "while moving forward on a long-distance straight road." It is determined that there is.

The terminal device 22 links the user ID corresponding to this driver stored in the driving characteristic history table TB3 based on the determined driving situation information of the vehicle C1A "while moving forward on a long-distance straight road", In addition, the improvement effect data (that is, the driving characteristic improvement support method) corresponding to the driving scene information "while moving forward on a long-distance straight road" is referred to. The terminal device 22 generates a control command to control the speaker 25 or the warning indicator light 26, respectively, based on the referenced improvement effect data, and outputs the control command to the speaker 25 or the warning indicator light 26, respectively. Note that when the terminal device 22 determines that driving characteristic improvement support is not necessary based on the referenced improvement effect data, it omits the control of the speaker 25 or the warning indicator light 26 described above.

The terminal device 22 also refers to information on one or more safety confirmation actions to be performed by the driver, corresponding to the determined driving situation information of the vehicle C1A "while moving forward on a long-distance straight road." The terminal device 22 determines whether or not the driver has executed the safety confirmation behavior corresponding to the driving scene information, based on the information on one or more safety confirmation behaviors and the behavioral characteristic data of the driver acquired by various sensors. Determine whether In addition, in the example shown in FIG. 25, an example will be described in which the vehicle C1A determines whether the driver has performed each of one safety confirmation action corresponding to the driving scene information "while moving forward on a long-distance straight road". do.

For example, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to execute driving characteristic improvement support that urges the driver to visually check the rear of the vehicle C1A, and also based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether the driver's body, face, or line of sight has turned in direction AC41 (that is, whether the driver has visually checked the rear of the vehicle C1A).

In addition, when one driving scene continues for more than the first predetermined time or the first traveling distance, as in the driving scene information "while moving forward on a long-distance straight road" shown in FIG. 25, the safety confirmation behavior determination process is performed. may be repeatedly executed periodically (eg, every predetermined time, every predetermined distance).

The terminal device 22 analyzes the driver's emotions based on the captured image captured by the in-vehicle camera 13A from the timing when the driving characteristic improvement support is started until the timing when the execution determination process of the safety confirmation behavior is finished. The terminal device 22 generates emotional data based on the analysis results. The terminal device 22 uses driving characteristic data, driving scene information, and judgments for each of the three safety confirmation actions acquired between the timing when the judgment of the driving situation is started and the timing when the execution judgment of the safety confirmation action is completed. Safety confirmation behavior data indicating the results and emotional data corresponding to the driving characteristic improvement support are generated respectively, and are recorded in the memory 15A in association with the user ID, and transmitted to the driving characteristic improvement server S3, and then stored in the database 54. record it.

Next, with reference to FIG. 26, an example of the driver's safety confirmation behavior for each driving situation will be described. FIG. 26 is a diagram illustrating an example of sensing a driver's safety confirmation behavior for each driving situation. It goes without saying that the driving scenes, safety confirmation actions, and sensor examples shown in FIG. 26 are just examples and are not limited thereto.

The safety confirmation behavior table TB5 shown in FIG. 26 is a table that associates driving scene information, a safety confirmation behavior that corresponds to the driving scene information and should be performed by the driver, and an example of a sensor that senses the safety confirmation behavior. Note that the safety confirmation behavior table TB5 is a table for making it easier to understand the explanation of the driver's safety confirmation behavior examples sensed for each driving situation, and is not essential and may be omitted.

For example, in the safety confirmation behavior table TB5 shown in FIG. 26, the terminal device 22 uses wireless communication such as Bluetooth (registered trademark) to transmit radio waves transmitted from the smart key or smartphone of the own vehicle owned by the driver by the in-vehicle sensor 24. If it is determined that the driver's approach to the own vehicle has been detected (sensed), the driving scene is "before getting into the vehicle" based on the driving scene data recorded in the driving characteristic learning device 23. It is determined that When the terminal device 22 determines that the driving scene is "before getting into the vehicle," the terminal device 22 uses the external sensor/camera 19A to determine the presence or absence of obstacles in the forward direction or reverse direction of the own vehicle (that is, the front and back direction of the own vehicle). Safety confirmation by visually checking the presence or absence of objects in contact with the opening and closing of at least one seat door of the host vehicle using the in-vehicle sensor 24 (for example, a door opening/closing sensor that detects whether each door is open or closed) Determine whether the action is being performed.

In addition, based on information acquired by various sensors such as the in-vehicle camera 13A and in-vehicle sensor 24 (door opening/closing sensor), and driving scene data recorded in the driving characteristic learning device 23, the driving scene is determined to be "before getting out of the vehicle." ”, the terminal device 22 detects the forward direction or reverse direction of the own vehicle (that is, the longitudinal direction of the own vehicle) using the in-vehicle camera 13A, the out-of-vehicle sensor/camera 19A, the in-vehicle sensor 24 (door opening/closing sensor), etc. the presence or absence of obstacles in the vehicle, the presence or absence of objects that come in contact with the door of at least one seat of the host vehicle by the in-vehicle sensor 24 (for example, a door opening/closing sensor that detects whether each door is open or closed), etc. Determine whether or not the safety confirmation action to visually confirm the safety check is being performed.

In addition, based on information acquired by various sensors such as the in-vehicle camera 13A and in-vehicle sensor 24 (door opening/closing sensor), and driving scene data recorded in the driving characteristic learning device 23, the driving scene is determined to be "A passenger is driving If the terminal device 22 determines that the vehicle is moving forward or backward (that is, before getting off the vehicle), the terminal device 22 uses the in-vehicle camera 13A, the out-vehicle sensor/camera 19A, the in-vehicle sensor 24 (door opening/closing sensor), etc. The presence or absence of obstacles in the front and rear directions), the presence of obstacles in the vehicle interior sensor 24 (for example, a door open/close sensor that detects whether the doors are open or closed) It is determined whether the safety confirmation action of visually checking the presence or absence of contact objects by opening and closing the door of the passenger's seat (passenger's seat) is performed.

Furthermore, based on the information acquired by various sensors such as the in-vehicle camera 13A, the accelerator pedal 17A, and the brake pedal 17B, and the driving scene data recorded in the driving characteristic learning device 23, the driving scene is determined to be "before starting the vehicle." ”, the terminal device 22 uses the in-vehicle camera 13A, external sensor/camera 19A, etc. to determine whether the vehicle is moving forward or backward (that is, in the front-rear direction of the vehicle), or if there is an approach from around the vehicle. It is determined whether a safety confirmation action is being performed to visually check the presence or absence of objects (for example, pedestrians, other vehicles, two-wheeled vehicles, etc.).

Also, based on the information acquired by various sensors such as the in-vehicle camera 13A, the accelerator pedal 17A, and the brake pedal 17B, and the driving scene data recorded in the driving characteristic learning device 23, the driving scene is "before applying the brakes". If it is determined that this is the case, the terminal device 22 uses the in-vehicle camera 13A, the external sensor/camera 19A, etc. to detect objects approaching from behind the own vehicle or around the own vehicle (e.g., pedestrians, other vehicles, motorcycles, etc.). It is determined whether or not a safety confirmation action to visually confirm the presence or absence of the vehicle is being performed.

Also, based on information acquired by various sensors such as the in-vehicle camera 13A, turn lamp 17C, and steering wheel 17D, and driving scene data recorded in the driving characteristic learning device 23, the driving scene is determined to be "before changing lanes." If so, the terminal device 22 uses the in-vehicle camera 13A, the external sensor/camera 19A, etc. to detect objects approaching from the rear left side, rear right side of the own vehicle, or around the own vehicle (for example, pedestrians, other vehicles, etc.). It is determined whether the safety confirmation action of visually checking the presence or absence of vehicles (such as motorcycles, etc.) is being performed.

Further, when it is determined that the driving scene is "while driving straight" based on the information acquired by various sensors such as the in-vehicle camera 13A and the driving scene data recorded in the driving characteristic learning device 23, The terminal device 22 uses an in-vehicle camera 13A, an external sensor/camera 19A, etc. to visually confirm the presence or absence of approaching objects (e.g., pedestrians, other vehicles, motorcycles, etc.) behind the own vehicle or around the own vehicle. Determine whether the confirmation action is being performed.

Also, based on the information acquired by various sensors such as the in-vehicle camera 13A, the accelerator pedal 17A, the brake pedal 17B, the turn lamp 17C, and the steering wheel 17D, and the driving scene data recorded in the driving characteristic learning device 23, the driving scene is When the terminal device 22 determines that it is "before making a right or left turn," the terminal device 22 uses the in-vehicle camera 13A, the external sensor/camera 19A, etc. to detect objects approaching from behind the own vehicle or around the own vehicle (for example, pedestrians). , other vehicles, two-wheeled vehicles, etc.).

Also, based on the information acquired by various sensors such as the in-vehicle camera 13A, the accelerator pedal 17A, and the brake pedal 17B, and the driving scene data recorded in the driving characteristic learning device 23, the driving scene is "before reversing". If it is determined that there is a fault, the terminal device 22 detects a fault in the forward direction or backward direction of the own vehicle (that is, in the longitudinal direction of the own vehicle) using the in-vehicle camera 13A, the out-of-vehicle sensor/camera 19A, the in-vehicle sensor 24 (door opening/closing sensor), etc. Determine whether or not safety confirmation actions are being performed to visually check the presence or absence of objects, the presence or absence of objects in contact with at least one seat of the own vehicle (for example, the seat of a passenger exiting the own vehicle) by opening and closing the door, etc. do.

Next, with reference to FIG. 27, the warning indicator lights 26 mounted on the vehicles C1A, . . . will be described. FIG. 27 is a diagram illustrating an example of the arrangement of warning indicator lights 26A and 26B.

It goes without saying that the respective arrangement positions of the two warning indicator lights 26A and 26B shown in FIG. 27 are merely examples, and are not limited thereto. Further, in the example shown in FIG. 27, two warning indicator lights 26A, 26B are each mounted, but the number of warning indicator lights mounted in each of the vehicles C1A, . . . may be three or more.

For example, the warning indicator light 26 may be provided on any one of the B-pillar, C-pillar, D-pillar, etc. of the vehicle C1A, . . . . The B pillars referred to herein are a pair of pillars provided in the center of the vehicle body of the vehicle C1A, between the driver's seat, the passenger seat, and the second seat. Further, the C-pillars are a pair of pillars provided at the center of the vehicle body between the second seat and the third seat and provided at the rear of the vehicle body of the vehicle C1A, . . . . Further, the D pillars are a pair of pillars provided behind the second or third seat and at the rear of the vehicle body of the vehicle C1A.

Each of the warning indicator lights 26A and 26B shown in FIG. 27 is an LED provided on each of a pair of front pillars (A pillars) provided on both sides of the respective windshields of the vehicles C1A, . . . . Each of the warning indicator lights 26A and 26B lights up or blinks in a predetermined color (for example, yellow, orange, red, etc.) based on a control command from the terminal device 22 or the ECU 16A, or goes out.

The terminal device 22 may turn on or blink the warning indicator light 26 in a different color based on the degree of risk (score) of the driving situation or the driving characteristics of the driver (driving skill, frequency of safety confirmation actions, etc.). . For example, if the terminal device 22 determines that the driving situation is highly dangerous, it may cause the warning indicator light 26 to flash in red, or if it determines that the driving situation is not highly dangerous, it may cause the warning indicator light 26 to blink in red. The warning indicator light 26 may be blinked in orange at longer intervals.

For example, when supporting the driver's visual confirmation of the rear of the vehicle C1A reflected in the left side mirror SM1, the terminal device 22 provides driving characteristic improvement support that lights up or blinks the warning indicator light 26B located on the left side. Execute. In addition, when supporting the driver's visual confirmation of the rear of the vehicle C1A reflected in the right side mirror SM2, the terminal device 22 executes driving characteristic improvement support by lighting or blinking the warning indicator light 26B located on the right side. . Thereby, the terminal device 22 can guide the driver's line of sight to the left side mirror SM1 (that is, the left side) or the right side mirror SM2 (that is, the right side) that corresponds to the driving scene by lighting or blinking the warning indicator light 26B. .

Further, for example, when the terminal device 22 detects a pedestrian, another vehicle, a two-wheeled vehicle, etc. on the left or right side of the vehicle C1A, the terminal device 22 executes driving characteristic improvement support that prompts the driver to visually check the right side of the vehicle C1A. . Specifically, the terminal device 22 supports driving characteristic improvement by lighting or blinking warning indicator lights 26A and 26B in a predetermined color, which are placed on the left or right side where a pedestrian, other vehicle, two-wheeled vehicle, etc. is detected. Execute.

Furthermore, for example, the terminal device 22 can measure the distance between the own vehicle and a detected pedestrian, other vehicle, two-wheeled vehicle, etc., the approaching speed between the pedestrian, other vehicle, two-wheeled vehicle, etc. approaching the own vehicle, etc. calculate. The terminal device 22 determines the degree of danger of the driving scene based on the calculated distance, approach speed, etc., and changes the color and blinking pattern of the warning indicator lamp 26A or warning indicator lamp 26B in accordance with the degree of danger of the driving situation. , determine the blinking speed, etc.

Specifically, when the terminal device 22 determines that the own vehicle does not require driving operations such as deceleration or stopping based on the calculated distance or the distance and the approaching speed, the terminal device 22 turns on the warning indicator light 26A or the warning indicator light. 26B blinks in orange, and when it is determined that the own vehicle does not require driving operations such as deceleration or stopping, the warning indicator light 26A or 26B blinks in red at shorter intervals. Thereby, the driver can intuitively understand the importance of safety confirmation actions at a glance based on the color, flashing pattern, flashing speed, etc. of the warning indicator light 26A or the warning indicator light 26B.

Next, with reference to FIG. 28, the speakers 25 mounted on the vehicles C1A, . . . will be described. FIG. 28 is a diagram illustrating an example of the arrangement of the speakers 25.

In the example shown in FIG. 28, four speakers 25A, 25B, 25C, and 25D are mounted inside the vehicles C1A, . . . , respectively. The speaker 25A is mounted on the dashboard DSB of each vehicle C1A, . . . near the left A-pillar or the left side mirror SM1. The speaker 25B is mounted on the dashboard DSB of each vehicle C1A, . . . near the right A-pillar or the right side mirror SM2. The speaker 25C is mounted near the left rear seat or the left C-pillar (not shown) of the vehicle C1A, . The speaker 25D is mounted near the left rear seat or the left C-pillar (not shown) of the vehicle C1A, . Note that the arrangement positions of the four speakers 25A, 25B, 25C, and 25D shown in FIG. 28 are merely examples, and it goes without saying that the arrangement is not limited thereto.

