JP2023079904A - Management method of driving characteristic improvement support data - Google Patents

Abstract

To more efficiently manage driving characteristic improvement support data based on driving characteristic data and feeling data.SOLUTION: A management method of driving characteristic improvement data links a plurality of pieces of driving scene information showing driving scenes of a vehicle, support data corresponding to the driving scene information to support improvement of safety confirmation behaviors of drivers, and driving characteristic data of the drivers for each driver ID to be registered, acquires the driver IDs of the drivers who drive the vehicle, the driving characteristic data of the drivers corresponding to the driving scene information, and feeling data of the drivers to support based on the support data, collates the driver ID of each of a plurality of drivers with the acquired driver IDs, generates new support data corresponding to the acquired driving scene information on the basis of the driving characteristic data and the feeling data, and updates the support data linked with the same driving scene information as the acquired driving scene information among a plurality of pieces of driving scene information to the generated new support data.SELECTED DRAWING: Figure 17

Description

The present disclosure relates to a method of managing driving characteristic improvement assistance data.

2. Description of the Related Art Conventionally, a vehicle alarm device and a driving assistance device are known that assist a driver in confirming safety while driving, driving operation, and the like.

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

For example, in Patent Document 2, based on the relationship between a predetermined road parameter of the road on which the vehicle travels and the steering angle, it is determined whether or not the driver's safety confirmation is required. A vehicle warning device is disclosed that warns a driver when it is determined that it has not been done. Further, Patent Document 3 discloses a driving assistance device that learns the driving proficiency level of the driver based on the history of driving operations of the driver and assists driving according to the driving assistance level based on the driving proficiency level. It is In addition, in Patent Document 4, the driver's state relative to the external environment is estimated from 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 assistance device that performs or prohibits driving assistance according to the driving skill and the driver's condition.

JP 2015-71319 A Japanese Patent Application Laid-Open No. 2007-233476 JP 2009-48307 A JP 2015-110417 A

However, in the above-described vehicle alarm device and driving assistance device, since driving assistance is determined based on the driving skill (operation) of the driver, further improvement can be made in terms of performing driving assistance more suitable for the driver. There was room for

The present disclosure has been devised in view of the conventional circumstances described above, and is a method for managing driving characteristic improvement support data and a driving characteristic improvement support method capable of more efficiently managing driving characteristic improvement support data based on driving characteristic data and emotion data. intended to provide

The present disclosure provides a method for managing driving characteristic improvement assistance data executed by one or more computers communicable with at least one vehicle, comprising a plurality of pieces of driving scene information indicating a driving scene of the vehicle; Support data corresponding to the driving scene information and supporting improvement of safety confirmation behavior of the driver who drives the vehicle and driving characteristic data of the driver in the driving scene information are provided to a plurality of the drivers. Each ID is linked and registered, the driving scene information and the support data are linked, respectively, transmitted to the vehicle, and the driver ID of the driver who drives the vehicle and the driving scene information are associated with each other. obtaining the driving characteristic data of the driver and the emotion data of the driver with respect to assistance based on the assistance data, and comparing the driver IDs of the plurality of drivers with the acquired driver IDs; and generating new support data corresponding to the acquired driving scene information based on the driving characteristic data linked to the verified driver ID and the acquired driving characteristic data and emotion data. Then, the support data linked to the same driving scene information as the acquired driving scene information among the plurality of driving scene information linked to the collated driver ID is added to the generated new To provide a management method of driving characteristic improvement support data, which updates the data to a more suitable support data.

Further, the present disclosure is a method for managing driving characteristic improvement support data executed by a vehicle, comprising a plurality of pieces of driving scene information indicating a driving scene of the vehicle, and driving the vehicle corresponding to the driving scene information. support data for assisting the improvement of the safety confirmation behavior of the driver and the driver ID of the driver are linked and stored, and the driving characteristic data of the driver in the driving scene information and the driving scene information are associated with each other; A sensor acquires the emotion data of the driver with respect to the assistance based on the assistance data, and the acquired driving characteristic data and the emotion data, and the driving scene information from which the driving characteristic data and the emotion data are acquired. , the driving scene information is linked with the driver ID and transmitted to an external device, new assistance data corresponding to the driving scene information transmitted from the external device is acquired, and the assistance linked to the driving scene information is acquired. A method for managing driving characteristic improvement assistance data is provided, which updates the data to the acquired new assistance data.

The present disclosure also provides a method for managing driving characteristic improvement support data executed by one or more computers mounted on a vehicle, comprising a plurality of pieces of driving scene information indicating a driving scene of the vehicle and corresponding to the driving scene information. support data for assisting improvement of the safety confirmation behavior of the driver who drives the vehicle and the driver ID of the driver are linked and stored, and the driving characteristic data of the driver in the driving situation information and and the driver's emotion data for assistance based on the assistance data corresponding to the driving scene information is acquired by a sensor, and the acquired driving characteristic data and the emotion data and the driving characteristic data and the emotion data are combined. Linking the acquired driving scene information with the driver ID, transmitting to an external device, acquiring new support data corresponding to the driving scene information transmitted from the external device, and acquiring the driving scene A method for managing driving characteristic improvement support data is provided, which updates the support data linked to the information to the new support data obtained.

According to the present disclosure, driving characteristic improvement support data based on driving characteristic data and emotion data can be managed more efficiently.

FIG. 4 shows an example of a use case of the driving characteristic management system according to Embodiment 1. FIG. 1 is a block diagram showing an internal configuration example of a vehicle according to Embodiment 1. FIG. FIG. 2 is a block diagram showing an example internal configuration of a driving characteristic server according to the first embodiment; FIG. Block diagram showing an example of the internal configuration of a license server according to Embodiment 1 FIG. 2 is a sequence diagram showing an example of a driver initial registration procedure in the driving characteristic management system according to Embodiment 1. FIG. Flowchart showing an example of an initial registration procedure for a driver in a vehicle Flowchart showing an example of a vehicle ID registration procedure in a vehicle Flowchart showing an example of a driver's license ID registration procedure in a vehicle Flowchart showing an example of a procedure for registering a face image of a driver in a vehicle Flowchart showing an example of a procedure for initial registration of a driver in a driving characteristics server Flowchart showing an example of a vehicle ID registration procedure in the driving characteristic server Flowchart showing an example of a license ID registration procedure in a driving characteristics server Flowchart showing an example of a procedure for registering a face image of a driver in a driving characteristic server 4 is a sequence diagram showing an example of a procedure for collecting driving characteristic data of a driver in the driving characteristic management system according to the first embodiment; FIG. Flowchart showing an example of a procedure for acquiring driving characteristic data of a driver in a vehicle Flowchart showing an example of a procedure for collecting driving characteristic data of a driver in a driving characteristic server A diagram showing an example of a use case of the driving characteristic improvement support system according to the second embodiment. Block diagram showing an internal configuration example of a vehicle according to Embodiment 2 A diagram showing an example of a driving characteristic history table Block diagram showing an internal configuration example of a driving characteristic improvement server according to Embodiment 2 A diagram showing an example of a driving characteristic 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 an example of sensing the driver's safety confirmation behavior for each driving situation Diagram explaining an example of the arrangement of warning indicator lights Diagram explaining an example of speaker arrangement Diagram for explaining an example of modification of driving characteristic improvement support Flowchart showing an example of the operation procedure of the driving characteristic improvement support system according to the second embodiment Flowchart for explaining an example of the operation procedure of the driving characteristic improvement support system according to the second embodiment

(Background leading up to Embodiment 1)
In recent years, eKYC (electronic Know Your Customer), for example, is one type of system that can realize identity verification for users online. eKYC is a facial image or video of the user's face transmitted from a user terminal (e.g., PC (Personal Computer), smartphone, tablet terminal, etc.), and personal information such as the user's name, address, and date of birth. and a moving image of a personal identification document (for example, a driver's license, a residence card, a passport, a My Number card, etc.) in which the user's face image and the user's face image are described. eKYC collects pre-registered registration information related to this user (e.g., moving images, various personal information described in identity verification documents, etc.), acquired user's face image or video, and moving images of identity verification documents. The identity of the user is verified by matching the

Conventionally, the biological information of the driver and the information on the driving operation of the driver are acquired from the vehicle, the driver is specified, and the driving feature information of the specified driver and the ID of the vehicle driven by the driver are obtained. (For example, Patent Document 1: JP-A-2015-71319). However, when the vehicle is a rental car, a shared car, or the like, which is driven by a plurality of different drivers, the driver identification system associates the driver's driving feature information with the ID of the vehicle driven by the driver. Therefore, it was difficult to record and manage driving characteristic information for each driver.

Also, in recent years, there has been an increase in the number of accidents caused by driving errors caused by aging of elderly drivers (elderly drivers). Efforts to prevent such accidents include, for example, cognitive function tests for elderly drivers when renewing their driver's licenses, and recommendations for elderly drivers over a predetermined age to return their driver's licenses. However, if they surrendered their driver's license, the elderly driver could lose the means of transportation that are essential for independent daily living. Therefore, in determining whether or not to return the driver's license, it is possible to visualize changes in the driving behavior of elderly drivers by objectively evaluating the driving behavior of elderly drivers using collected driving characteristic data. Although desired, the driver identification system does not contemplate collecting and managing driving characteristic data for the purpose of obtaining the above-described driver-specific driving ratings.

Therefore, in the following first embodiment, an example of a method of managing driving characteristic data and an on-vehicle device for more efficiently collecting driving characteristic data for each driver and supporting management of the collected driving characteristic data will be described. .

Hereinafter, each embodiment specifically disclosing the management method of driving characteristic data, the vehicle-mounted 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 description than necessary may be omitted. For example, detailed descriptions of well-known matters and redundant descriptions 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. It should be noted that the accompanying drawings and the following description are provided to allow those skilled in the art to fully understand the present disclosure and are not intended to limit the claimed subject matter.

(Embodiment 1)
A use case example of the driving characteristic management system 100 according to the first embodiment will be described with reference to FIG. FIG. 1 is a diagram showing a use case example of the driving characteristic management system 100 according to the first embodiment. The driving characteristic management system 100 in FIG. 1 illustrates an example of transmitting a face image of a driver as an example of biological information.

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

The driving characteristic management system 100 acquires the driving characteristic data of the driver who drives the vehicle transmitted from the 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), accumulates them in the driving characteristic server S1, and manages them. In addition, the driving characteristics management system 100 manages license IDs of each of a plurality of drivers registered in advance in the license server S2. The driving characteristic management system 100 executes driving evaluation for each driver using the driving characteristic server S1 or the license server S2, and transmits the driving evaluation result 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, the in-vehicle camera 13, the gyro sensor 14, the accelerator pedal 17A, the brake It is acquired by the pedal 17B, the turn lamp 17C, the speed sensor 18, the outside sensor/camera 19, the GPS sensor 20, or the steering wheel 17D (see FIG. 2)).

For example, the driving characteristic data is data indicated by at least one of a driving characteristic parameter and a driving characteristic vector, and includes acceleration, jerk, lateral G (that is, acceleration generated perpendicular to the direction of travel), steering angle, etc. , 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, the line of sight of the driver, and the like. The driving characteristic data is not limited to the above example, and may be data indicating the driving characteristic of the driver 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 addition average value calculated based on the number of data included in the driving characteristic data and the value for each data. For example, the driving characteristic vector is represented by an Nth-order vector when the number of data in the driving characteristic data is N (N: an integer equal to or greater than 1).

Each of the vehicles C1, . 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, . and the vehicle ID are linked and transmitted to the driving characteristic server S1. Further, each of the vehicles C1, . are recorded in association with the driver's license ID that has already been initially registered.

In the initial registration, each of the vehicles C1, . . Each of the vehicles C1, . , license plate information) and transmitted to the driving characteristic server S1.

At the time of collecting the driving characteristic data, each of the vehicles C1, . and transmits it to the driving characteristic server S1. Further, each of the vehicles C1, . It is sent to the server S1 to request the driving characteristics server S1 to authenticate the driver (that is, identify the driver). Each of the vehicles C1, . Further, each of the vehicles C1, . When the electric signal indicating that the vehicle has been completed is obtained, the acquisition and transmission of the driver's biometric information are terminated.

Each of the vehicles C1, .

The driver's license ID here refers to the captured image of the driver's license of the driver who drives the vehicle captured by the in-vehicle camera 13, or a driver's license reader capable of reading the driver's license ID written on the driver's license. (illustration) (for example, face image of the driver, information about the driver, various numbers assigned to identify the driver, etc.). The license reader may be capable of transmitting the license ID read by short-range wireless communication such as NFC (Near Field Communication) or Bluetooth (registered trademark) to the processor 12A, or via 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.

The driver's license ID is information about the driver's license obtained by image analysis of the captured image captured by the in-vehicle camera 13, or input by the driver to the input unit 12D (see FIG. 2) of the car navigation device 12. It may be information about a driver's license input by an input operation.

Also, the biometric information of the driver here is one or more face images, irises, fingerprints, veins, voice, etc. of the driver. If the biological information of the driver is the driver's iris, fingerprint, vein, voice, etc., each of the vehicles C1, . . . (not shown).

A face image of the driver is captured by the in-vehicle camera 13 . In addition, it is desirable that a plurality of face images of the driver are captured at the time of initial registration. Includes 1 sheet. When the number of facial images captured at the time of initial registration is two or more, the in-vehicle camera 13 analyzes the orientation of the driver's face by image analysis, One or more face images captured while facing (for example, the left direction, the right direction, etc.) are captured. In the following description, a face image captured when the person is facing left is referred to as a "left face image", and a face image captured when the person is facing right is referred to as a "right face image". .

The iris is obtained by image analysis by the ICM (Intelligent Control Module, not shown) mounted on the vehicle C1, the car navigation device 12, or the driving characteristic server S1 using the face image of the driver captured by the in-vehicle camera 13. may be obtained.