When the terminal device 22 detects an object approaching the own vehicle (for example, a pedestrian, another vehicle, a motorcycle, etc.), an obstacle around the own vehicle, etc. using various sensors, the terminal device 22 activates each of the four speakers 25A to 25D. A speaker at a position corresponding to the detected approaching object or obstacle is made to output a sound indicating that the approaching object or obstacle has been detected.

For example, the terminal device 22 uses the in-vehicle camera 13A and the out-vehicle sensor/camera 19A in a driving scene "when changing lanes" in which the vehicle is changing lanes from the lane in which it is currently traveling to the lane on the right in the direction of travel. Detects other vehicles approaching from the rear right side of the own vehicle using various sensors such as In such a case, the terminal device 22 performs driving characteristic improvement support by outputting audio from the speaker 25D located in the direction in which the other vehicle is detected (in this case, right rear), and performs safety confirmation on the right rear. encourage drivers to

Further, for example, in the driving scene "when turning left", the terminal device 22 detects the approach of a pedestrian from the front in the direction of travel of the own vehicle using various sensors such as the inside camera 13A and the outside sensor/camera 19A. In such a case, the terminal device 22 performs driving characteristic improvement support by outputting audio from the speaker 25B placed in the direction in which the pedestrian is detected (in this case, the left front), and performs a safety check on the left front. encourage drivers to

For example, when the terminal device 22 determines that it is necessary to visually check the rear of the own vehicle using various sensors such as the in-vehicle camera 13A and the outside sensor/camera 19A, the terminal device 22 may use two speakers 25C arranged at the rear of the own vehicle, By outputting audio from each of the 25D, driving characteristics improvement support is performed and the driver is urged to check the safety of the rear.

In addition, the terminal device 22 analyzes approaching objects or obstacles detected by various sensors such as the in-vehicle camera 13A and the outside sensor/camera 19A, and analyzes the type of the detected approaching object or obstacle (for example, pedestrian, etc.). (vehicles, motorcycles, etc.) may be output to each of the speakers 25A to 25D. For example, when the terminal device 22 detects a pedestrian approaching from the sidewalk, it displays "A pedestrian is approaching from the sidewalk", and when it detects a bicycle (two-wheeled vehicle) approaching from behind, it displays "A bicycle from behind". The speakers 25A to 25D output a sound such as "A vehicle is approaching" to perform driving characteristic improvement support.

Next, with reference to FIG. 29, a modification example of the driving characteristic improvement support method indicated by the improvement effect data will be described. FIG. 29 is a diagram illustrating a modification example of driving characteristic improvement support. Note that the example of the driving characteristic improvement support method and the modification example of the driving characteristic improvement support shown in FIG. 29 are merely examples, and the present invention is not limited thereto.

The driving characteristic improvement server S3 stores the frequency of the driver's previous safety confirmation behavior based on the driving characteristic data (specifically, behavioral characteristic data) in the driving scene to which the driver's user ID is linked, and the vehicle C1A. The frequency of the latest driver safety confirmation behavior based on the driving characteristic data (specifically, behavior characteristic data) in the driving situation acquired from ,... is calculated, respectively, and improvement effect data corresponding to the driving situation information is calculated. The change in the frequency of the driver's safety confirmation behavior before and after the driving characteristic improvement support performed based on the above is determined.

Specifically, the driving characteristic improvement server S3 determines whether or not the driver's safety confirmation behavior in this driving scene is increasing, based on the frequency of the previous safety confirmation behavior and the latest frequency of safety confirmation behavior. In other words, it is determined whether or not the driving characteristics have improved. The driving characteristic improvement server S3 collects this driving scene information based on the acquired emotional data and the determination result of whether the frequency of safety confirmation behavior is increasing (that is, whether the driving characteristics are improving or not). Generate and update new improvement effect data corresponding to. The driving characteristic improvement server S3 transmits the generated improvement effect data to the vehicles C1A, . Note that the driving characteristic improvement server S3 may execute the improvement effect data generation process periodically (for example, every day, every week, every month, etc.).

The driving characteristics improvement server S3 determines that the acquired emotional data of the driver indicates a positive emotion of "pleasure" and that the frequency of safety confirmation behavior after driving characteristics improvement support has increased (i.e. , the driving characteristics have improved), the driver's driving characteristics have improved, and the driving characteristics improvement support method indicated by the improvement effect data corresponding to this driving characteristics information (that is, the driving characteristics improvement support method (that is, the speaker 25 or warning display) is determined to be improved. control method of the light 26) is determined to be more effective. In such a case, the driving characteristic improvement server S3 generates improvement effect data corresponding to this driving scene information as new improvement effect data of other driving scene information, and links it to other driving scene information to improve the improvement effect. Register (update) in database DB4.

On the other hand, the driving characteristics improvement server S3 determines that the acquired emotional data of the driver indicates a positive emotion of "pleasure" and that the frequency of safety confirmation behavior after driving characteristics improvement support has not increased. (In other words, the driving characteristics have not improved), the driver's driving characteristics have not improved, but the driving characteristics improvement support method indicated by the improvement effect data corresponding to this driving characteristics information (in other words, the Alternatively, it is determined that the method for controlling the warning indicator light 26 is effective. In such a case, the driving characteristic improvement server S3 generates new improvement effect data that increases the frequency of driving characteristic improvement support indicated by the improvement effect data corresponding to this driving scene information, and registers it in the improvement effect database DB4. (Update.

In addition, the driving characteristic improvement server S3 determines that the acquired emotional data of the driver indicates a negative emotion of "unpleasantness" and that the frequency of safety confirmation behavior after driving characteristic improvement support has increased. (In other words, the driver's driving characteristics have improved). control method) needs to be changed. In such a case, the driving characteristic improvement server S3 generates effect improvement data different from the improvement effect data corresponding to this driving scene information, and registers (updates) it in the improvement effect database DB4 as new improvement effect data of this driving scene information. ) and is also registered (updated) in the improvement effect database DB4 as new improvement effect data of other driving scene information.

On the other hand, the driving characteristics improvement server S3 determines that the acquired emotional data of the driver indicates a positive emotion of "pleasure" and that the frequency of safety confirmation behavior after driving characteristics improvement support has not increased. (In other words, the driver's driving characteristics have not improved), the driving characteristics of this driver have not improved, and the currently set driving characteristics improvement support method (in other words, the driver's driving characteristics have not improved) control method) is determined to be invalid. In such a case, the driving characteristic improvement server S3 generates effect improvement data different from the improvement effect data corresponding to this driving scene information, and registers (updates) it in the improvement effect database DB4 as new improvement effect data of this driving scene information. )do.

For example, if the current improvement effect data is a support method that uses the speaker 25 and the warning indicator light 26 to perform a safety confirmation action, the driving characteristic improvement server S3 selects one of the speaker 25 and the warning indicator light 26. If the current improvement effect data is a support method that uses the warning indicator light 26 to perform a safety confirmation action, the speaker 25 is used to generate new improvement effect data to perform a safety confirmation action. Generate new improvement effect data to implement actions.

As described above, the driving characteristics improvement server S3 in the second embodiment can improve the driving characteristics based on the driving characteristics improvement status corresponding to the frequency of the driver's safety confirmation behavior and the driver's reaction (emotional data) due to the driving characteristics improvement support. , it is possible to set a driving characteristic improvement support method that is more suitable for the driver.

Next, the operating procedure of the driving characteristic improvement support system 200 according to the second embodiment will be described with reference to FIGS. 30 and 31, respectively. FIG. 30 is a flowchart illustrating an example of the operating procedure of the driving characteristic improvement support system 200 according to the second embodiment. FIG. 31 is a flowchart illustrating an example of the operating procedure of the driving characteristic improvement support system 200 according to the second embodiment.

Each of the vehicles C1A, . . . in the driving characteristic improvement support system 200 waits in a sleep state (St51). Each of the vehicles C1A, . . . determines whether the in-vehicle sensor 24 detects a driver approaching the vehicle (St52). For example, each of the vehicles C1A, . . . determines that a driver approaching the own vehicle is detected when it is determined that a radio wave transmitted by a smart key, smartphone, etc. owned by the driver is detected.

If each of the vehicles C1A,... determines in the process of step St52 that the in-vehicle sensor 24 has detected a driver approaching the own vehicle (St52, YES), each of the vehicles C1A,... (St53).

On the other hand, if each of the vehicles C1A,... determines in the process of step St52 that the in-vehicle sensor 24 does not detect the driver approaching the own vehicle (St52, NO), the process moves to step St51, The computer waits in a sleep state (St51).

Each of the vehicles C1A, . . . acquires driving characteristic data of the driver using various sensors and starts monitoring driving behavior in the current driving scene (St54). Each of the vehicles C1A, . . . determines whether the current driving situation is a driving situation that requires a safety confirmation action and the degree of risk (score) of the current driving situation is equal to or higher than a predetermined value. (St55).

In each of the vehicles C1A,..., in the process of step St55, the current driving scene is a driving scene that requires safety confirmation behavior, and the degree of risk (score) of the current driving scene is equal to or higher than a predetermined value. If it is determined that (St55, YES), based on the acquired driving characteristic data (specifically, behavioral characteristic data), it is determined whether the execution of the safety confirmation behavior by the driver is detected (St56). . Note that here, there may be a plurality of safety confirmation actions corresponding to the driving scene. In addition, if there are multiple safety confirmation actions corresponding to a driving situation and the order in which they are performed is determined, each of the vehicles C1A,... You may decide whether

In each of the vehicles C1A, ..., when it is determined in the process of step St56 that execution of a safety confirmation behavior by the driver is detected based on the acquired driving characteristic data (specifically, behavioral characteristic data) ( St56, YES), the acquired driving characteristic data, driving scene information, emotional data for driving characteristic improvement support corresponding to the driving scene information, and user ID are linked and transmitted to the driving characteristic improvement server S3. , is stored in the memory 15A. Each of the vehicles C1A, ... acquires new improvement effect data transmitted from the driving characteristic improvement server S3, and updates (changes) the current improvement effect data of the driving scene information to the acquired new improvement effect data. (St57).

On the other hand, in the process of step St56, each of the vehicles C1A, ... has not detected execution of the safety confirmation behavior by the driver based on the acquired driving characteristic data (specifically, behavioral characteristic data). If determined (St56, NO), driving characteristic improvement support is executed based on the current driver's driving characteristic data (that is, driving skill) and the improvement effect data corresponding to the driving scene information (St58).

Each of the vehicles C1A, . . . analyzes the captured image captured by the in-vehicle camera 13A, and analyzes the driver's reaction (emotional data) to the executed driving characteristic improvement support and the driver's behavior characteristic data. Each of the vehicles C1A, . . . accumulates and stores driving characteristic data including the acquired behavioral characteristic data in the memory 15A. Further, each of the vehicles C1A, . . . transmits the driving scene information, the driver's emotional data regarding the driving characteristic improvement support, the driving characteristic data, and the user ID in a linked manner to the driving characteristic improvement server S3. Each of the vehicles C1A, ... acquires new improvement effect data transmitted from the driving characteristic improvement server S3, and updates (changes) the current improvement effect data of the driving scene information to the acquired new improvement effect data. (St59).

On the other hand, in the process of step St55, each of the vehicles C1A, ... determines that the current driving scene is a driving scene that requires safety confirmation behavior, and that the degree of risk (score) of the current driving scene is greater than or equal to a predetermined value. If it is determined that it is not (St55, NO), based on the acquired driving characteristic data (specifically, behavioral characteristic data), it is determined whether or not the execution of the safety confirmation behavior by the driver is detected (St60). ).

In each of the vehicles C1A, ..., when it is determined in the process of step St60 that execution of a safety confirmation behavior by the driver is detected based on the acquired driving characteristic data (specifically, behavioral characteristic data) ( St60, YES), the acquired driving characteristic data, driving scene information, driver's emotional data regarding driving characteristic improvement support, and user ID are linked and transmitted to the driving characteristic improvement server S3, and the memory 15A to be memorized. Each of the vehicles C1A, ... acquires new improvement effect data transmitted from the driving characteristic improvement server S3, and updates (changes) the current improvement effect data of the driving scene information to the acquired new improvement effect data. (St57).

On the other hand, in the process of step St60, each of the vehicles C1A, ... has not detected execution of the safety confirmation behavior by the driver based on the acquired driving characteristic data (specifically, behavioral characteristic data). If it is determined (St60, NO), based on the driver's current driving characteristics (that is, the frequency of the latest safety confirmation behavior in the current driving situation), driving characteristic improvement support is executed to improve safety corresponding to the driving situation. It is determined whether confirmation action is to be encouraged (St61).

Specifically, in the process of step St61, each of the vehicles C1A, . . . calculates the frequency of the latest safety confirmation behavior in the current driving situation indicated by the current driving characteristics. For each of the vehicles C1A,..., check whether the latest calculated frequency of safety confirmation behavior is equal to or higher than a threshold regarding the frequency of safety confirmation behavior set corresponding to the degree of risk (score) of the current driving scene. Determine.

For example, if the driving scene is "driving on a straight road" and the risk level (score) corresponding to this driving scene is "low", the threshold for the frequency of safety confirmation behavior is set to 1/4. . In such a case, each of the vehicles C1A, . . . determines whether the frequency of the latest safety confirmation behavior of the driver in the driving scene "while driving on a straight road" is 1/4 or more.

Furthermore, for example, if the driving scene is "changing lanes" and the risk level (score) corresponding to this driving scene is "high", the threshold for the frequency of safety confirmation behavior is set to 1/2. Ru. In such a case, each of the vehicles C1A, . . . determines whether the frequency of the driver's latest safety confirmation behavior in the driving scene "when changing lanes" is 1/2 or more.

When each of the vehicles C1A,... determines in the process of step St61 to execute driving characteristic improvement support based on the driver's current driving characteristics to encourage safety confirmation behavior corresponding to the driving situation (St61, YES), driving characteristic improvement support is executed based on the current driving characteristic data (that is, driving skill) of the driver and the improvement effect data corresponding to the driving scene information (St58). Specifically, for each of the vehicles C1A,..., the calculated frequency of the latest safety confirmation behavior is not equal to or greater than a threshold regarding the frequency of safety confirmation behavior set corresponding to the degree of risk (score) of the current driving scene. If it is determined that this is the case, it is determined that driving characteristic improvement support is executed to encourage safety confirmation behavior corresponding to the driving situation (St61, YES).