Fingerprints may be acquired by image analysis by the ICM, the car navigation device 12, or the driving characteristic server S1 mounted on the vehicles C1, . Alternatively, it may be acquired by a fingerprint sensor (not shown) provided in the vehicle C1, .

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

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

The driving characteristic server S1 is connected to each of the vehicles C1, . The driving characteristic server S1 executes initial registration based on the control command requesting the initial registration of the 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, . Link and record.

In the initial registration, the driving characteristic server S1 receives a control command requesting initial registration of the driver transmitted from each of the vehicles C1, . Get the ID. The driving characteristic server S1 collates the acquired biometric information of the driver with the license ID to determine whether the driver indicated by the biometric information and the driver indicated by the license ID are the same person (that is, identity verification). When the driving characteristic server S1 determines that the driver indicated by the acquired biometric information and the license ID is 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). The face image of the driver registered here may be one front face image, or may be one front face image and one or more right-facing face images or left-facing face images. .

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

The driving characteristic server S1 executes the driving evaluation using the driving characteristic data of the predetermined driver based on the control command requesting the result of the driving evaluation 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 or not to renew a driver's license, or an employee of an insurance company who handles automobile insurance (products). Accordingly, the staff of the National Police Agency can make a decision regarding renewal of the driver's license based on the predetermined driving evaluation result of the driver displayed on the wireless terminal device P1. Similarly, the employee of the insurance company calculates the automobile insurance premium for the predetermined driver based on the driving evaluation result (that is, the index indicating the degree of safe driving) of the predetermined 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 characteristic server S1 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 a plurality of registered drivers. The driving characteristic server S1 extracts the driving characteristic data of the driver corresponding to the driver's license ID or biometric information included in the control command and the vehicle ID of the vehicle from which the driving characteristic data was acquired, based on the result of the matching. , to the wireless terminal device P1 or the car navigation device 12 .

Here, when the driving characteristic server S1 executes the driving evaluation of the driver based on the accumulated driving characteristic data, the driving characteristic server S1 corresponds to the driver's 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 driver's 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. The license server S2 records and manages the license IDs of multiple drivers. The information recorded and managed by the license server S2 is not limited to the license ID, and may be, for example, information on renewal of the driver's license, 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 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, and uses the matching result as a driving device. Send to property server S1. The driving characteristic server S1 extracts the driving characteristic data of the driver corresponding to the driver's license ID or biometric information included in the control command and the vehicle ID of the vehicle from which the driving characteristic data was acquired, based on the result of the matching. , to the license server S2.

Here, when the driving characteristic server S1 executes the driving evaluation of the driver based on the accumulated driving characteristic data, the driving characteristic server S1 corresponds to the driver's 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) owned by a driver, a relative of the driver, a police officer, an employee of an insurance company, a notebook PC, a tablet terminal, a smart phone, or the like. Note that the wireless terminal device P1 is not limited to the example described above, and may be the car navigation device 12 mounted on the vehicle C1, . . .

The wireless terminal device P1 can receive an input operation by the driver, a relative of the driver, or the like, and generates a control command requesting the driver's driving evaluation result based on the input operation. 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 the control command, and transmits them to the driving characteristic server S1. Further, when the wireless terminal device P1 acquires the driving evaluation result of the driver transmitted from the driving characteristic server S1, the wireless terminal device P1 outputs the acquired driving evaluation result of the driver to the monitor (not shown) of the wireless terminal device P1. . 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 driving evaluation result of the driver on the display unit 12C of the car navigation device 12. Output.

The network NW connects each of the plurality of vehicles C1, . .

Next, an internal configuration example of the vehicle C1, . . . according to the first embodiment will be described with reference to FIG. FIG. 2 is a block diagram showing an internal configuration example of vehicles C1, . . . according to the first embodiment. The internal configuration of the vehicle C1, . is omitted. Since each of the vehicles C1, . . . has the same internal configuration, the internal configuration of the vehicle C1 will be described below.

The vehicle C1 includes 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 by a CAN (Controller Area Network) or the like so that data can be transmitted and received.

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 is not limited to this.

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 electric signal for notifying completion of initial registration, an electric signal for notifying completion of driver identification, and the like, which are transmitted from the driving characteristics server S1, and outputs them to the processor 12A.

The car navigation device 12 is a device capable of accepting a driver's operation. Also, the car navigation device 12 may be an IVI (In-Vehicle Information) device capable of providing, for example, a car navigation function, a location information providing service function, an Internet connection function, a multimedia reproduction 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 section. The processor 12A cooperates with the memory 12B to collectively perform various processes and controls. Specifically, the processor 12A implements the function of each part by referring to the programs and data held in the memory 12B and executing the programs.

The processor 12A starts the initial registration process based on the control command for starting the initial registration of the driver in the driving characteristic server S1 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), the vehicle ID, and initial registration of the driver. It is linked with the control command and transmitted to the driving characteristic server S1. The driver's license ID may be driver's license information input to the input unit 12D. Similarly, it may be the license plate information input to the input unit 12D by the driver's operation.

The processor 12A starts acquiring the driver's driving characteristic data at the timing of acquiring the control command from the ECU 16 or the communication device 11 indicating that the driver's boarding has been detected. The processor 12A acquires the angular velocity of the vehicle C1 as driving characteristic data based on the electrical signal output from the gyro sensor 14, and receives various sensors (for example, the in-vehicle camera 13, the gyro sensor 14, the accelerator pedal 17A) via the ECU 16. , brake pedal 17B, turn lamp 17C, speed sensor 18, vehicle exterior sensor/camera 19, GPS sensor 20, steering wheel 17D, etc.). Driving characteristic data acquired by various sensors will be described later. The processor 12A associates the acquired driving characteristic data with the vehicle ID, and transmits them to the driving characteristic server S1. In addition, the processor 12A causes the in-vehicle camera 13 to capture a facial image of the driver as the biological information of the driver used for driver registration or identification performed by the driving characteristic server S1. The processor 12A associates the face image of the driver output from the in-vehicle camera 13 with the vehicle ID, and transmits the result to the driving characteristic server S1.

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

In addition, the processor 12A may perform image analysis of the face image of the driver output from the in-vehicle camera 13, and detect the line of sight of the driver, the drowsiness detection, the emotion detection, and the like. The processor 12A associates the detected detection result with the vehicle ID as driving characteristic data and transmits the data to the driving characteristic server S1.

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) for storing programs and data defining the operation of the processor 12A. have. The RAM temporarily stores data or information generated or obtained by the processor 12A. 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 unit 12D is a user interface configured integrally with the display unit 12C. The input unit 12D converts the received driver's operation into an electric 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 accepts an input operation of a driver's license ID or a 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 captures an image of 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 boarding by the driver, and outputs the image to the processor 12A. The processor 12A analyzes the captured face image of the driver to detect the orientation of the driver's face. When the processor 12A determines that the detected face orientation of the driver is the preset face orientation, the processor 12A associates the face image with the vehicle ID, and transmits the information from the communication device 11 to the driving characteristic server S1. send. Note that the process of detecting the orientation of the driver's face from the face image may be executed by the driving characteristic server S1.

For example, if a frontal face image is required for driver authentication during initial registration or identification of a driver during recording of driving characteristic data, processor 12A determines that the detected driver's face orientation is frontal. The front face image determined as the vehicle ID is associated with the vehicle ID and transmitted to the driving characteristic server S1.

Further, for example, in driver authentication at initial registration or identification of a driver at the time of recording driving characteristic data, when face images in which the driver faces a plurality of different directions are required, the processor 12A One or more face images selected from each of a front face image determined to be facing the front, a right-facing face image determined to be facing right, or a left-facing face image determined to be facing left, and to select. The processor 12A associates the selected two or more face images with the vehicle ID, and transmits them to the driving characteristic server S1. As a result, the vehicle C1 can more effectively suppress impersonation of the driver using the front face image of the driver captured in advance.

Further, the in-vehicle camera 13 may capture an image of the driver's driver's license based on the driver's input operation 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 to display it on the display unit 12C, and the captured image displayed on the display unit 12C includes the captured area of the driver's license. The frame line shown may be superimposed. As a result, the car navigation device 10 can support the imaging of the face image of the driver's license used to identify the driver, or the imaging of the driver's license from which various information described on the driver's license can be read.

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

The memory 15 has, 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) for storing programs and data defining 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. Moreover, the memory 15 may store the vehicle ID of the vehicle C1.

The ECU 16 comprehensively executes processing and control of each unit. 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. Based on the electric signal output from the operation unit 17, the ECU 16 receives various operation information (for example, rapid 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 detects conditions for detecting the driver's boarding, such as closing the door of the driver's seat, wearing the seat belt of the driver's seat, releasing the side brake after the ignition is turned on, and a load sensor (not shown) provided in the driver's seat. The driver's seated detection is performed by the driver, or the torque of the steering wheel 17D is detected. The ECU 16 detects whether the driver gets on the vehicle based on whether or not one or more or two conditions for detecting the driver's getting on are satisfied. The ECU 16 generates a control command indicating that the driver's boarding has been detected, and outputs the control command to the processor 12A of the car navigation device 12 or the communication device 11 .

In addition, the ECU 16 detects, for example, the opening of the driver's door, the unlocking of the driver's seat belt, the ignition OFF, or the detection of driving by a load sensor (not shown) provided in the driver's seat, as conditions for detecting the driver's getting off the vehicle. Detects the absence of a person, etc. The ECU 16 detects the driver getting off the vehicle based on whether or not one or more or two or more driver getting off detection conditions are satisfied. The ECU 16 generates a control command indicating that it has detected that the driver has gotten off the vehicle, and outputs the control command 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 number of revolutions of the drive shaft inside the vehicle C1. The speed sensor 18 outputs the measured speed of the vehicle C1 to the processor 12A.

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

The GPS sensor 20 is not limited to the signal of the US GPS (Global Positioning System), for example, a satellite (not shown) capable of providing a satellite positioning service such as Russia's GLONASS (Global Navigation Satellite System) or Europe's Galileo, or A satellite positioning signal transmitted from a quasi-zenith satellite (not shown) is received. The GPS sensor 20 calculates information on the traveling speed and traveling position of the vehicle C1 based on the received satellite positioning signals, and outputs the information to the processor 12A. The GPS sensor 20 may be used to calculate the travel speed and travel position information of the vehicle C1 based on satellite positioning signals or quasi-zenith satellites.

Next, referring to FIG. 3, the internal configuration of the driving characteristic server S1 according to Embodiment 1 will be described. FIG. 3 is a block diagram showing an example internal configuration of the driving characteristic server S1 according to the first embodiment. In the following description, various data or information collected (recorded) and managed by the driving characteristic server S1 will be described using the driving characteristic table TB1 as an example for ease of understanding. is not required and may be omitted.

The driving characteristic server S<b>1 includes a communication unit 31 , a processor 32 and a memory 33 .

The communication unit 31 is connected to each of the vehicles C1, .

The processor 32 is configured using, for example, a CPU, DSP, or FPGA, and controls the operation of each section. The processor 32 cooperates with the memory 33 to collectively perform various processes and controls. Specifically, the processor 32 refers to the programs and data held in the memory 33 and executes the programs, thereby implementing the functions of the units. Processor 32 generates driving characteristic table TB1 and stores it in memory 33 .

The driving characteristic table TB1 records and manages a vehicle ID, driving characteristic data, and biometric information (a driver's face image in the example shown in FIG. 3) in association with a driver's license ID. As an example, the driving characteristic table TB1 shown in FIG. 3 records a user ID that is assigned to each driver and that can identify the driver, in association with the driver's license ID. Also, 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 characteristic table TB1 shown in FIG. The certificate ID "YYY" is linked with the vehicle ID "KKK", the user ID "BBB", the facial image data, and the driving characteristic data, and the license ID "ZZZ" is linked with the vehicle ID "MMM". , the user ID “CCC”, face image data, and driving characteristic data are associated with each other and recorded. As a result, the driving characteristic table TB1 shows that when a vehicle having the same vehicle ID "KKK" is driven by a plurality of different drivers (for example, two users "AAA" and "BBB"), However, since the driving characteristic data can be recorded for each license ID, the driving characteristic data can be managed for each driver.

Processor 32 starts initial registration processing based on the control command requesting initial registration transmitted from each of vehicles C1, . . . . The processor 32 associates the driver's license ID, the biological information of the driver, and the vehicle ID transmitted from each of the vehicles C1, . If the processor 32 determines that the acquired driver's license ID has already been registered in the driving characteristics table TB1, the driver's biometric information linked to the registered driver's license ID and the acquired biometric information Match information. When 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 matches the acquired biometric information to the license ID registered in the driving characteristic table TB1. The vehicle ID obtained is further linked and recorded.

When the processor 32 acquires the vehicle ID and the driving characteristic data transmitted from each of the vehicles C1, . Further, when the processor 32 acquires the vehicle ID transmitted from each of the vehicles C1, . Then, it is determined whether or not the driver corresponding to the acquired biometric information has been registered.

The processor 32 has already registered a driver corresponding to the acquired biometric information (that is, the acquired biometric information of the driver and the biometric information registered (stored) in the driving characteristic table TB1 are collated). If so, 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. This allows processor 32 to record and manage driving characteristic data for each license ID (ie, driver).

Also, the processor 32 acquires a control command requesting a driving evaluation for a predetermined driver transmitted from the wireless terminal device P1, and the driver's license ID or biometric information corresponding to the predetermined driver. The processor 32 collates 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 uses the driver's driving characteristic data corresponding to the driver's license ID or the biometric information included in the control command to perform the driving evaluation of the driver. The processor 32 generates driving evaluation results and transmits them to the wireless terminal device P1.

Similarly, the processor 32 acquires a control command requesting a driving evaluation for a given driver transmitted from the license server S2, and the license ID or biometric information corresponding to the given driver. The processor 32 collates the obtained driver's license ID or biometric information with the driver's license IDs or biometric information registered in the memory 33 . Based on the verification result, the processor 32 uses the driver's driving characteristic data corresponding to the driver's license ID or the biometric information included in the control command to perform the driving evaluation of the driver. Processor 32 generates and transmits driving evaluation results to license server S2.