On the other hand, if each of the vehicles C1A,... determines in the process of step St61 not to perform driving characteristic improvement support and encourage safety confirmation behavior corresponding to the driving situation based on the driver's current driving characteristics. (St61, NO), the acquired driving characteristic data, driving scene information, driver's emotional data regarding driving characteristic improvement support, and user ID are linked and transmitted to the driving characteristic improvement server S3, and the memory Store in 15A. Each of the vehicles C1A, ... acquires new improvement effect data transmitted from the driving characteristic improvement server S3, and updates (changes) the current improvement effect data of the driving scene information to the acquired new improvement effect data. (St57). Specifically, each of the vehicles C1A,... If it is determined that there is, it is determined that driving characteristic improvement support is not executed to prompt safety confirmation behavior corresponding to the driving situation (St61, NO).

Each of the vehicles C1A, . . . determines whether or not the end of driving by the driver is detected (St). Note that the term "completion of driving" as used herein may mean that the driver gets off the vehicle and moves away from the host vehicle by a predetermined distance or more.

In each of the vehicles C1A,..., if it is determined in the process of step St62 that the end of driving by the driver is detected (St62, YES), the driving behavior sensing system is ended (St63), and the vehicle enters the sleep state again. Wait (St51).

On the other hand, if it is determined in the process of step St62 that the completion of driving by the driver has not been detected (St62, NO), each of the vehicles C1A,... moves to the process of step St55, and each of the vehicles C1A,... It is determined again whether the current driving scene is a driving scene that requires a safety confirmation action and the degree of risk (score) of the current driving scene is equal to or higher than a predetermined value (St55).

As described above, each of the vehicles C1A, ... in the second embodiment supports the driver's safety confirmation behavior based on the driving situation and the driver's driving characteristics (driving skill). It can help improve characteristics (driving skills). Further, the driving characteristic improvement server S3 in the second embodiment is configured to improve the performance of the driver based on the driving scene, the driver's driving characteristics (driving skill), and the driver's reaction (emotional data) to the driving characteristic improvement support. A suitable driving characteristic improvement support method (improvement effect data) can be determined. Therefore, each of the vehicles C1A, . (driving skills) can be supported.

As described above, the driving characteristic improvement server S3 according to the second embodiment is one or more computers that can communicate with at least one vehicle C1A, . . . . The driving characteristic improvement support data management method executed by the driving characteristic improvement server S3 is a driving characteristic improvement effect data management method executed by one or more computers capable of communicating with at least one vehicle C1A,... There is a plurality of driving scene information indicating driving scenes of vehicles C1A, ... and improvement effect data (support data) that supports improvement of safety confirmation behavior of drivers driving vehicles C1A, ... corresponding to the driving scene information. (one example) and the driver's driving characteristic data in the driving scene information are linked and registered for each user ID (an example of a driver ID) of multiple drivers, and the driving scene information and improvement effect data are respectively registered. Linked and transmitted to the vehicle C1A,..., the user ID of the driver driving the vehicle C1A,..., the driver's driving characteristic data corresponding to the driving scene information, and the driver's support based on the improvement effect data. The obtained user ID is checked against each user ID of multiple drivers, and the driving characteristic data linked to the checked user ID and the obtained driving Based on the characteristic data and emotion data, new improvement effect data corresponding to the acquired driving scene information is generated, and the acquired driving scene information is generated from among the plurality of driving scene information linked to the verified user ID. The improvement effect data linked to the same driving scene information as the scene information is updated to the generated new improvement effect data. Note that the computer referred to here is configured to include at least the driving characteristic improvement server S3.

As a result, the driving characteristic improvement server S3 according to the second embodiment receives the driving scene information and the driver's driving performance as the driving characteristic improvement support result using the improvement effect data transmitted in advance to each of the vehicles C1A,... It is possible to acquire the characteristics and the driver's emotional data regarding the driving characteristic improvement support (an example of support for safety confirmation behavior) indicated by the improvement effect data. The driving characteristics improvement server S3 generates new improvement effect data based on the acquired current state of the driver (that is, the driver's driving characteristics (driving skills) and emotions), and also generates new improvement effect data By linking the data, driving scene information, driving characteristic data, and emotional data used to generate this new improvement effect data to the user ID, improvement effect data for each user ID can be generated more efficiently. can be managed.

Further, as described above, the driving characteristic improvement server S3 according to the second embodiment uses the acquired driving characteristic data and the registered driving characteristic data to determine whether the driver's driving characteristics in the driving scene have improved. Then, new improvement effect data is generated based on the emotion data and the determination result as to whether or not the driving characteristics have improved. Thereby, the driving characteristic improvement server S3 according to the second embodiment can generate improvement effect data more suitable for the current driver's condition (that is, the driver's driving characteristics (driving skill) and emotions).

Further, as described above, when the driving characteristic improvement server S3 according to the second embodiment determines that the emotional data is positive and the driving characteristics have improved, the driving characteristic improvement server S3 according to the second embodiment The improvement effect data linked to the plurality of driving scene information is updated to the generated new improvement effect data. As a result, the driving characteristics improvement server S3 according to the second embodiment determines that the driving characteristics of the driver have improved, and the improvement effect data (i.e., driving performance that the driver feels comfortable (i.e., positive)). Improvement effect data indicating a driving characteristic improvement support method that is more suitable for the driver can be created by continuing the characteristics improvement support method) in the current driving situation and generating and updating new improvement effect data in other driving situations. can be managed more efficiently.

Further, as described above, when the driving characteristic improvement server S3 according to the second embodiment determines that the emotional data is positive and the driving characteristics have not improved, the driving characteristic improvement server S3 according to the second embodiment New improvement effect data is generated in which the frequency of support is increased compared to the improvement effect data, and the improvement effect data linked to the same driving scene information as the acquired driving scene information is used as the generated new improvement effect data. Update to data. As a result, the driving characteristics improvement server S3 according to the second embodiment can implement new improvements that increase the frequency of support based on the improvement effect data (i.e., the driving characteristics improvement support method) that the driver feels comfortable (i.e., positively). By generating and updating the effect data, it is possible to more efficiently manage the improvement effect data indicating a driving characteristic improvement support method more suitable for the driver.

Further, as described above, when the driving characteristic improvement server S3 according to the second embodiment determines that the emotional data is negative and the driving characteristics have been improved, the driving characteristic improvement server S3 according to the second embodiment can provide an improvement effect corresponding to the acquired driving scene information. Generate new improvement effect data different from the data, and update the improvement effect data linked to other driving situation information different from the acquired driving scene information to the generated new improvement effect data, and Omitting changes to improvement effect data linked to the same driving scene information as the driving scene information. As a result, the driving characteristics improvement server S3 according to the second embodiment determines that the driver's driving characteristics have improved and the improvement effect data (i.e., driving In addition to generating and updating new improvement effect data for the same driving situation (characteristic improvement support method), improvement effect data that is different from the improvement effect data that the driver felt uncomfortable (that is, negative) in other driving situations. By generating and updating the improvement effect data as new improvement effect data, it is possible to more efficiently manage the improvement effect data indicating a driving characteristic improvement support method more suitable for the driver.

Further, as described above, when the driving characteristic improvement server S3 according to the second embodiment determines that the emotional data is negative and the driving characteristics have not improved, the driving characteristic improvement server S3 according to the second embodiment New improvement effect data different from the improvement effect data is generated, and improvement effect data linked to the same driving scene information as the acquired driving scene information is updated to the generated new improvement effect data. As a result, the driving characteristics improvement server S3 according to the second embodiment determines that the driving characteristics of the driver have not improved, and the improvement effect data (i.e., , driving characteristic improvement support method) is generated and updated as new improvement effect data for the current driving situation, and the driver is similarly uncomfortable (that is, negative) in other driving situations. By generating and updating improvement effect data that is different from the improvement effect data perceived by the driver as new improvement effect data, it is possible to more efficiently manage improvement effect data that indicates driving characteristic improvement support methods that are more suitable for the driver. .

Furthermore, as described above, the improvement effect data generated by the driving characteristic improvement server S3 according to the second embodiment is transmitted to the speaker 25 or the warning indicator light installed in the vehicle C1A, which executes driving characteristic improvement support by sound or light. 26 (an example of a safe driving support device). Thereby, the driving characteristic improvement server S3 according to the second embodiment can more efficiently manage the control commands for the speaker 25 or the warning indicator light 26 in the driving characteristic improvement support executed in each vehicle C1A, . . . .

In addition, as described above, the improvement effect data generated by the driving characteristic improvement server S3 according to the second embodiment is a control command for controlling the safe driving support equipment installed in the vehicle C1A, ..., which performs support by voice or light. If the emotion data is negative, new improvement effect data is generated that causes support to be performed using either voice or light. As a result, when the driving characteristic improvement server S3 according to the second embodiment determines that the driver feels uncomfortable (that is, negatively) with the support method based on the current improvement effect data, the driving characteristic improvement server S3 according to the second embodiment By generating and updating new improvement effect data for the changed support method, it is possible to more efficiently manage the improvement effect data indicating the driving characteristic improvement support method more suitable for the driver. For example, if the current improvement effect data is a support method that uses the speaker 25 and the warning indicator light 26 to perform a safety confirmation action, the driving characteristic improvement server S3 controls whether the speaker 25 or the warning indicator light 26 is activated. If the current improvement effect data is a support method that uses the warning indicator light 26 to perform a safety confirmation action, the speaker 25 is used to generate new improvement effect data to perform a safety confirmation action. Generate new improvement effect data to implement actions.

In addition, as described above, the improvement effect data generated by the driving characteristic improvement server S3 according to the second embodiment is a control command for controlling the safe driving support equipment installed in the vehicle C1A, ... that performs support by sound or light. If the emotional data is negative, new improvement effect data is generated in which the frequency of audio or light assistance is reduced compared to the improvement effect data corresponding to the acquired driving scene information. As a result, when the driving characteristic improvement server S3 according to the second embodiment determines that the driver feels uncomfortable (that is, negatively) with the support method based on the current improvement effect data, the driving characteristic improvement server S3 according to the second embodiment By generating and updating new improvement effect data that reduces the frequency of improvement support, it is possible to more efficiently manage the improvement effect data that indicates a driving characteristic improvement support method that is more suitable for the driver.

As described above, the vehicles C1A, ... according to the second embodiment can check the safety of the driver who drives the vehicle C1A, ... in response to a plurality of driving scene information indicating the driving scenes of the vehicle C1A, ... and the driving scene information. Improvement effect data that supports behavior improvement is linked and stored with the driver's user ID, and support is provided based on the driver's driving characteristic data in the driving scene information and the improvement effect data corresponding to the driving scene information. The driver's emotional data is acquired by various sensors (an example of a sensor), and the acquired driving characteristic data and emotional data are linked to the driving situation information from which the driving characteristic data and emotional data were acquired, and the user ID. and transmits it to an external device, acquires new improvement effect data corresponding to the driving scene information sent from the external device, and transfers the improvement effect data linked to the driving scene information to the acquired new improvement effect. Update to data. Moreover, one or more computers mounted on the vehicles C1A, . . . here may be configured by the terminal device 22, the ECU 16A, or the like.

As a result, the vehicles C1A, ... according to the second embodiment receive the driving scene information and the driver's driving characteristics as the driving characteristic improvement support result based on the acquired improvement effect data transmitted from the driving characteristic improvement server S3. By transmitting the driver's emotional data regarding the driving characteristic improvement support (an example of safety confirmation behavior support) to the driving characteristic improvement server S3, the driver's current state (that is, the driver's current driving characteristic data, New improvement effect data based on emotional data) can be obtained. In addition, each of the vehicles C1A, . By linking, improvement effect data can be managed more efficiently.

(Details leading to Embodiment 3)
In recent years, the history of driving operations of drivers has been developed as a technology to suppress the increase in accidents caused by driving errors and forgetting to check safety as elderly drivers age, and to extend the driving life of elderly drivers. There is a driving support method that uses a learning model (hereinafter referred to as "artificial intelligence") that is trained as learning data to provide driving support to improve the driving characteristics of the driver. However, when a driver drives two or more vehicles (e.g., a private car, a rental car, etc.), such driving support methods are difficult to use because each vehicle has driving support devices (e.g., pillars, side mirrors, room mirrors, etc.). Because the location, type, number, etc. of warning indicators (warning indicators, speakers, and other audio output devices) differ, there is a problem in that the driving support methods and the driving support effects obtained differ from vehicle to vehicle. Therefore, in a driving support method, it has been desired to transfer driving support and driving support data between a plurality of vehicles driven by the same driver so that the driver can obtain the same driving support effect.

Conventionally, Patent Document 5 discloses an information processing device that transfers learning data used for learning of artificial intelligence between two artificial intelligences that use different algorithms. In learning artificial intelligence using two different algorithms, the information processing device may omit taking over raw data before the data format is changed and learning data attached with learning results by each artificial intelligence. However, the information processing device is capable of handing over learning data, including the learning results of driving support suitable for the driver, between different artificial intelligences that use different algorithms for each vehicle. It has been difficult to manage the intelligence and the artificial intelligence learned to support the driving of each vehicle.

Patent Document 6 discloses an artificial intelligence service that generates an artificial intelligence model suitable for the user's characteristics by converting or modifying the base artificial intelligence model to be suitable for the characteristics extracted from the user's information. has been done. Furthermore, in Patent Document 7, two artificial intelligence applications are used, the generated artificial intelligence (learning results) is managed by one artificial intelligence application in a secure environment, and the user's personal information is managed in a non-secure environment. Managed by another artificial intelligence application. However, artificial intelligence services and artificial intelligence systems are compatible with each vehicle and separate and manage the base artificial intelligence that uses different algorithms and the artificial intelligence that has been trained to suit the driver of each vehicle. It is not assumed that the data indicating the driving characteristics of the driver (that is, the learning data) will be passed on to a device other than the vehicle for use.

Therefore, in Embodiment 3 below, an example of a control method that supports management of driver driving characteristic data collected in different vehicles and handing over of driver driving characteristic data between vehicles will be described. In the following description, the same reference numerals are used for the same components as in Embodiment 1 or Embodiment 2, and the description thereof will be omitted.

The personal characteristic data in Embodiment 3 includes vehicle-related information (for example, vehicle inspection history information), driver driving characteristic data collected by the vehicle, driving characteristic evaluation results, safety confirmation behavior data, and improvement effect data. , shows driver emotional data regarding driving characteristic improvement support. Personal information is data related to the driver obtained by a wireless terminal device, etc. that can accept input operations by the driver, the driver's relatives, etc., including the driver's name, biological information (the driver's face image, iris , fingerprints, veins, voice, etc.), driver's license ID, and daily life information (TV viewing, bathing, toilet, sleep, etc.).

(Embodiment 3)
An example use case of the driving characteristic improvement support system 300 according to the third embodiment will be described with reference to FIG. 32. FIG. 32 is a diagram illustrating an example use case of the driving characteristic improvement support system 300 according to the third embodiment.