The memory 33 has, for example, a RAM as a work memory that is used when executing each process of the processor 32 and a ROM that stores programs and data that define the operation 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 obtained 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. FIG.

Note that the memory 33 may accumulate driving characteristic data for a predetermined period of time or a predetermined number of times of driving for each driver. The predetermined period here is, for example, the most recent 6 months, the most recent 50 times, or the like. One drive is a drive performed between the timing at which the driver's boarding is detected by the vehicles C1, . . . and the timing at which the driver's getting off 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 of time or more among the plurality of driving characteristic data that have been stored in association with the same license ID, the processor 32 has accumulated the driving characteristic data for a predetermined period or longer. Delete the driving characteristic data In addition, when the processor 32 determines that there is driving characteristic data of driving more than the most recent predetermined number of times among the driving characteristic data accumulated in association with the same license ID, the processor 32 Delete property data. As a result, 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, referring to FIG. 4, the internal configuration of the license server S2 according to the first embodiment will be described. FIG. 4 is a block diagram showing an example internal configuration of the license server S2 according to the first embodiment. In the following description, the license table TB2 is used as an example to explain various data or information collected (recorded) and managed by the license server S2 for ease of understanding. is not required and may be omitted.

The license server S2 includes a communication unit 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. 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 mounted on each of the vehicles C1, . . . via the network NW. may be connected.

The processor 42 is configured using, for example, a CPU, DSP, or FPGA, and controls the operation of each unit. The processor 42 cooperates with the memory 43 to collectively perform various processes and controls. Specifically, the processor 42 refers to the programs and data held in the memory 43 and executes the programs to implement the functions of the respective units.

The processor 42 receives, for example, license IDs of a plurality of drivers transmitted from each of the wireless terminal devices P1 owned by the drivers, police officers, employees of insurance companies, etc., and information on the drivers (for example, driving person's name, address, face image data as an example of biometric information, etc.). The processor 42 creates a license table TB2 by associating the acquired license ID with the information about the driver corresponding to this license ID. Processor 42 stores generated license table TB2 in memory 43 .

The driver's license table TB2 links the driver's information (the driver's name and address in FIG. 4) and the driver's biological information (the driver's face image in the example shown in FIG. 4) to the driver's license ID. be recorded and managed. 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 driver's license table TB2 shown in FIG. The driver's name "△△□", the address "***", and the face image data are linked to the ID "BBB", and the driver's name "○△× ”, the address “***”, and the data of the face image are associated with each other and recorded.

Also, the processor 42 acquires the control command requesting the driving evaluation of the predetermined driver transmitted from the wireless terminal device P1 and the driver's license ID corresponding to the predetermined driver. The processor 42 generates a control command requesting a driving evaluation for a predetermined driver, associates the generated control command with the obtained license ID, and transmits them to the driving characteristic server S1. When the processor 42 acquires the driving evaluation result of the 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 has, for example, a RAM as a work memory that is used when executing each process of the processor 42, and a ROM that stores programs and data that define the operation of the processor 42. FIG. 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 obtained 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. Memory 43 stores license table TB2 generated by processor .

Next, referring to FIG. 5, an initial driver registration procedure executed by the driving characteristic management system 100 will be described. FIG. 5 is a sequence diagram showing an example of an initial driver registration procedure of the driving characteristic management system 100 according to the first embodiment. In the following description, an example in which the driver's front face image, left-facing face image, and right-facing face image are used as the biometric information of the driver will be described, but it is needless to say that the present invention is not limited to this.

A driver, who is an example of a user who uses the driving characteristic management system 100, operates the car navigation device 12 and selects (presses) an initial registration button (not shown) displayed on the display unit 12C. An operation to request 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 biometric information) of the driver based on the driver's operation received by the input unit 12D. The in-vehicle camera 13 is controlled by the car navigation device 12 and images the face of the driver (St102). Further, the in-vehicle camera 13 captures an image of the driver's driver's license (an example of the driver's license ID) held within the angle of view of the in-vehicle camera 13 by the driver (St103). The in-vehicle camera 13 associates the captured face image of the driver with the driver's license ID and transmits them to the car navigation device 12 (St104).

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

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

Based on the control command requesting initial registration, the driving characteristic server S1 collates the front face image of the driver appearing in the acquired driver's license ID with the registered face image (St108). When the driving characteristic server S1 determines that the front face image of the driver reflected in the driver's license ID matches the registered face image (that is, the driver is the same driver), the driver's face image and The license ID and the vehicle ID are linked and registered (stored) in the memory 33 to complete 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 is completed, and transmits the notification 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 to notify the driver of the initial registration completion (St111).

The driving characteristic server S1 compares the license IDs of a plurality of registered drivers with the obtained license IDs or face images, and as a result of the matching, the license IDs of the plurality of registered drivers are checked. and the obtained driver's license ID or face image do not match (that is, the same driver is not registered), the process of step St108 may be executed to execute initial registration. . When the driving characteristic server S1 determines that the license IDs of a plurality of registered drivers match the obtained license ID or face image (that is, the same driver is registered), may complete the initial registration by linking the acquired vehicle ID to the registered driver's 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, referring to FIG. 6, an initial driver registration procedure executed in each of the vehicles C1, . . . will be described. FIG. 6 is a flow chart showing an example of an initial driver registration procedure for vehicles C1, . . .

Each of the vehicles C1, .

Each of the vehicles C1, . is output to and displayed on the display unit 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 the initial registration data. One or more screens.

On the other hand, each of the vehicles C1, . . . ends the initial registration procedure shown in FIG.

Each of the vehicles C1, . . . performs vehicle ID registration (St13), license ID registration (St14), and facial image registration (St15). Each of the vehicles C1, .

Each of the vehicles C1, . exit.

On the other hand, in the process of step St16, each of the vehicles C1, . Then, the initial registration procedure corresponding to the incomplete processing of steps St13 to St15 is displayed, and only the incomplete processing of steps St13 to St15 is executed again. For example, each of the vehicles C1, . ID registration process) is executed again.

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

The car navigation device 12 outputs to the display unit 12C an image, a video, or a sound corresponding to the vehicle ID registration procedure recorded in the memory 12B (St131).

Each of the vehicles C1, .

The car navigation device 12 receives an 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 own vehicle recorded in the memory 15 (St132B).

The in-vehicle camera 13 captures the vehicle inspection certificate of the own vehicle held within the angle of view by the driver, and outputs the captured image of the vehicle inspection inspection to the processor 12</b>A of the car navigation device 12 . The car navigation device 12 analyzes the captured image of the output vehicle inspection certificate and acquires the vehicle ID appearing 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, referring to FIG. 8, an initial driver registration procedure executed in each of the vehicles C1, . . . will be described. FIG. 8 is a flow chart showing an example of driver's license ID registration procedures for vehicles C1, . . . Specifically, FIG. 8 is a flowchart showing the process of step St14 shown in FIG.

The car navigation device 12 outputs to the display unit 12C an image, a video, or a sound corresponding to the license ID registration procedure recorded in the memory 12B (St141).