The driving characteristic improvement support system 300 includes each of two or more vehicles C2A, C2B, . . . , a driving characteristic improvement server S4, a network NWB, a wireless terminal device P2, and an operation terminal P3. Note that the operating terminal P3 is not essential and may be omitted.

Similar to the driving characteristic improvement support system 200 described in the second embodiment, the driving characteristic improvement support system 300 receives driving characteristic data, which is the driver's personal characteristic data, and safety confirmation behavior data from one vehicle C2A. get. The driving characteristic improvement support system 300 transmits the acquired personal characteristic data to the driving characteristic improvement server S4. The driving characteristic improvement support system 300 determines whether or not the driver's driving characteristics have improved based on the driver's driving skill indicated by the driving characteristic data and the driver's safety confirmation behavior while driving indicated by the safety confirmation behavior data. The driving characteristic improvement evaluation result is recorded in the driving characteristic improvement server S4 and transmitted to the vehicle C2A. The driving characteristic improvement support system 300 updates the improvement effect data (an example of new improvement effect data) indicating the content of driving support for the driver in the vehicle C2A based on the driving characteristic improvement evaluation result, and updates the updated improvement effect data to the vehicle C2A. Executes driving characteristic improvement support based on data.

In addition, when the driving characteristic improvement support system 300 detects that the driver who was driving the vehicle C2A has gotten into a vehicle C2B different from the vehicle C2A, the driving characteristic improvement support system 300 performs a transfer data list TB9 (see FIG. 39), the handover data acquired by vehicle C2A is transmitted to vehicle C2B. Further, the driving characteristic improvement support system 300 performs driving characteristic improvement support executed by the vehicle C2B by learning using the driver's driving characteristic improvement evaluation results in the vehicle C2A and the driver's personal information or personal characteristic data. By generating artificial intelligence (learned data) and transmitting it to the vehicle C2B, support for improving the driving characteristics of the driver in the vehicle C2B is executed.

The transfer data list TB9 is set in advance by the driver or the driver's relatives, and is a list of the personal information and personal characteristic data of the driver between different vehicles C2A, C2B,... This is data indicating whether or not the transfer is possible. The driving characteristic improvement support system 300 improves the performance of drivers in multiple vehicles by passing transferable personal information or personal characteristic data (hereinafter referred to as "transfer data") between different vehicles in the transfer data list TB9. Make driving characteristic improvement support possible.

Note that the handover data list may be set or generated for each vehicle that is a handover destination. For example, the transferable data list corresponding to a specific vehicle owned by a relative may be different from the transferable data list corresponding to vehicles shared through car sharing, rental cars, etc., and personal characteristic data that can be transferred. . Thereby, the driving characteristic improvement support system 300 can prevent personal information and personal characteristic data from being transferred to a vehicle that is not intended by the driver.

Each of the vehicles C2A, . . . is connected to the driving characteristic improvement server S4 and the operating terminal P3 via the network NWB so as to be able to communicate wirelessly. Note that the wireless communication referred to here includes, for example, a wireless LAN represented by Wi-Fi (registered trademark), a cellular communication system (mobile communication system), and the type thereof is not particularly limited. Moreover, each of the vehicles C2A, . . . may be connected to the wireless terminal device P2 so as to be capable of wireless communication.

Each of the vehicles C2A, ... identifies the driver driving the own vehicle, and uses artificial intelligence to support improvement of driving characteristics corresponding to the identified driver, to the driver described in Embodiment 2. We will begin providing support for improving the driving characteristics of drivers and acquiring data on their driving characteristics. Further, each of the vehicles C2A, . . . starts determining (identifying) a driving scene. Each of the vehicles C2A, . . . executes driving characteristic improvement support for the driver (that is, support for safety confirmation behavior) using artificial intelligence, and acquires the driver's emotional data regarding this driving characteristic improvement support.

The artificial intelligence referred to here is learned data that supports the improvement of the driver's driving characteristics in each vehicle. The driving characteristic improvement server S4 uses the driving characteristics improvement server S4 to add personal information of the driver (for example, age, gender, daily life information, etc.) to the base artificial intelligence (hereinafter referred to as "base artificial intelligence") for each vehicle. It is generated through learning using characteristic data, improvement effect data for each driving situation, etc. Note that the generation of artificial intelligence may be executed by the ECU 16B, the terminal device 22 (see FIG. 33), etc. of each vehicle.

Each of the vehicles C2A, . , is transmitted to the driving characteristic improvement server S4. Note that the timing of transmitting these data may be periodically executed, or may be the timing at which the end of driving by the driver is detected.

In the following description, in order to make the description easier to understand, an example will be described in which the driver changes from vehicle C2A to vehicle C2B.

The driving characteristic improvement server S4, which is an example of a computer, has a function (driver authentication) that can be realized by the driving characteristic server S1 in the first embodiment, and a function (improvement) that can be realized by the driving characteristic improvement server S3 in the second embodiment. (Driving characteristic improvement support by generating and updating effect data) is possible.

The driving characteristic improvement server S4 is connected to each of the vehicles C2A, . . . and the wireless terminal device P2 so as to be capable of data communication via the network NWB. The driving characteristic improvement server S4 acquires the user ID of the driver, the vehicle ID of the own vehicle, and new personal characteristic data transmitted from each of the vehicles C2A, . Further, the driving characteristic improvement server S4 acquires the driver's personal information, the transfer data list, etc. transmitted from the wireless terminal device P2.

The driving characteristic improvement server S4 performs relearning using the acquired new personal characteristic data or personal information as learning data, and updates the artificial intelligence "A'" currently used in the vehicle C2A.

Further, the driving characteristic improvement server S4 determines whether the driver and the vehicle (i.e., vehicle C2B). The driving characteristic improvement server S4 extracts the personal information and personal characteristic data of the driver to be inherited by the specified vehicle C2B, based on the transfer data list corresponding to the specified driver. The driving characteristic improvement server S4 executes relearning on the base artificial intelligence "B" corresponding to the identified vehicle C2B using the extracted personal information and personal characteristic data as learning data, and performs relearning on the base artificial intelligence "B" corresponding to the identified vehicle C2B. An artificial intelligence "B'" suitable for the driver is generated and sent to the vehicle C2B.

The wireless terminal device P2 can accept input operations from the driver, the driver's relatives, etc., and has the same functions as the wireless terminal devices P1 and P1A, a function to generate a transfer data list based on the input operations, and a function to generate a transfer data list based on the input operations. A function of transmitting the driver's daily life information and the like to each of C2A, . . . or the driving characteristic improvement server S4 is realized. The wireless terminal device P2 displays on a monitor (not shown) a transfer list setting screen (see FIGS. 42 to 45) for generating a transfer data list of driver transfer data to be transferred between vehicles. Using the handover list setting screen, the wireless terminal device P2 accepts a driver's setting operation (selection operation, deletion operation, editing operation, etc.) of the handover data to be taken over between each vehicle based on the driver's operation, and sets the handover data. A list TB9 (see FIG. 39) is generated and sent to the driving characteristic improvement server S4.

Note that the transfer of data may be carried out using an external storage medium EM such as a USB memory (see Figure 39) by an administrator (e.g., a dealer) who has authority to view and manage this information (data). good. In such a case, the administrator uses the operation terminal P3, which can accept administrator operations and is connected to each of the vehicles C2A, C2B, etc. to enable wireless or wired communication, to perform inter-vehicle communication. The driver's transfer data (personal information, personal characteristic data) is transferred based on the transfer data list TB9.

The operation terminal P3, which is an example of a computer, can accept input operations by an administrator or the like, and is realized by, for example, a PC, a notebook PC, or the like. The operation terminal P3 is connected to the driving characteristic improvement server S4 and each vehicle C2A, . . . so as to enable wireless communication or wired communication.

The operation terminal P3 acquires the transfer data list TB9 of the driver designated by the administrator's operation from the driving characteristic improvement server S4. The operation terminal P3 acquires the driver's handover data corresponding to the handover data list TB9 from the vehicle C2A, and records it in the external storage medium EM (for example, a USB memory, etc.).

The operation terminal P3 associates the driver's handover data recorded in the external storage medium EM with a control command requesting an update of the artificial intelligence "B" used in the vehicle C2B, and sends it to the driving characteristics improvement server S4. Then, the driving characteristic improvement server S4 is made to update the artificial intelligence "B".

Note that when the same operation terminal P3 is used to transfer the transfer data from the vehicle C2A to the vehicle C2B, the driver's transfer data is stored (written) in an internal storage medium such as the memory 63 of the operation terminal P3. You can.

Further, the operation terminal P3 may be realized using an in-vehicle ECU installed in each vehicle. In such a case, the operating terminal P3 may, for example, connect the external storage medium EM to the in-vehicle ECU of the vehicle C2A so as to be able to transmit and receive data to record the driver's handover data, or connect the external storage medium EM to the in-vehicle ECU of the vehicle C2B. The driver's takeover data may be transmitted (written) by being connected to enable data transmission and reception.

The network NWB connects each of the plurality of vehicles C2A, . . . , the driving characteristic improvement server S4, the wireless terminal device P2, and the operating terminal P3 to enable wireless or wired communication.

Next, an example of the internal configuration of the vehicles C2A, . . . in the third embodiment will be described with reference to FIG. 33. FIG. 33 is a block diagram showing an example of the internal configuration of vehicles C2A, . . . in the third embodiment. The internal configuration of the vehicle C2A,... shown in FIG. 33 is an example of the internal configuration when the driver's face image is used as biometric information, and includes sensors for acquiring other biometric information, a driver's license reader, etc. illustration is omitted.

Since the vehicles C2A, . . . have similar internal configurations, the following description will mainly focus on the internal configuration of the vehicle C2A. Furthermore, the vehicles C2A,... realize the functions that can be realized by the vehicles C1,... in the first embodiment and the functions that can be realized by the vehicles C1A,... in the second embodiment, and the vehicles C1,..., It has the same configuration as C1A, . Therefore, in the following description, the same components as those of the vehicles C1, . . . , C1A, .

The vehicle C2A is configured to include at least a communication device 11A, a terminal device 22, an in-vehicle camera 13A, a gyro sensor 14, a memory 15B, and an ECU 16B. Each part inside the vehicle C2A is connected to enable data transmission and reception via CAN or the like.

The memory 15B includes, for example, a RAM as a work memory used when executing each process of the ECU 16B, and a ROM that stores programs and data that define the operations of the ECU 16B. Data or information generated or acquired by the ECU 16B is temporarily stored in the RAM. A program that defines the operation of the ECU 16B is written in the ROM. Further, the memory 15B may store one or more user IDs who drive the vehicle C2A and a driving characteristic history table TB3 (see FIG. 19).

Memory 15B stores artificial intelligence data 151. The artificial intelligence data 151 includes a base artificial intelligence "A" of the vehicle C1A and an artificial intelligence "A'" for executing driving characteristic improvement support suitable for the driver. Note that when there are multiple drivers, the memory 15B may include artificial intelligence suitable for each driver.

The ECU 16B collectively executes processing and control of each section. The ECU 16B is configured using a so-called electronic circuit control device, and realizes the functions of each section such as the AI processing section 161 by referring to programs and data held in the memory 15B and executing the programs. Furthermore, the ECU 16B can implement functions that can be implemented by the ECUs 16 and 16A (see FIGS. 2 and 18). The ECU 16B acquires information output from various sensors as driving characteristic data (personal characteristic data). ECU 16B outputs driving characteristic data to processor 22A.

The AI processing unit 161 uses the artificial intelligence "A'" recorded in the memory 15B to control the speaker 25, warning indicator light 26, etc., and executes driving characteristic improvement support. Note that the driving characteristic improvement support method executes driving characteristic improvement support based on the driver's personal information in addition to the driving characteristic improvement support method executed by the ECU 16A described in the second embodiment.

For example, the artificial intelligence "A'" is an artificial intelligence that is retrained using the driver's bedtime, wake-up time, breathing rate, and sleep quality (see Figure 45) included in the driver's daily life information "sleep" as learning data. When the driver's sleep time is short due to intelligence, the AI processing unit 161 makes the execution timing of driving characteristic improvement support earlier. As a result, even if the driver's response to driving characteristic improvement support is delayed due to sleep deprivation, vehicle C1A can quickly perform driving characteristic improvement support to help the driver at the timing when safety confirmation actions should be performed. We can support people to carry out safety confirmation actions.

In addition, when relearning (updating) the artificial intelligence "A'" in the vehicle C1A, the ECU 16B uses information acquired by various sensors (personal characteristic data) or the driver's personal information transmitted from the wireless terminal device P2. The artificial intelligence "A'" may be retrained using the information as learning data. The ECU 16B uses the re-learned artificial intelligence "A" to provide driving characteristic improvement support to the driver.

Note that the execution of the driving characteristic improvement support using the artificial intelligence data 151 and the relearning of the artificial intelligence may be executed by the processor 22A of the terminal device 22.

Next, with reference to FIG. 34, an example of the internal configuration of the driving characteristic improvement server S4 will be described. FIG. 34 is a block diagram showing an example of the internal configuration of the driving characteristic improvement server S4 in the third embodiment.

Further, the driving characteristic improvement server S4 realizes the functions that can be realized by the driving characteristic server S1 in the first embodiment and the functions that can be realized by the driving characteristic improvement server S3 in the second embodiment. It has a similar configuration. Therefore, in the following description, the same components as those of the driving characteristic improvement server S3 will be given the same reference numerals, and the description will be omitted.

The driving characteristic improvement server S4 includes a communication unit 51, a processor 520, a memory 530, and a database 540. Note that the database 540 may be configured as a separate entity that is connected to the driving characteristic improvement server S4 so as to enable data communication.

The processor 520 is configured using, for example, a CPU, a DSP, or an FPGA, and controls the operations of each section. Processor 520 cooperates with memory 530 to perform various types of processing and control in an integrated manner. Specifically, the processor 520 refers to the program and data held in the memory 530, and executes the program to control each unit such as the support method generation unit 52A, the personal characteristics management unit 52B, and the artificial intelligence learning unit 52C. Realize the functions of Further, the processor 520 realizes the functions of each section that can be realized by each of the processors 32 and 52 (see FIGS. 3 and 20).

When the driving characteristic learning model or driving scene data is updated, the processor 520 transmits the updated driving characteristic learning model or driving scene data to each of the vehicles C2A, . . . .

The processor 520 also acquires the user ID, vehicle ID, new personal characteristic data from each of the vehicles C2A, etc., or acquires the driver's personal information, transfer data list, etc. from the wireless terminal device P2. do. Based on the acquired data (information), the processor 520 executes transfer of transfer data (personal information and personal characteristic data), generation of artificial intelligence, relearning (update), and the like. The processor 520 transmits the generated or retrained artificial intelligence to each vehicle C2A, .

The personal characteristic management unit 52B uses the personal information and personal characteristic data acquired from each of the vehicles C2A, ... and the personal information acquired from the wireless terminal device P2 in the personal information/personal characteristic data table TB7. It is stored (registered) for each vehicle ID driven by a person ID.

The personal characteristic management unit 52B refers to the transfer data list database DB6 based on the acquired user ID or driver's personal information. The personal characteristics management unit 52B stores the driver's personal information stored in the personal information/personal characteristics database DB5 based on the acquired user ID or the transfer data list TB9 (see FIG. 39) corresponding to the driver's personal information. Among the information and personal characteristic data, driver handover data to be taken over from vehicle C2A to vehicle C2B is extracted. The personal characteristic management section 52B associates the extracted driver's handover data with the user ID and vehicle ID and outputs the linked data to the artificial intelligence learning section 52C.

The artificial intelligence learning section 52C refers to the improvement effect learning model 53B based on the vehicle ID output from the personal characteristic management section 52B, and obtains the base artificial intelligence of the vehicle corresponding to the vehicle ID. The artificial intelligence learning unit 52C performs learning on the acquired base artificial intelligence using the extracted driver's takeover data as learning data, and generates artificial intelligence capable of improving driving characteristics suitable for the driver. . The artificial intelligence learning section 52C outputs the generated artificial intelligence to the communication section 51, and causes the communication section 51 to transmit it to the corresponding vehicle.

In addition, when the artificial intelligence to which the acquired user ID information is associated is stored in the improvement effect learning model 53B, the artificial intelligence learning unit 52C transmits the driver's takeover data extracted to this artificial intelligence. Re-learning (updating) using learning data may be performed. For example, the artificial intelligence learning unit 52C stores in the improvement effect learning model 53B that the acquired vehicle ID indicates the vehicle C2A, and the artificial intelligence "A'" associated with the acquired user ID information is stored in the improvement effect learning model 53B. In this case, an artificial intelligence "A''" is generated by relearning this artificial intelligence "A'".

The memory 530 includes, for example, a RAM as a work memory used when the processor 520 executes each process, and a ROM that stores programs and data that define the operations of the processor 520. Data or information generated or acquired by the processor 520 is temporarily stored in the RAM. A program that defines the operation of the processor 520 is written in the ROM.

The memory 530 stores a driving characteristic learning model 53A and an improvement effect learning model 53B. Further, the memory 530 stores programs and data stored in the memories 33 and 53 (see FIGS. 3 and 20), and allows the processor 520 to realize each of the processors 32 and 52 (see FIGS. 3 and 20). This makes it possible to realize the functions of each part.

In addition, in the third embodiment, the improvement effect learning model 53B is configured to perform similar training for each of a plurality of different vehicles in accordance with the number and arrangement of the speakers 25, warning indicator lights 26, etc. provided in each of the vehicles C2A,... A base artificial intelligence model for executing driving characteristic improvement support is stored for each vehicle ID. In addition, the improvement effect learning model 53B is generated by executing learning using personal information and personal characteristic data as learning data on the base artificial intelligence (for example, base artificial intelligence "A", "B") for each vehicle. The artificial intelligence for each driver (for example, artificial intelligence "A'", "B'"), user ID and vehicle ID are stored in association with each other.

The database 540 records a user database DB1, a driving scene database DB2, a driving characteristics database DB3, an improvement effect database DB4, a personal information/personal characteristics database DB5, and a takeover data list database DB6.

The personal information/personal characteristics database DB5 stores personal information/personal characteristics data of one or more vehicles driven by the driver, personal information of the driver acquired by the vehicle corresponding to each vehicle ID, and personal characteristics data for each user ID. It is stored (registered) in the personal characteristic data table TB7 (see FIG. 36). The personal information/personal characteristics database DB5 includes the driver's personal information registered in the user database DB1 and the driver's daily life information transmitted from the wireless terminal device P2, as well as the driving characteristics database DB3 and the improvement effect database DB4. It may be a database that collectively stores (registers) and manages personal characteristic data registered in each.

The takeover data list database DB6 stores (registers) the takeover data list transmitted from the wireless terminal device P2 for each user ID.

Next, with reference to FIG. 35, an example of the internal configuration of the operating terminal P3 will be described. FIG. 35 is a block diagram showing an example of the internal configuration of operating terminal P3 in the third embodiment.

The operation terminal P3 includes a communication section 61, a processor 62, a memory 63, a display section 64, an input section 65, and a user database DB7. Note that the user database DB7 is not an essential configuration and may be omitted.

The communication unit 61 includes a transmitting circuit and a receiving circuit that transmit and receive data between each of the vehicles C2A, . . . and the driving characteristic improvement server S4 via the network NW. Further, the communication unit 61 includes a transmitting circuit and a receiving circuit that transmit and receive data to and from an external storage medium EM such as a USB memory or an SD card.

The processor 62 is configured using, for example, a CPU, a DSP, or an FPGA, and controls the operations of each section. The processor 62 cooperates with the memory 63 to perform various types of processing and control in an integrated manner. Specifically, the processor 62 references programs and data held in the memory 63 and executes the programs to realize the functions of each section.

The memory 63 includes, for example, a RAM as a work memory used when the processor 62 executes each process, and a ROM that stores programs and data that define the operations of the processor 62. Data or information generated or acquired by the processor 62 is temporarily stored in the RAM. A program that defines the operation of the processor 62 is written in the ROM.

The display unit 64 is configured using, for example, an LCD or an organic EL, and displays various screens for handing over the driver handover data between the plurality of vehicles C2A, . . . . For example, the display unit 64 displays a selection screen (not shown) on which a driver to whom the handover data is to be transferred can be selected (designated), a vehicle to which the handover data is to be transferred (that is, a transfer destination) can be selected (designated) A selection screen (not shown), etc. is displayed.

The input unit 65 is realized by, for example, a keyboard, a mouse, a touch panel, etc., and accepts administrator operations. The input unit 65 converts the received administrator operation into an electrical signal and outputs it to the processor 62. Note that the input section 65 may be a user interface configured integrally with the display section 64.

The user database DB7 stores (registers) personal information or user IDs of drivers who are targets of handover data for each driver. Note that the user database DB7 is not essential and may be omitted, or may be configured separately from the operating terminal P3.

If the user database DB7 is omitted, the administrator may identify the driver by personal information other than the user ID (e.g., driver's license ID, information about the driver (name, age, date of birth, etc.), The driver to whom the handover data is to be taken over may be designated (specified) by inputting various numbers, etc. that are assigned to the driver into the input unit 65.

The external storage medium EM is, for example, a USB memory, an SD card, or the like, and is a storage medium that can record inherited data. The external storage medium EM records (writes out) the handover data transmitted from the operating terminal P3 for each driver, and reads out the recorded handover data to the operating terminal P3.

Next, with reference to FIG. 36, the personal information/personal characteristic data table TB7 recorded by the driving characteristic improvement server S4 will be explained. FIG. 36 is a diagram illustrating an example of the personal information/personal characteristics data table TB7.

The personal information/personal characteristic data table TB7 records and manages a vehicle ID and personal information and personal characteristic data acquired by the vehicle corresponding to the vehicle ID in association with a user ID. Note that the user ID may be a driver's license ID.

For example, the personal information/personal characteristics data table TB7 shown in FIG. ”, “○○△”, and “〇△△” are linked with the personal information and personal characteristic data acquired by the vehicle, and the user ID “BBB” is assigned the vehicle ID “△△△”. , the personal information and personal characteristic data acquired by the vehicle corresponding to the vehicle ID "△△△" are linked, and the user ID "CCC" is associated with the vehicle ID "XXXX" and the vehicle ID "XXXX". Personal information and personal characteristic data obtained from vehicles corresponding to `` are linked and recorded. Thereby, the personal information/personal characteristic data table TB7 can efficiently manage the personal information and personal characteristic data of the driver even when one driver drives a plurality of different vehicles.

Referring to FIG. 37, a first example of a handover procedure by the driving characteristic improvement support system 300 according to the third embodiment will be described. FIG. 37 is a sequence diagram illustrating a first example of a procedure for handing over data of a driver in the driving characteristic improvement support system 300 according to the third embodiment. The handover data handover procedure example 1 referred to here is a handover data handover procedure executed by each of the wireless terminal device P2, the vehicle C2A, . . . , and the driving characteristic improvement server S4.

In the following description, an example will be described in which the driver initial registration process (steps St101 to St111) shown in FIG. 5 has been completed in each of the vehicles C2A and C2B.

Furthermore, in the first example of the procedure for handing over the driver's personal information data and personal characteristic data shown in FIG. 37, an example will be described in which the driving characteristic improvement server S4 executes relearning (updating) of the artificial intelligence; however, the present invention is not limited to this. . Relearning (updating) of the artificial intelligence may be performed in each vehicle C2A, C2B. In such a case, each vehicle C2A, C2B executes relearning (update) of the artificial intelligence using the takeover data transmitted from the driving characteristic improvement server S4.

The wireless terminal device P2 receives an input operation by the driver or a relative of the driver, generates a takeover data list TB9 (see FIG. 39) (St401), and transmits it to the vehicle C2A (St402). Although FIG. 37 shows an example in which the handover data list TB9 is transmitted to the vehicle C2A, the wireless terminal device P2 may transmit the same handover data list TB9 to the driving characteristic improvement server S4. Further, after being transmitted to the vehicle C2A, the handover data list TB9 may be further transmitted by the vehicle C2A to the driving characteristic improvement server S4, or after being transmitted to the driving characteristic improvement server S4, the handover data list TB9 may be transmitted to the driving characteristic improvement server S4. It may also be sent to vehicle C2A.

The driving characteristic improvement support system 300 executes the driver authentication process (Steps St301 to Step St312) shown in FIG. 14 between the vehicle C2A and the driving characteristic improvement server S4 that can implement the functions of the driving characteristic server S1. .

After the driver authentication is completed, the driving characteristic improvement support system 300 performs the operations shown in FIGS. 30 and 31 between the vehicle C2A and the driving characteristic improvement server S4 that can implement the functions of the driving characteristic improvement server S3. The driving characteristic improvement process (steps St51 to St63) shown in FIG. Although not shown in the example shown in FIG. 37, the driving characteristic improvement process executes learning using the driver's personal information and personal characteristic data (handover data) from the previous driving as learning data. It may be executed using artificial intelligence "A'" obtained by

Furthermore, in the driving characteristic improvement support using artificial intelligence in the third embodiment, the vehicle C2A further performs driving characteristic improvement support using lifestyle information (for example, sleep information) included in the driver's personal information. good. For example, vehicle C2A uses artificial intelligence "A'" to acquire sleep information (e.g., bedtime, wake-up time, breathing rate, sleep quality, etc.), which is the driver's personal information, from wireless terminal device P2. perform an assessment of the driver's sleep. If the vehicle C2A determines that the driver is sleep deprived as a result of the evaluation, the vehicle C2A executes driving characteristic improvement support that is appropriate for the driver's physical condition by speeding up the execution timing of driving characteristic improvement support during driving. do.

When the vehicle C2A detects that the driver has finished driving, it improves driving characteristics by linking the user ID, vehicle ID, and new personal information and personal characteristic data of the driver acquired during the current driving. It is transmitted to server S4 (St403). Note that the data transmission timing may be executed periodically (for example, every 30 minutes, one hour, etc.), or may be executed at the timing of the end of driving as described above.

The driving characteristic improvement server S4 stores (registers) new personal information and personal characteristic data transmitted from the vehicle C2A in the personal information/personal characteristic database DB5 based on the user ID and vehicle ID (St404). In addition, the driving characteristics improvement server S4 performs relearning (update) on the current artificial intelligence "A'" of the vehicle C2A using new personal information and personal characteristic data as learning data, and updates the current artificial intelligence "A'" of the vehicle C2A to '' is generated (St404). The driving characteristic improvement server S4 stores (registers) the vehicle ID of the vehicle C2A, the ID of the user who drives the vehicle C2A, and the generated artificial intelligence "A'' in the improvement effect learning model 53B. , is transmitted to vehicle C2A (St405).

The vehicle C2A records the artificial intelligence "A''" transmitted from the driving characteristic improvement server S4 in the memory 15B.

Here, a description will be given of driving characteristic improvement support processing when a driver changes from vehicle C2A to vehicle C2B due to purchasing a private car, using a shared car, or the like. Note that when the driving characteristic improvement support system 300 determines that the driver of vehicle C2A is riding as a passenger in vehicle C2B, such as when the driver rides together as an instructor during road practice with a provisional driving license, etc. , a driving characteristic improvement support process may be executed for the driver who is a fellow passenger.

The driving characteristic improvement support system 300 executes the driver authentication process (Steps St301 to Step St312) shown in FIG. 14 between the vehicle C2B and the driving characteristic improvement server S4 that can realize the functions of the driving characteristic server S1. .

The driving characteristic improvement server S4 refers to the takeover data list database DB6 based on the user ID (driver's biometric information, license information, etc.) and vehicle ID transmitted from the vehicle C2B. Based on the driver transfer data list TB9 (see FIG. 39) corresponding to this user ID, the driving characteristic improvement server S4 searches the personal information/personal characteristic database DB5 for information on drivers who can be transferred from the vehicle C2A to the vehicle C2B. Extract the inherited data.

The driving characteristic improvement server S4 performs relearning (update) on the base artificial intelligence "B" of the vehicle C2B using the extracted takeover data as learning data to generate the artificial intelligence "B'" (St406). . The driving characteristic improvement server S4 associates the vehicle ID of the vehicle C2A, the user ID driving the vehicle C2A, and the generated artificial intelligence "B'" and stores (registers) them in the improvement effect learning model 53B. , is transmitted to vehicle C2B (St407).

Vehicle C2B records the artificial intelligence "B'" transmitted from driving characteristic improvement server S4 in memory 15B, and starts supporting the driver's driving characteristic improvement.

As described above, the driving characteristic improvement support system 300 according to the third embodiment can transfer the driver's handover obtained from the vehicle C2A that the driver last drove, even when the driver drives a plurality of different vehicles. Based on the artificial intelligence "B'" generated by learning using data, vehicle C2B can also perform driving characteristic improvement support similar to or similar to vehicle C2A. In addition, if relearning (updating) of artificial intelligence is possible in each vehicle C2A and C2B, the driving characteristic improvement support system 300 transfers the driver handover data acquired in vehicle C2A to the latest vehicle C2B. As a result, driving characteristic improvement support similar to or similar to that of vehicle C2A can be performed in vehicle C2B as well.