The car navigation device 12 receives an input of a driver's license ID (for example, vehicle license plate information, etc.) to the input unit 12D (St142). Note that the processing 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 characteristic server S1 obtains the driver's 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 within the angle of view 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 them to the communication device 11 . Communication device 11 transmits the captured image of the driver's license output from car navigation device 12 and the driver's license ID to driving characteristic server S1 (St144). If the processing of 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 characteristic server S1.

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

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

The in-vehicle camera 13 captures an image of the driver's driver's license presented within the angle of view of the in-vehicle camera 13 by the driver. Here, the in-vehicle camera 13 covers the entire area of the driver's license. , address information, nationality information, valid date information, number information, type information, etc.) are captured within the angle of view (St152). In-vehicle camera 13 outputs the captured image of the driver's license to processor 12A.

When the license ID is input by the driver in step St142, only the face image of the driver shown in the driver's license may be captured, or in the process of step St143, the face image of the driver, In the case of capturing an image of various information written on the driver's license, the processing of step St152 may be omitted. Further, the driving characteristics server S1 may determine whether or not the face image of the driver and various information described in the driver's license are included in the captured image of the driver's license. , may be executed by the processor 12</b>A 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 takes an image of the driver's face facing rightward with respect to the in-vehicle camera 13 positioned in front of the driver (St154), and outputs the imaged right-facing face image F12 to the processor 12A. . The in-vehicle camera 13 takes an image of the driver's face facing leftward with respect to the in-vehicle camera 13 positioned in front of the driver (St154), and outputs the imaged left-facing face image F13 to the processor 12A. .

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

Next, referring to FIG. 10, an initial driver registration procedure executed by the driving characteristic server S1 will be described. FIG. 10 is a flow chart showing an example of an initial driver registration procedure in the driving characteristic server S1.

The driving characteristic server S1 in the driving characteristic management system 100 determines whether or not a control command requesting initial registration has been obtained from each of the vehicles C1, . . . (St21).

When the driving characteristic server S1 determines in the process of step St21 that the control command requesting initial registration has been acquired from each of the vehicles C1, . . . Execute the registration process. Note that the initial registration data referred to here is, for example, the vehicle ID of the vehicle, the driver's license ID, the driver's biometric information (here, a plurality of face images of the driver, which are displayed in three different directions). (three face images captured from each of the above), but needless to say, the present invention is not limited to this.

On the other hand, when the driving characteristics 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, . exit.

The driving characteristics server S1 executes registration of the vehicle ID (St22), registration of the driver's license ID (St23), and registration of the face image (St24). The driving characteristic server S1 determines whether or not all the processes (that is, initial registration) of steps St22 to St24 have been completed (St25).

When the driving characteristic server S1 determines in the process of step St25 that the processes of steps St22 to St24 (that is, the initial registration) are all completed (St25, YES), the initial registration procedure shown in FIG. 10 is terminated. do.

On the other hand, when the driving characteristic server S1 determines in the process of step St25 that the processes of steps St22 to St24 (that is, the initial registration) are not all completed (St25, NO), the process of step St21 Then, the initial registration procedure corresponding to the incomplete processes of steps St22 to St24 is displayed, and only the incomplete processes of steps St22 to St24 are executed again. For example, each of the vehicles C1, . Execute.

Next, referring to FIG. 11, an initial driver registration procedure executed by the driving characteristic server S1 will be described. FIG. 11 is a flow chart showing an example of a vehicle ID registration procedure in the driving characteristic server S1. Specifically, FIG. 11 is a flow chart 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 or not the analyzed vehicle ID is valid as the vehicle ID to be initially registered (St223). For example, when the acquired vehicle ID is a captured image, the driving characteristic server S1 performs image analysis to analyze whether the vehicle ID is based on a vehicle inspection certificate or a license plate, or If the vehicle ID is character information input by the driver's operation, it is analyzed whether the character information is information contained in the vehicle inspection certificate or the license plate. When the driving characteristic server S1 determines that the analysis result is information that can be used as the vehicle ID, the driving characteristic server S1 determines that the vehicle ID is valid.

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

On the other hand, when the driving characteristic server S1 determines in the processing of step St223 that the analyzed vehicle ID is not valid as the vehicle ID to be initially registered (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 notifying 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 steps St234 (see FIG. 12) and step St249 (see FIG. 13).

Next, referring to FIG. 12, an initial driver registration procedure executed by the driving characteristic server S1 will be described. FIG. 12 is a flow chart showing an example of a license ID registration procedure in the driving characteristic server S1. Specifically, FIG. 12 is a flow chart 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 characteristic server S1 stores various information of the driver's license corresponding to the acquired license ID (for example, the driver's face image, name information, address information, nationality information, valid date written on the driver's license, etc.) information, number information, type information, etc.) and transmits it to the license server S2. The driving characteristic server S1 acquires various information of the driver's license corresponding to the license ID transmitted from the license server S2 (St232A). Note that the process of step St232A is executed when the face image described in the driver's license cannot be acquired from each of the vehicles C1, . is not matched.

The driving characteristic server S1 determines whether the obtained 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 determines whether or not various information can be read from the captured image, or determines whether the driver's license is the expiration date, and the driver's facial image included in the acquired license ID is compared with the facial image of the driver registered in the driving characteristic table TB1 to identify the driver. determine whether it is possible.

After the processing of step St232A, or when determining that the acquired license ID is valid in the processing of step St232B (St232B, YES), the driving characteristic server S1 registers the acquired license ID ( St 233). If the driving characteristic server S1 determines that the driver's license ID has already been registered in the driving characteristic table TB1, the process of registering the license ID in step St233 may be omitted.

On the other hand, when the driving characteristic server S1 determines in the processing 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 (St232C). Note that the driving characteristic server S1 may similarly execute the process of step St232C when various information on the driver's license cannot be obtained from the license server S2 in the process of step St232A.

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

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

The driving characteristic server S1 receives and acquires the captured images of the driver's license transmitted from each of the vehicles C1, . . . (St241). Further, the driving characteristic 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 biometric information) transmitted from each of the vehicles C1, . . . (St242).

The driving characteristic server S1 performs face matching between the driver's face image in the captured image of the acquired driver's license and the front face image, and compares the face image of the driver in the captured image of the driver's license with the front face image. , and the obtained front face image are the same or similar (that is, whether or not they are the same person) (St243).

In the processing of step St243, the driving characteristic server S1 determines that the face image of the driver appearing 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), this front face image and each of the left-facing face image and the right-facing face image are used to perform face matching (St244).

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

The driving characteristic server S1 determines whether or not the face shown in the front face image and the faces shown in 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 processing of step St246 that the face reflected in the front face image and the faces reflected in 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), the captured image of the driver's license and each of the front face image, the left face image, and the right face image are linked to the license ID determined to be valid in the process of step St232B. is recorded (St247).