The driving characteristic improvement support system 300 also extracts and processes transfer data based on a transfer data list in which transfer data (personal information and personal characteristic data) desired to be transferred between multiple vehicles with different drivers is selected. Execute. Therefore, the driving characteristic improvement support system 300 protects the driver's personal information by preventing the transfer (common) of personal information and personal characteristic data that the driver does not desire, and also allows the driver to drive in a different vehicle in a way that is more suitable for the driver. Characteristic improvement support can be realized.

Referring to FIG. 38, a second example of the handover procedure by the driving characteristic improvement support system 300 according to the third embodiment will be described. FIG. 38 is a sequence diagram illustrating a second example of the handover procedure for driver handover data of the driving characteristic improvement support system 300 according to the third embodiment. The second example of the handover data handover procedure referred to herein is a handover data handover procedure executed by the administrator's operation and executed by each of the operating terminal P3, the vehicle C2A, . . . , and the driving characteristic improvement server S4.

In the following description, an example will be described in which the driver initial registration process (steps St101 to St111) shown in FIG. 5 has been completed in each of the vehicles C2A and C2B.

In the following description, an example will be described in which the generation process of the takeover data list TB9 shown in FIG. 37 (step St401) and the registration process of the takeover data list TB9 to the driving characteristic improvement server S4 (step St402) have been completed. explain.

The operation terminal P3 receives an operation by the administrator to start handing over the driver's handover data between the vehicle C2A and the vehicle C2B (St501). The operating terminal P3 generates a control command requesting the transmission of takeover data (personal information and personal characteristic data) and transmits it to the vehicle C2A (St502).

Based on the transmitted control command, the vehicle C2A refers to the takeover data list TB9 transmitted in advance from the wireless terminal device P2 and recorded in the memory 15B (St503). The vehicle C2A extracts the handover data based on the handover data list TB9 and transmits it to the operation terminal P3 (St504).

Operation terminal P3 acquires the handover data transmitted from vehicle C2A. The operation terminal P3 writes the acquired takeover data to the external storage medium EM (eg, USB memory, SD card, etc., see FIG. 39) based on the administrator's operation (St505).

The operating terminal P3 accepts an administrator operation to relearn (update) the base artificial intelligence "B" of the vehicle C2B to an artificial intelligence "B'" capable of supporting the driver's driving improvement (St506). The operating terminal P3 reads the handover data of the driver who drives the vehicle C2B from the external storage medium EM (St507). The operation terminal P3 generates a control command requesting relearning (update) of the base artificial intelligence "B" of the vehicle C2B, and updates the generated control command, the driver's user ID, and the driver's takeover data. are associated with each other and transmitted to vehicle C2B (St508).

Based on the control command transmitted from the operation terminal P3, the vehicle C2B generates a control command requesting relearning (update) of the base artificial intelligence "B" of the vehicle C2B, and uses the acquired user ID of the driver. and the driver's handover data are associated with each other and transmitted to the driving characteristic improvement server S4 (St509).

Based on the control command sent from the vehicle C2B, the driving characteristics improvement server S4 performs relearning (update) on the base artificial intelligence "B" of the vehicle C2B using the acquired driver takeover data as learning data. Then, artificial intelligence "B'" is generated (St510). The driving characteristic improvement server S4 transmits the generated artificial intelligence "B'" to the vehicle C2B (St511). Note that the driving characteristic improvement server S4 may store (register) the generated artificial intelligence "B'" in association with the user ID in the improvement effect learning model 53B.

The vehicle C2B acquires the artificial intelligence "B'" sent from the driving characteristics improvement server S4, records it in the memory 15B (St513), and generates a notification of completion of relearning (update) to the artificial intelligence "B'". and transmits it to the operating terminal P3 (St513).

As described above, the driving characteristic improvement support system 300 according to the third embodiment executes the same driving characteristic improvement support for vehicle C2B as for vehicle C2A by taking over the data taken over by the administrator using external storage medium EM. can.

As described above, the driving characteristic improvement support system 300 according to the third embodiment uses the external storage medium EM to select the vehicle C2A that the driver last drove, even when the driver drives a plurality of different vehicles. The acquired driver handover data can be taken over to the vehicle C2B.

The driving characteristic improvement support system 300 also provides a transfer data list in which transfer data (personal information and personal characteristic data) desired to be transferred between multiple vehicles with different drivers is selected based on instructions (operations) by the administrator. Based on this, extraction of the transfer data and transfer processing are executed. Therefore, the driving characteristic improvement support system 300 protects the driver's personal information by preventing the transfer (common) of personal information and personal characteristic data that the driver does not desire, and also allows the driver to drive in a different vehicle in a way that is more suitable for the driver. Characteristic improvement support can be realized.

Referring to FIG. 39, corresponding to the handover procedure example 1 shown in FIG. 37, the handover data handover example 1 executed via the driving characteristic improvement server S4, and the handover procedure example 2 shown in FIG. 38, A second example of handover data executed via external storage medium EM will be described. FIG. 39 is a diagram illustrating handover examples 1 and 2 of driver handover data.

The transfer data list TB8 includes each personal information and personal characteristic data acquired by the vehicle C2A during the current driving, and each of these personal information and personal characteristic data that can be transferred to another vehicle (here, the vehicle C2B). This is a table that associates information on whether or not the information exists.

The transfer data list TB9 associates each personal information and personal characteristic data acquired by the vehicle C2A during driving with information as to whether each of these personal information and personal characteristic data can be transferred to the vehicle C2B. It is a table.

The personal information/personal characteristic data table TB10 shows the driver's personal information/personal characteristic data handed over to the vehicle C2A by the driving characteristic improvement server S4.

First, a first example of handing over data will be described.

The vehicle C2A stores the driver's personal information "AA" acquired from the wireless terminal device P2 between the time when the driver starts driving and the time when the driver ends driving, and the personal characteristic data "AAAA", "BBBB", " ``CCCC'', ``DDDD'', and ``EEEE''. Based on the transfer data list recorded in the memory 15B, the vehicle C2A selects the personal information "AA" that can be transferred from the transfer data list TB8 to the driving characteristic improvement server S4, and the personal characteristic data "AAAA", "BBBB", " EEEE" and transmitted to the driving characteristic improvement server S4.

The driving characteristics improvement server S4 extracts personal information "AA" that can be transferred from the vehicle C2A to the vehicle C2B, and personal characteristic data "AAAA", "EEEE", and "XXXX" from the transfer data list TB9, and Send to C2B.

The vehicle C2B uses the personal information "AA" sent from the driving characteristic improvement server S4 and the personal characteristic data "AAAA", "EEEE", and "XXXX" as learning data to relearn the base artificial intelligence "B" ( update) and generates artificial intelligence "B'". Vehicle C2B uses the generated artificial intelligence "B'" to support the improvement of the driver's driving characteristics.

In addition, in FIG. 39, in order to make the explanation easier to understand, the handover data (personal information (or personal characteristic data) will be specifically explained, but it goes without saying that generation of the transfer data lists TB8, TB9 or the personal information/personal characteristic data table TB10 is not essential and may be omitted.

Further, in FIG. 39, an example has been described in which the vehicle C2A and the driving characteristic improvement server S4 each have different takeover data lists. In such a case, the vehicle C2A extracts the takeover data based on the takeover data list transmitted in advance from the wireless terminal device P2 and recorded in the memory 15B, and sends it to the driving characteristic improvement server S4. Further, the driving characteristic improvement server S4 extracts the takeover data to be taken over to the vehicle C2B based on a takeover data list different from the takeover data list possessed by the vehicle C2A.

Next, a second example of handing over data will be described.

The vehicle C2A stores the driver's personal information "AA" acquired from the wireless terminal device P2 between the time when the driver starts driving and the time when the driver ends driving, and the personal characteristic data "AAAA", "BBBB", " ``CCCC'', ``DDDD'', and ``EEEE''. Based on the control command transmitted from the operation terminal P3, the vehicle C2A selects personal information "AA" that can be transferred to the vehicle C2B from the transfer data list TB8, and personal characteristic data "AAAA", "BBBB", and "EEEE". Each is extracted and transmitted to the operating terminal P3.

The operating terminal P3 writes personal information "AA" that can be taken over to the vehicle C2B and personal characteristic data "AAAA", "BBBB", and "EEEE" into the external storage medium EM based on the administrator's operation. In addition, the operation terminal P3 reads the personal information "AA" written to the external storage medium EM and the personal characteristic data "AAAA", "BBBB", "EEEE", respectively, based on the administrator's operation, Send to vehicle C2B.

Vehicle C2B acquires personal information "AA" and personal characteristic data "AAAA", "EEEE", and "XXXX" transmitted from operation terminal P3. Vehicle C2B receives a control command requesting relearning (update) of base artificial intelligence "B", personal information "AA" used for relearning base artificial intelligence "B", and personal characteristic data "AAAA", " BBBB" and "EEEE" are transmitted to the driving characteristic improvement server S4.

The driving characteristic improvement server S4 is based on the control command sent from the vehicle C2B, and is based on artificial intelligence that uses the personal information "AA" and the personal characteristic data "AAAA", "BBBB", and "EEEE" as learning data. Executes relearning (update) of "B" and generates artificial intelligence "B'". The driving characteristic improvement server S4 transmits the artificial intelligence "B'" generated by relearning to the vehicle C2B.

However, each of the vehicles C2A and C2B may differ in the number, arrangement, etc. of speakers and warning indicator lights. In such a case, vehicle C2B, which is the destination of the handover data, is equipped with equipment located at the same location as vehicle C2A, or with the same method (for example, various lighting, lighting control methods for pillars, etc., audio output method). It is difficult to implement driving characteristic improvement support.

The base artificial intelligence stored in each vehicle in Embodiment 3 performs driving characteristic improvement support inherited from other vehicles based on the number and arrangement of speakers 25, warning indicator lights 26, etc. installed in the own vehicle. By changing the execution method, device (speaker, warning indicator light, etc.) or the location of the device, it is possible to execute driving characteristic improvement support that is expected to have the same or similar effects as driving characteristic improvement support in other vehicles. Hereinafter, with reference to FIG. 40 and FIG. 41, an example of changing the driving characteristic improvement support operation (method or device) between vehicles C2A and C2B will be specifically described.

With reference to FIG. 40, modification example 1 of the driving characteristic improvement support operation will be described. FIG. 40 is a diagram illustrating a first modification of the driving characteristic improvement support operation between vehicles C2A and C2B.

In the example shown in FIG. 40, for example, the vehicle C2A is not provided with warning indicator lights 26A and 26B on each of the pair of front pillars (A pillars), and a warning indicator light 26C (for example, an LED) is not provided on the right side mirror SM2. etc.) are provided. Further, for example, in the vehicle C2B, the right side mirror SM2 is not provided with the warning indicator light 26C, but the pair of front pillars (A pillars) are each provided with warning indicator lights 26A and 26B.

For example, the vehicle C2A uses artificial intelligence learned using improvement support data (personal characteristic data) to change the warning indicator light 26C (e.g., LED, etc.) provided on the right side mirror SM2 to a predetermined color (e.g., , yellow, orange, red, etc.). As a result, vehicle C2A provides driving characteristic improvement support to encourage the driver to visually check (safety confirmation behavior) whether there are objects approaching from the rear right side of the own vehicle (e.g., pedestrians, other vehicles, two-wheeled vehicles, etc.). Execute.

In such a case, the artificial intelligence "B'" learned by the base artificial intelligence "B" of the vehicle C2B using the takeover data acquired by the vehicle C2A as the learning data is the warning indicator light 26C of the right side mirror SM2. The driving characteristic improvement support that is performed using the A-pillar is changed to be performed using the warning indicator light 26B, which is the front right pillar (A-pillar).

Vehicle C2B uses artificial intelligence "B'" to control the warning indicator light 26B, which is the front right pillar (A pillar), to turn on and blink in a predetermined color (for example, yellow, orange, red, etc.). . As a result, vehicle C2B provides driving characteristic improvement support to encourage the driver to visually check (safety confirmation behavior) whether there are objects approaching from the rear right side of the own vehicle (for example, pedestrians, other vehicles, two-wheeled vehicles, etc.). Execute.

As described above, by using the base artificial intelligence corresponding to each vehicle, the driving characteristic improvement support system 300 in the third embodiment uses the same device (in the above example, the warning indicator light 26C of the right side mirror SM2) between vehicles. ), it is possible to change the method, device, or location of the device to achieve the same driving characteristic improvement support for each vehicle. Thereby, the driving characteristic improvement support system 300 can support the driver so that the same or similar driving characteristic improvement support effect can be obtained even in different vehicles.

Next, with reference to FIG. 41, a second modification of the driving characteristic improvement support operation will be described. FIG. 41 is a diagram illustrating a second modification of the driving characteristic improvement support operation between vehicles C2A and C2B.

In the example shown in FIG. 41, for example, the vehicle C2A has five speakers 25A to 25E disposed inside each door and at the rear of the vehicle. Further, for example, in the vehicle C2B, four speakers 25F, 25G, 25H, and 25I are arranged in the vehicle, each corresponding to the position of each door, and near the ceiling.

The vehicle C2A uses, for example, artificial intelligence learned using the improvement support data (personal characteristic data) to output audio from the speaker 25E provided at the rear of the vehicle. As a result, the vehicle C2A performs driving characteristic improvement support for prompting the driver to check safety behind the vehicle.

In such a case, the artificial intelligence "B'" learned by the base artificial intelligence "B" of the vehicle C2B using the takeover data acquired by the vehicle C2A as learning data is the driving characteristic performed using the speaker 25E. Improvement support is changed to be performed by two speakers 25H and 25I placed at the rear of the vehicle.

Vehicle C2B uses artificial intelligence "B'" to output audio from speakers 25H and 25I at the rear of the vehicle. As a result, the vehicle C2A performs driving characteristic improvement support for prompting the driver to check safety behind the vehicle.

As described above, by using the base artificial intelligence corresponding to each vehicle, the driving characteristic improvement support system 300 according to the third embodiment can solve the problem even when there are no devices (in the above example, the speaker 25E) in the same arrangement among the vehicles. However, the method, device, or location of the device can be changed to achieve the same driving characteristic improvement support for each vehicle. Thereby, the driving characteristic improvement support system 300 can support the driver so that the same or similar driving characteristic improvement support effect can be obtained even in different vehicles.

Note that the driving characteristic improvement support system 300 may change from driving characteristic improvement support using audio using the speaker 25 to driving characteristic improvement support using a warning indicator light 26 such as turning on or blinking a light. Further, the driving characteristic improvement support system 300 may change the type of sound output from the speaker 25, the lighting control pattern of the warning indicator lamp 26, or the lighting color of the warning indicator lamp 26. .

The driving characteristics improvement server S4 also has a database (not shown) that records the number, arrangement, or control method (for example, audio pattern, lighting color, lighting pattern, etc.) of the speakers 25 and warning indicator lights 26 for each vehicle. You can leave it there. In such a case, the driving characteristic improvement server S4 collects information on the number, arrangement, or control method of the speakers 25 and warning indicator lights 26 of the vehicle C2A from which the handover data has been acquired (collected), and the vehicle to which the handover data is to be taken over. The information on the number, arrangement, or control method of the C2B speakers 25 and warning indicator lights 26 is compared, and a method or device that makes each driving characteristic improvement support possible is assigned. The driving characteristic improvement server S4 may perform learning on the base artificial intelligence "B" of the vehicle C2B using the assignment result, the driver's personal information, and the driving characteristic data as learning data.

Next, an example of generation of a takeover data list executed by the wireless terminal device P2 will be described with reference to each of FIGS. 42 to 45. FIG. 42 is a screen transition diagram illustrating an example of deletion of inherited data. Note that each of the transfer data setting screens SC11, SC12, SC13, and SC14 shown in FIG. 42 is an example, and it goes without saying that the present invention is not limited thereto.

The takeover data list TB9 (see FIG. 39) is generated by the wireless terminal device P2 that can accept operations by the driver or a relative of the driver, and is transmitted to the driving characteristic improvement server S4 and managed. In the following description, in order to make the description easier to understand, an example will be described in which the driver performs a handover data creation operation.

The wireless terminal device P2 generates a takeover data setting screen SC11 that can accept driver operations, and displays it on a monitor (not shown).

The transfer data setting screen SC11 includes a transfer data major classification item SL111 "Lifestyle", a major classification item SL112 "Car", and a search bar SR. Major classification item SL111 "Lifestyle" indicates a group in which personal information related to the driver's daily life information is grouped. The major classification item SL112 "car" indicates a group in which driving characteristic data related to driver's driving characteristic data is grouped.

Further, the search bar SR searches the driver's personal information or personal characteristic data for personal information or personal characteristic data including a search condition (for example, a word) input by the driver's operation. The wireless terminal device P2 generates a search result screen including the search results and displays it on the monitor. Note that the search process using the search bar SR will be explained in detail with reference to FIG. 44, which will be described later.

When the wireless terminal device P2 receives the driver's selection (press) operation of the major classification item SL112 "Car" on the handover data setting screen SC11 shown in FIG. A handover data setting screen SC12 including the classification item SL121 "Vehicle inspection", the intermediate classification item SL122 "Driving operation", and the intermediate classification item SL123 "Safety confirmation" is generated and displayed on the monitor.

The transfer data setting screen SC12 includes each of the intermediate classification items SL121 to SL123 of transfer data and a search bar SR. Here, the intermediate classification item SL121 "vehicle inspection" indicates a group in which improvement support data (driving characteristic improvement support) regarding vehicle inspection is grouped. The intermediate classification item SL122 "driving operation" indicates a group in which improvement support data (driving characteristic improvement support) regarding driving operations by the driver are grouped. The intermediate classification item SL123 "safety confirmation" indicates a group in which improvement support data (driving characteristic improvement support) regarding safety confirmation by the driver is grouped. Note that the intermediate classification item SL123 "safety confirmation" may include improvement support data (driving characteristic improvement support) regarding safety confirmation when the driver is a passenger.

When the wireless terminal device P2 receives a selection (press) operation of the middle category item SL123 "Safety confirmation" by the driver on the handover data setting screen SC12 shown in FIG. A handover data setting screen SC13 is generated and displayed on the monitor, including each of the minor classification item SL131 "Before getting into the vehicle", the minor classification item SL132 "Before getting out of the vehicle", etc.

The handover data setting screen SC13 includes each of the small classification items SL131, . . . of the handover data, and a search bar SR. Here, the subcategory item SL131 "before getting into the vehicle" indicates improvement support data (driving characteristics improvement support) for safety confirmation behavior in the driving scene "before getting into the vehicle." Minor category item SL132 "Before getting off the vehicle" indicates improvement support data (driving characteristic improvement support) for safety confirmation behavior in the driving scene "Before getting off the vehicle".

When the wireless terminal device P2 receives the selection (press) operation of the minor category item SL132 "Before getting off the vehicle" by the driver on the handover data setting screen SC13 shown in FIG. 42, the wireless terminal device P2 selects the driving scene "Before getting off the vehicle" A transfer data setting screen SC14 including operation buttons SL141 "Take out", operation buttons SL142 "Share", and operation buttons SL143 "Delete" regarding safety confirmation behavior improvement support data (driving characteristics improvement support) is generated and monitored. to be displayed.

The handover data setting screen SC14 includes each of handover data operation buttons SL141 to SL143.

When the driver selects the operation button SL143 "Delete" on the handover data setting screen SC14 shown in FIG. Set it so that it cannot be shared with other vehicles (in other words, cannot be taken over). When the operation button SL143 "Delete" is selected, the wireless terminal device P2 selects the personal information or personal characteristic data ( Here, the data for improving safety confirmation behavior during the driving scene "before getting out of the vehicle" is deleted.

Further, the operation button SL141 "Take out" is a button for writing improvement support data for safety confirmation behavior in the driving scene "before getting off the vehicle" to the external storage medium EM in order to take over from the vehicle C2A to the vehicle C2B. When the driver selects the operation button SL141 "Take out", the wireless terminal device P2 transmits the improvement support data for safety confirmation behavior in the driving scene "before getting off the vehicle" to the operation terminal P3, and stores it in the external storage medium EM. Have them write it out.

The operation button SL142 "Share" is a button for setting the improvement support data for safety confirmation behavior in the driving scene "before getting off the vehicle" to be shareable (that is, transferable) to other vehicles. When the operation button SL142 "Share" is selected, the wireless terminal device P2 generates a transfer data list in which transferable information is added to the personal information or personal characteristic data indicated by the corresponding subcategory item. Personal information or personal characteristic data with transferable information is used as learning data for the base artificial intelligence of other vehicles.

FIG. 43 is a screen transition diagram illustrating an example of setting the transfer data. Note that each of the transfer data setting screens SC21, SC22, SC23, SC24, and SC25 shown in FIG. 43 is an example, and it goes without saying that the present invention is not limited thereto.

The wireless terminal device P2 generates a takeover data setting screen SC21 that can accept driver operations, and displays it on a monitor (not shown).

The transfer data setting screen SC21 includes a transfer data major classification item SL211 "Lifestyle", a major classification item SL212 "Car", and a search bar SR. Major classification item SL211 "Lifestyle" indicates a group in which personal information related to driver's daily life information is grouped. The major classification item SL212 “car” indicates a group in which driving characteristic data related to the driving characteristic data of the driver is grouped.

In the handover data setting screen SC21 shown in FIG. 43, when the wireless terminal device P2 receives the driver's selection (pressing) operation of the middle category display button SLT21 for major category item SL212 "Car", the wireless terminal device P2 selects (presses) the major category item SL212 "Car". A transfer data setting screen SC22 including the intermediate classification item SL221 "Vehicle inspection", the intermediate classification item SL222 "Driving operation", and the intermediate classification item SL223 "Safety confirmation" linked to "" is generated and displayed on the monitor.

The transfer data setting screen SC22 includes each of the intermediate classification items SL221 to SL223 of transfer data and a search bar SR. Here, the intermediate classification item SL221 "vehicle inspection" indicates a group in which improvement support data (driving characteristic improvement support) regarding vehicle inspection is grouped. The intermediate classification item SL222 "driving operation" indicates a group in which improvement support data (driving characteristic improvement support) regarding driving operations by the driver are grouped. The intermediate classification item SL223 "safety confirmation" indicates a group in which improvement support data (driving characteristic improvement support) regarding safety confirmation by the driver is grouped. Note that the intermediate classification item SL223 "safety confirmation" may include improvement support data (driving characteristic improvement support) regarding safety confirmation when the driver is a passenger.

On the handover data setting screen SC22 shown in FIG. 43, the wireless terminal device P2 allows the driver to select (press) the selection area SLT221 to select all minor categories included in the medium category item SL223 "Safety confirmation" at once. If accepted, a transfer data setting screen SC23 including batch operation buttons SL231 "Take out all", batch operation buttons SL232 "Share all", and batch operation buttons SL233 "Delete all" is generated and displayed on the monitor.

The handover data setting screen SC23 includes batch operation buttons SL231 to SL233. Here, the batch operation button SL231 "Bring everything out" is used to improve driving characteristics by collecting personal information or personal characteristic data corresponding to each of the minor classification items SL241, SL242, ... grouped into the medium classification item SL223 "Safety confirmation". This is a button for transmitting to the server S4 and executing management by the driving characteristic improvement server S4.

When the driver selects the collective operation button SL231 "Take everything out", the wireless terminal device P2 corresponds to all the minor classification items SL241, SL242, ... grouped in the medium classification item SL223 "Safety confirmation". Personal information or personal characteristic data is transmitted to the operating terminal P3 and written to the external storage medium EM.

When the driver selects the collective operation button SL232 "Share all", the wireless terminal device P2 corresponds to all the minor categories SL241, SL242, etc. grouped in the middle category SL223 "Safety confirmation". Personal information or personal characteristic data to be shared with other vehicles (that is, transferable) is set to be shared with other vehicles, and a transferable data list is generated that includes transferable information.

When the wireless terminal device P2 receives a selection (press) operation of the batch operation button SL233 "Delete all" by the driver, the wireless terminal device P2 deletes all the minor categories SL241, SL242, Set the personal information or personal characteristic data corresponding to each of the following to not be shared with other vehicles (in other words, not transferable), and personal information or personal characteristic data grouped in the medium classification item SL223 "Safety confirmation" from the transfer data list. Delete.

On the handover data setting screen SC22 shown in FIG. 43, the wireless terminal device P2 accepts an operation by the driver to select (press) a selection area SLT222 that displays all minor categories included in the medium category item SL223 "Safety confirmation". In this case, a takeover data setting screen SC23 including each of all the minor classification items SL241, SL242, . . . included in the medium classification item SL223 "Safety confirmation" is generated and displayed on the monitor.

The takeover data setting screen SC24 includes subcategory items SL241, . . . and a search bar SR.

When the wireless terminal device P2 receives the selection (press) operation of the minor category item SL242 "Before getting off the vehicle" by the driver on the handover data setting screen SC24 shown in FIG. 43, the wireless terminal device P2 selects the driving scene "Before getting off the vehicle". A transfer data setting screen SC15 including operation buttons SL251 "Take out", operation buttons SL252 "Share", and operation buttons SL253 "Delete" regarding safety confirmation behavior improvement support data (driving characteristics improvement support) is generated and monitored. to be displayed.

The handover data setting screen SC25 includes each of handover data operation buttons SL251 to SL253.

In the handover data setting screen SC25 shown in FIG. 43, when the wireless terminal device P2 receives a selection (press) operation of the operation button SL251 "Take out" by the driver, the wireless terminal device P2 selects the safety confirmation behavior in the driving scene "before getting off the vehicle". The improvement support data is transmitted to the operation terminal P3 and written to the external storage medium EM. Note that the operation button SL252 is the same as the operation button SL142 shown in FIG. 42, so a description thereof will be omitted. Further, since the operation button SL253 is similar to the operation button SL143 shown in FIG. 42, the explanation will be omitted.

FIG. 44 is a screen transition diagram illustrating an example of searching for inherited data. Note that each of the transfer data setting screens SC21, SC22, SC31, and SC32 shown in FIG. 44 is an example, and it goes without saying that the present invention is not limited thereto.

The wireless terminal device P2 accepts an input operation for the search condition "brake" in the search bar SR21 of the handover data setting screen SC21 shown in FIG. The wireless terminal device P2 searches all the personal information and personal characteristic data for personal information or personal characteristic data that satisfies the search condition "brake", generates a transfer data setting screen SC31 including the search results, and displays it on the monitor. do.

The transfer data setting screen SC31 includes small category items SL313 and SL315 that satisfy the search condition "brake", medium category items SL312 and SL314 in which small category items SL313 and SL315 are grouped, and medium category items SL312 and SL314 are grouped together. Major classification item SL311. Note that the takeover data setting screen SC31 may be generated including only the subcategory items SL313 and SL315 that satisfy the search condition "brake".

The wireless terminal device P2 accepts an input operation for the search condition "brake safety confirmation" in the search bar SR31 of the handover data setting screen SC31 shown in FIG. 44. The wireless terminal device P2 searches all the personal information and personal characteristic data for personal information or personal characteristic data that satisfies the search condition "brake safety confirmation", generates a transfer data setting screen SC32 containing the search results, and displays the screen on the monitor. to be displayed.

The transfer data setting screen SC32 displays a medium category item SL322 that satisfies the search condition "brake safety confirmation," a major category item SL321 in which the medium category item SL322 is grouped, and a minor category item SL323 grouped in the medium category item SL322. include. Note that the handover data setting screen SC32 may be generated including only the medium classification item SL322 that satisfies the search condition "brake safety confirmation".

Note that the search bar SR may accept input of search conditions via an input interface (e.g., touch panel, keyboard, etc.) provided in or connected to the wireless terminal device P2, or The input of search conditions may be accepted by voice recognition of the utterances collected by a microphone (not shown) provided in P2.

FIG. 45 is a screen transition diagram illustrating an example of editing inherited data. It should be noted that the succession data setting screens SC41 and SC42 and the system diagram of personal information/personal characteristic data shown in FIG. 45 are merely examples, and it goes without saying that the present invention is not limited thereto.

The wireless terminal device P2 generates a takeover data setting screen SC21 that can accept driver operations, and displays it on a monitor (not shown).

The transfer data setting screen SC41 includes a transfer data major category item SL411 "Lifestyle", a major category item SL412 "Car", a favorite item SL413, and a search bar SR. Major classification item SL411 "Lifestyle" indicates a group in which personal information related to the driver's daily life information is grouped. Major classification item SL412 “Car” indicates a group in which driving characteristic data related to driver's driving characteristic data is grouped. Favorite item SL413 indicates one or more pieces of personal information or personal characteristic data grouped based on driver operations.

When the wireless terminal device P2 receives the selection (pressing) operation of the favorite button SLT41 by the driver on the handover data setting screen SC41 shown in FIG. Generate and display on the monitor.