On the other hand, in the processing of step St246, the driving characteristic server S1 determines that the face reflected in the front face image and the faces reflected in 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). If (St246, NO), a control command is generated to request re-imaging (i.e., re-imaging) of the captured image of the driver's license, the front face image, the left-facing face image, and the right-facing face image, and via the network NW. is transmitted (notified) to the vehicle (St248).

The driving characteristic server S1 registers each of a plurality of facial images as an example of biometric information in association with a driver's license ID, generates a control command for notifying completion of registration of the facial image, and, via the network NW, It transmits (notifies) to the vehicle (St249). Note that the process of step St249 may be executed simultaneously with the processes of steps St226 (see FIG. 11) and step St234 (see FIG. 12).

Next, referring to FIG. 14, a procedure for collecting driving characteristic data of the driver executed by the driving characteristic management system 100 will be described. FIG. 14 is a sequence diagram showing an example of a driver's driving characteristic data collection procedure of the driving characteristic management system 100 according to the first embodiment. In the following description, an example in which the driver's front face image, left-facing face image, and right-facing face image are used as the biometric information of the driver will be described, but it is needless to say that the present invention is not limited to this.

The procedure for collecting the driving characteristic data, which will be described with reference to FIGS. 14 to 16, is a process that is executed after the initial registration is completed or when the driver drives the vehicle C1 that has been initially registered in advance. be. 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 boarding of the driver based on whether or not one or more or two or more driver boarding detection conditions are satisfied (St302). The ECU 16 generates a control command indicating that the driver's boarding has been detected, outputs the control command to the processor 12A of the car navigation device 12, and starts sensing (obtaining) driving characteristic data of the driver. The car navigation device 12 starts sensing (obtaining) driving characteristic data of the driver based on the control command output from the ECU 16 .

The driving characteristic data is obtained from various sensors (for example, the in-vehicle 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 exterior sensor/camera 19, the GPS sensor 20, etc. 2)) and output to the car navigation device 12 or the ECU 16. FIG.

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 one or more acquired driving characteristic data with the vehicle ID and outputs them to the communication device 11 (St304). The communication device 11 transmits the linked one or more pieces of driving characteristic data and the vehicle ID to the driving characteristic server S1 via the network NW (St305).

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

In addition, the vehicle C1 captures an image of the driver's face with the in-vehicle camera 13 (St307). The in-vehicle camera 13 outputs the captured face 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 them to the communication device 11 (St308). The communication device 11 transmits one or more associated face images of the driver and the vehicle ID to the driving characteristic server S1 via the network NW (St309).

Note that the face images captured in the process of step St307 include a plurality of face images (for example, the driver's front face image, left-facing face image, and right-facing It is preferable that the face image is two or more of the face images, but at least one front face image is sufficient. Further, determination of the direction of the driver's face reflected in the face image may be performed by the driving characteristic server S1.

The driving characteristic server S1 receives and acquires the vehicle ID and the face image of the driver transmitted from the communication device 11 (St310). The driving characteristic server S1 performs face matching on the obtained facial images of the drivers, and compares the facial images of a plurality of drivers registered in the driving characteristic table TB1 (for example, the facial images appearing in the captured image of the driver's license). Among them, it is determined whether or not there is a face image identical or similar to the obtained face image of the driver (St311).

The driving characteristic server S1 selects the driver corresponding to the facial image identical or similar to the obtained facial image of the driver among the facial images of the plurality of drivers registered in the driving characteristic table TB1. Identify the driver corresponding to the image. Further, the driving characteristic server S1 extracts the driving characteristic data associated with the same vehicle ID as the vehicle ID associated with the facial image of the driver from among the temporarily stored driving characteristic data. The driving characteristic server S1 records (stores) the extracted driving characteristic data in association with the identified driver's license ID (St312).

After finishing driving, the driver gets off the vehicle (St313). The ECU 16 of the vehicle C1 detects the driver getting off based on whether or not one or more or two or more driver getting off detection conditions are satisfied (St314). The ECU 16 generates a control command indicating that the driver has exited the vehicle, outputs the control command to the processor 12A of the car navigation device 12, and terminates sensing (acquisition) of the driver's driving characteristic data. The car navigation device 12 terminates sensing (acquisition) of 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 from the communication device 11 during the period T1 in the driving characteristic table TB1 in association with the license ID of the driver.

When the license server S2 acquires the control command requesting the driving evaluation of the 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. are linked and transmitted to the driving characteristic server S1 (St316).

The driving characteristic server S1 acquires the control command and license ID transmitted from the license server S2. The driving characteristic server S1 collates the license IDs of the plurality of drivers registered in the driving characteristic table TB1 with the acquired predetermined driver's license ID based on the acquired control command. The driving characteristic server S1 uses the driving characteristic data linked to the collated license ID to perform the driving evaluation of the predetermined driver (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 characteristic server S1 (St319). The license server S2 stores 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 implemented by the car navigation device 12 . Note that the predetermined driver's driving evaluation process 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's driving characteristic data acquisition procedure executed in each of the vehicles C1, . . . will be described. FIG. 15 is a flow chart showing an example of a procedure for acquiring the driving characteristic data of the drivers of the vehicles C1, . . .

Each of the vehicles C1, . In the process of step St31, each of the vehicles C1, .

On the other hand, each of the vehicles C1, . Continue detection.

Each of the vehicles C1, . It is desirable that the face images captured here are the front face image F21, the right-facing face image F22, and the left-facing face image F23, but are not limited thereto.

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

Each of the vehicles C1, . When each of the vehicles C1, . The procedure for acquiring the driver's driving characteristic data shown is terminated. Each of the vehicles C1, . It may be transmitted to the driving characteristic server S1.

On the other hand, when each of the vehicles C1, . Continue to acquire data. Note that the process of step St33 may be omitted after the driver identification process (step St44) by the driving characteristic server S1 is completed.

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

The driving characteristic server S1 determines whether or not 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).

If the driving characteristic server S1 determines in the process of step St41 that it has received the vehicle ID, the one or more driving characteristic data, and the one or more facial images transmitted from each of the vehicles C1, . . . , 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, the one or more driving characteristic data, and the 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 matching on the acquired face image of the driver (St43). The driving characteristic server S1 selects a face image that is the same as or similar to the acquired driver's face image among the plurality of driver's face images (for example, the face image shown in the captured image of the driver's license) registered in the driving characteristic table TB1. The driver's license ID linked to the facial image identical or similar to the acquired facial image of the driver is specified based on whether or not there is a facial image to be acquired (St44).

Here, before the process of step St43, the driving characteristic server S1 collates the vehicle IDs transmitted from each of the vehicles C1, . , one or more driver's license IDs associated with the matched vehicle ID may be extracted. As a result, in the process of step St44, the driving characteristic server S1 reduces the number of facial images of the driver that have been registered in the driving characteristic table TB1 and are compared with the acquired facial image of the driver. The accuracy of matching can be improved.

When the driving characteristic server S1 determines in the process of step St44 that there is a facial image identical or similar to the obtained facial image of the driver, the driving characteristic server S1 determines the driver's license ID linked to the facial image. Then, it is determined that the driver corresponding to the obtained face image has been identified (St44, YES). The driving characteristic server S1 associates the acquired driving characteristic data with the specified license ID and records (accumulates) it in the driving characteristic table TB1 (St45).