The handover data setting screen SC42 includes a medium classification item SL421 "Sleep" grouped by the driver, a grouping item SL422 "Confirmation when getting on and off", a grouping item SL423 "Confirmation while driving", and a search bar SR. .

When the wireless terminal device P2 receives the driver's selection (press) operation of the intermediate classification item SL421 "Sleep" on the handover data setting screen SC41 shown in FIG. A takeover data setting screen (not shown) including LST1 is generated and displayed on the monitor. In the example shown in FIG. 45, the list LST1 includes a medium classification item SL421 and a plurality of small classification items grouped into the medium classification item SL421: "bedtime", "wake-up time", "breathing rate", and "sleep quality". and each of the following.

When the wireless terminal device P2 receives a selection (press) operation of the grouping item SL422 "Confirmation when getting on and off" by the driver on the handover data setting screen SC41 shown in FIG. A transfer data setting screen (not shown) including various items (list LST2) grouped under "Confirmation when getting on and off" is generated and displayed on the monitor. In the example shown in FIG. 45, list LST2 includes a plurality of subcategories: "Before getting into the vehicle," "Before getting off the vehicle," and "Before the passenger gets off the vehicle."

When the wireless terminal device P2 receives a selection (press) operation of the grouping item SL423 "Confirm while driving" by the driver on the handover data setting screen SC41 shown in FIG. A handover data setting screen (not shown) including various items (list LST3) grouped under "Confirmation during operation" is generated and displayed on the monitor. In the example shown in FIG. 45, list LST3 includes multiple subcategories: "Before starting the vehicle," "Before applying the brakes," "Before changing lanes," "While driving straight," "Turning right or left." ``before moving the vehicle'' and ``before reversing the vehicle.''

Furthermore, the wireless terminal device P2 renames and rearranges various items (major category items, medium category items, and minor category items, respectively) included in each list LST1 to LST3 based on the driver's operation.

For example, when the wireless terminal device P2 receives an editing operation for a grouping item from the driver, the wireless terminal device P2 generates or changes the name of the grouping item "confirmation while driving," and selects and rearranges various items grouped into the grouping item. , delete operations, etc. are further accepted. As a result, the wireless terminal device P2 selects the grouping item SL422 "Confirmation when getting on and off" that includes each of the multiple subcategories "Before getting into the vehicle", "Before getting off the vehicle", and "Before the passenger gets off the vehicle" Execute the generation.

For example, the wireless terminal device P2 rearranges the minor category item "before turning right or left" after the minor category item "before starting the vehicle" based on the driver's operation. As a result, the wireless terminal device P2 changes the order of the subcategory items displayed on the subsequent handover data setting screen to "Before starting the vehicle," "Before turning left or right," "Before applying the brakes," etc. be able to.

As described above, the driving characteristic improvement support system 300 according to Embodiment 3 is configured to provide the driving characteristic improvement server S4 or the operation terminal that can cooperate with at least the vehicle C2A (an example of a first vehicle) and the vehicle C2B (an example of a second vehicle). P3 (an example of a computer) is an executable control method, which is acquired by the vehicle C2A, is used to support improvement of the driving characteristics of the driver driving the vehicle C2A, and inputs personal characteristic data corresponding to the driver. If a predetermined condition is satisfied, the personal characteristic data corresponding to the driver is output to be made available to the vehicle C2B.

Thereby, the driving characteristic improvement support system 300 according to the third embodiment receives input of the driver's personal information and personal characteristic data from the external storage medium EM or the vehicle C2A before changing, and when the driver changes to a different vehicle. Furthermore, the driver's personal information and personal characteristic data collected (obtained) by the vehicle C2A before the transfer can be transmitted to the vehicle C2B after the transfer. Therefore, the driving characteristic improvement support system 300 protects the driver's personal information by preventing the handover (common) of personal information and personal characteristic data that the driver does not desire, and also improves driving characteristics that are more suitable for drivers in different vehicles. Characteristic improvement support can be realized.

Further, as described above, the driving characteristic improvement server S4 or the operating terminal P3 of the driving characteristic improvement support system 300 according to the third embodiment is configured from at least one computer. Thereby, the driving characteristic improvement support system 300 according to the third embodiment can manage the driver's driving characteristic data collected in each of the different vehicles C2A and C2B using a computer.

Further, as described above, the predetermined condition in the driving characteristic improvement support system 300 according to the third embodiment is that the driving characteristic improvement server S4 or the operation terminal P3 receives a predetermined instruction (specifically, the driver changes vehicles). This is the case when a control command is received that detects a driver's handover data, an operation by an administrator to start handing over the driver's handover data, etc.). As a result, the driving characteristic improvement support system 300 according to the third embodiment can transfer the driving characteristic data of the driver between vehicles C2A and C2B when the driver changes vehicle C2A or at a timing desired by the administrator. It can be carried out. Therefore, the driving characteristic improvement support system 300 protects the driver's personal information by preventing the handover (common) of personal information and personal characteristic data that the driver does not desire, and also improves driving characteristics that are more suitable for drivers in different vehicles. Characteristic improvement support can be realized.

Further, as described above, the predetermined instruction in the driving characteristic improvement support system 300 according to the third embodiment includes information specifying (designating) the driver. As a result, the driving characteristic improvement support system 300 according to the third embodiment transfers only the personal information or personal characteristic data of the specified driver between vehicles, and therefore transfers personal information and personal characteristic data that the driver does not wish to transfer. (common) can be prevented.

Further, as described above, the driving characteristic improvement server S4 or the operating terminal P3 in the driving characteristic improvement support system 300 according to the third embodiment includes a transmitting circuit and a receiving circuit (that is, communication units 51 and 61), and the driving characteristic improvement server S4 or the operating terminal P3 in the driving characteristic improvement support system 300 according to the third embodiment is is used to support the improvement of the driving characteristics of the driver driving the vehicle C2A, and when the receiving circuit receives the personal characteristic data corresponding to the driver from the vehicle C2A and satisfies a predetermined condition, the personal characteristic data corresponding to the driver is This is a control method in which a transmission circuit transmits characteristic data to vehicle C2B, and the predetermined condition is when it is detected that a driver has boarded vehicle C2B. As a result, the driving characteristic improvement support system 300 according to the third embodiment transfers only the personal information or personal characteristic data of the specified driver between vehicles, and therefore transfers personal information and personal characteristic data that the driver does not wish to transfer. (common) can be prevented.

Further, as described above, the driving characteristic improvement support system 300 according to the third embodiment uses the driver as the first driver, and is capable of supporting the improvement of the driving characteristics of the first driver who drives the vehicle C2A. used to receive first personal characteristic data corresponding to the first driver, acquired by the vehicle C2A, used to support improvement of driving characteristics of a second driver driving the vehicle C2A, and corresponding to the second driver. If it is detected that the first driver got into the vehicle C2B, the first personal characteristic data corresponding to the first driver is sent to the vehicle C2B, and the second driver When it is detected that the person has boarded the vehicle C2B, second personal characteristic data corresponding to the second driver is transmitted to the second vehicle. As a result, the driving characteristic improvement support system 300 according to the third embodiment protects the driver's personal information by preventing the transfer (common) of personal information and personal characteristic data that the driver does not desire, and also It is possible to realize driving characteristic improvement support that is more suitable for the driver in the vehicle.

Furthermore, as described above, the personal characteristic data in the driving characteristic improvement support system 300 according to the third embodiment is the learning data of the driving support model used for the driving characteristic improvement support of the driver executed by the vehicle C2B. Thereby, the driving characteristic improvement support system 300 according to the third embodiment can realize driving characteristic improvement support more suitable for the driver even in the vehicle C2B different from the vehicle C2A.

Further, as described above, the personal characteristic data in the driving characteristic improvement support system 300 according to the third embodiment is at least one personal characteristic data specified by the driver among the plurality of personal characteristic data acquired by the vehicle C2A. . As a result, the driving characteristic improvement support system 300 according to the third embodiment can handle private cars used by a predetermined driver and vehicles that can be used by an unspecified number of drivers (rental cars, car sharing vehicles). Even if the driver's personal information and personal characteristic data are transferred between the In addition to protecting personal information, it is possible to provide driving characteristic improvement support that is more suitable for drivers in different vehicles.

Further, as described above, the driving characteristic improvement server S4 or the operation terminal P3 in the driving characteristic improvement support system 300 according to the third embodiment selects predetermined personal characteristic data from among the plurality of personal characteristic data acquired by the vehicle C2A. receives input. As a result, the driving characteristic improvement support system 300 according to the third embodiment protects the driver's personal information by preventing the transfer (common) of personal information and personal characteristic data that the driver does not desire, and also It is possible to realize driving characteristic improvement support that is more suitable for the driver in the vehicle.

Further, as described above, the driving characteristic improvement server S4 in the driving characteristic improvement support system 300 according to the third embodiment allows the specification of predetermined personal characteristic data to be sent to an external device (for example, the wireless terminal device P2 operated by the driver). receive from Thereby, the driving characteristic improvement support system 300 according to the third embodiment can inherit (common) only the personal information and personal characteristic data desired by the driver.

Further, as described above, the driving characteristic improvement server S4 in the driving characteristic improvement support system 300 according to the third embodiment can hold a plurality of pieces of personal characteristic data acquired by the vehicle C2A, and can hold a plurality of pieces of personal characteristic data acquired by the vehicle C2A. Among the data, predetermined personal characteristic data is output. Thereby, the driving characteristic improvement support system 300 according to the third embodiment can inherit (common) only the personal information and personal characteristic data desired by the driver.

Further, as described above, the driving characteristic improvement server S4 in the driving characteristic improvement support system 300 according to the third embodiment specifies predetermined personal characteristic data from the outside (for example, the wireless terminal device P2 operated by the driver). receive. Thereby, the driving characteristic improvement support system 300 according to the third embodiment can inherit (common) only the personal information and personal characteristic data desired by the driver.

Further, as described above, the driving characteristic improvement server S4 in the driving characteristic improvement support system 300 according to the third embodiment is capable of holding a plurality of pieces of personal characteristic data acquired by the first vehicle, and is capable of holding a plurality of pieces of personal characteristic data acquired by the first vehicle. At least one of the characteristic data can be deleted by an instruction from the outside (for example, the wireless terminal device P2 operated by the driver). Thereby, the driving characteristic improvement support system 300 according to the third embodiment can inherit (common) only the personal information and personal characteristic data desired by the driver.

Although various embodiments have been described above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that those skilled in the art can come up with various changes, modifications, substitutions, additions, deletions, and equivalents within the scope of the claims, and It is understood that it falls within the technical scope of the present disclosure. Further, each of the constituent elements in the various embodiments described above may be arbitrarily combined without departing from the spirit of the invention.

The present disclosure is useful as a control method that supports management of driver driving characteristic data collected in different vehicles and handing over of driver driving characteristic data between vehicles.

10, 12 Car navigation device 11, 11A Communication device 12A, 32, 42, 52, 62 Processor 12B, 15, 33, 43, 53, 63 Memory 12C, 22C, 64 Display section 12D, 22D, 65 Input section 13, 13A In-vehicle camera 14 Gyro sensor 16, 16A ECU
17 Operation unit 17A Accelerator pedal 17B Brake pedal 17C Turn lamp 17D Steering 18 Speed sensor 19, 19A External sensor/camera 20 GPS sensor 24 In-vehicle sensor 25, 25A, 25B, 25C, 25D Speaker 26, 26A, 26B Warning indicator light 31, 41, 51, 61 Communication unit 52A Support method generation unit 54 Database 100 Driving characteristic management system 300 Driving characteristic improvement support system C1, C1A, C2A, C2B Vehicle EM External storage medium NW, NWA, NWB Network P2 Wireless terminal device P3 Operation terminal S4 Driving characteristics improvement server TB3 Driving characteristics history table TB4 Driving characteristics improvement management tables TB8, TB9 Transferred data list TB10 Personal characteristics data table

Claims (13)

A control method executable by a computer capable of cooperating with at least a first vehicle and a second vehicle,
Receiving input of personal characteristic data corresponding to the driver, which is acquired by the first vehicle and used to support improvement of the driving characteristics of the driver driving the first vehicle;
If a predetermined condition is met, outputting the personal characteristic data corresponding to the driver to make it available to the second vehicle;
Control method. The control method according to claim 1,
The computer is composed of at least one computer.
Control method. The control method according to claim 1,
The predetermined condition is when the computer receives a predetermined instruction;
Control method. 4. The control method according to claim 3,
The predetermined instruction includes information specifying the driver,
Control method. The control method according to claim 1,
The computer includes a transmitting circuit and a receiving circuit,
the receiving circuit receives from the first vehicle the personal characteristic data corresponding to the driver, which is acquired by the first vehicle and is used to support improvement of driving characteristics of a driver driving the first vehicle;
If the predetermined condition is met, the transmission circuit transmits the personal characteristic data corresponding to the driver to the second vehicle, the control method comprising:
The predetermined condition is a case where it is detected that the driver has gotten into the second vehicle.
Control method. 6. The control method according to claim 5,
The driver is a first driver,
receiving first personal characteristic data corresponding to the first driver, which is acquired by the first vehicle and is used to support improvement of driving characteristics of the first driver driving the first vehicle;
receiving second personal characteristic data corresponding to the second driver, which is acquired by the first vehicle and used to support improvement of driving characteristics of a second driver driving the first vehicle;
If it is detected that the first driver got into the second vehicle, transmitting the first personal characteristic data corresponding to the first driver to the second vehicle;
If it is detected that the second driver got into the second vehicle, transmitting the second personal characteristic data corresponding to the second driver to the second vehicle;
Control method. The control method according to claim 1,
The personal characteristic data is learning data for a driving support model used to support improvement of the driving characteristics of the driver, which is executed by the second vehicle.
Control method. The control method according to claim 1,
The personal characteristic data is at least one personal characteristic data specified by the driver among a plurality of personal characteristic data acquired by the first vehicle.
Control method. The control method according to claim 1,
The computer receives input of predetermined personal characteristic data from among the plurality of personal characteristic data acquired by the first vehicle.
Control method. The control method according to claim 9,
The computer receives designation of the predetermined personal characteristic data from an outside. The control method according to claim 1,
The computer is capable of holding a plurality of personal characteristic data acquired by the first vehicle, and outputs predetermined personal characteristic data among the plurality of held personal characteristic data.
Control method. The control method according to claim 11,
the computer receives designation of the predetermined personal characteristic data from an external source;
Control method. The control method according to claim 1,
The computer is capable of holding a plurality of personal characteristic data acquired by the first vehicle, and is capable of deleting at least one of the plurality of held personal characteristic data by an instruction from an outside.
Control method.

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