On the other hand, when the driving characteristics server S1 determines in the process of step St44 that there is no face image identical or similar to the acquired face image of the driver, the driver's license ID linked to this face image (St44, NO). The driving characteristic server S1 determines whether or not it has received a control command for notifying the end of driving from each of the vehicles C1, . . . (St46).

When the driving characteristic server S1 determines in the process of step St46 that it has received a control command to notify the end of driving from each of the vehicles C1, . , and 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 face image. When the driving characteristic server S1 determines that the driver's license ID is identified, the driving characteristic data that is associated with the same vehicle ID and is temporarily stored is linked to the identified license ID and recorded ( accumulation) (St47A). As a result, the driving characteristic server S1 can accumulate the temporarily stored driving characteristic data even if the initial registration of the driver's license ID has not been completed.

Further, when the driving characteristic server S1 determines in the process of step St46 that it has received a control command to notify the end of driving from each of the vehicles C1, . . . The acquired 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 linked to the vehicle ID whose license ID has been identified and one or more face images from each of the vehicles C1, . . . (St48).

When the driving characteristic server S1 determines in the process of step St48 that it has received one or more driving characteristic data linked to the vehicle ID whose license ID has been specified and one or more face images (St48 , YES), the acquired driving characteristic data is associated with the identified license ID and recorded (accumulated) in the driving characteristic table TB1 (St45).

On the other hand, when the driving characteristic server S1 determines in the process of step St48 that it has not received one or more driving characteristic data linked to the vehicle ID whose license ID has been identified and one or more face images. (St48, NO), the driving characteristics server S1 determines whether or not it has received a control command to notify the end of driving from each of the vehicles C1, . . . (St49).

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

On the other hand, when 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, . . . return.

As described above, the method of 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, includes the biological information of a plurality of drivers (an example of The biological information registered in the characteristic table TB1) and the driver's license ID are linked and registered, and the biological information of the driver who drives the vehicle C1, . and when it is determined that there is biometric information identical or similar to the biometric information (biological information transmitted from each of the vehicles C1, . . . ) among the registered biometric information of the drivers The driver's license ID and the driving characteristic data linked to the biometric information are linked and recorded.

As a result, the driving characteristic server S1 according to Embodiment 1 can record the identified driver's license ID in association with the driving characteristic data of the driver transmitted from each of the vehicles C1, . . . Even when driving a plurality of different vehicles, the driving characteristic data of the driver can be managed more efficiently. Therefore, in collecting and managing (recording) driving characteristic data used for driving evaluation for determining whether or not to return the 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 behavior of corresponding elderly drivers.

Further, as described above, the driving characteristic server S1 according to the first embodiment further acquires the biological information, the driving characteristic data, and the vehicle ID (an example of the vehicle identification information) that can identify each of the vehicles C1, . . . , when it is determined that there is the same or similar biometric information among the registered biometric information of the plurality of drivers (the biometric information transmitted from each of the vehicles C1, . . . ), the same or similar biometric information The linked license ID, driving characteristic data, and vehicle ID are linked and recorded. As a result, the driving characteristic server S1 according to the first embodiment makes it possible to identify the vehicle for which the driving characteristic data is acquired, and objectively evaluates the driving operation of each vehicle of the elderly driver corresponding to the driver's license ID. driving characteristic data can be collected and managed (recorded) more effectively.

In addition, as described above, the driving characteristic server S1 according to the first embodiment has the same or similar biological information among the plurality of registered drivers' biological information (biological information transmitted from each of the vehicles C1, . . . ). If it is determined that there is no biometric information, the driving characteristic data and the vehicle ID are associated and temporarily stored. As a result, the driving characteristic server S1 according to Embodiment 1 links the driving characteristic data transmitted from each of the vehicles C1, . By attaching it, the driving characteristic data can be temporarily stored until the driver is specified.

Further, as described above, the driving characteristic server S1 according to the first embodiment further acquires the driving end information of the vehicles C1, . . . If it is determined that there is no identical or similar biological information among the biological information (biological information transmitted from each of the vehicles C1, . . . ), the driving characteristic data and the vehicle ID are associated and temporarily stored. As a result, the driving characteristic server S1 according to Embodiment 1, even when the identification of the driver using the biological information is not completed at the timing when the driver finishes driving, By associating 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 has the same or similar biological information among the plurality of registered drivers' biological information (biological information transmitted from each of the vehicles C1, . . . ). If it is determined that there is no biometric information, new biometric information of the driver driving the vehicle (new biometric information transmitted from each of the vehicles C1, . 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 stored driving characteristic data and the vehicle ID are linked. to record. As a result, the driving characteristic server S1 according to Embodiment 1 acquires new biological information of the driver from each of the vehicles C1, . Based on this, the driver identification process 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 vehicle ID can be linked and recorded.

In addition, as described above, the driving characteristic server S1 according to the first embodiment has the same or similar biological information among the plurality of registered drivers' biological information (biological information transmitted from each of the vehicles C1, . . . ). 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 in the memory 33 the driving characteristic data for which the driver is determined to be unidentifiable. .

Further, as described above, the driving characteristic server S1 according to the first embodiment further acquires the driving end information of the vehicles C1, . . . If it is determined that there is no identical or similar biological information among the biological information (biological information transmitted from each of the vehicles C1, . . . ), the driving characteristic data is deleted. As a result, the driving characteristic server S1 according to Embodiment 1 does not record in the memory 33 the driving characteristic data for which it is determined that the driver cannot be identified at the timing when the driver finishes driving. can be more effectively suppressed.

As described above, the driving characteristic server S1 according to Embodiment 1 acquires the driver's biological information and the driver's license ID corresponding to the biological information, and obtains the driving characteristics included in the biological information and the driver's license ID. If it is determined that the face image of the person matches, the biometric information and the driver's license ID are linked and registered. As a result, the driving characteristic server S1 according to the first embodiment stores the driver's biometric information (for example, face image, iris, etc.) transmitted from each of the vehicles C1, and the driver's face included in the driver's license ID. By registering a new driver's license ID based on the result of matching with the image, spoofing by others can be suppressed more effectively.

Further, as described above, the biometric information (registered biometric information) registered in the driving characteristic server S1 according to Embodiment 1 is facial images of a plurality of drivers. Also, the biological information (biological information transmitted from each of the vehicles C1, . . . ) is the facial image of the driver who drives the vehicle. As a result, the driving characteristic server S1 according to the first embodiment uses the face images of the drivers captured and transmitted by the respective vehicles C1, . . . The driver can be identified by face matching with the face image. In addition, by using the face image as the biometric information, each of the vehicles C1, . It can be sent to the property server S1. Therefore, the driving characteristic server S1 repeats the process of requesting transmission of the face image of the driver and the face matching process using the transmitted face image to each of the vehicles C1 until the driver is specified. can be executed repeatedly.

In addition, as described above, the driving characteristic server S1 according to Embodiment 1 stores a front face image (an example of the first registered face image) in which the face of the driver faces the front (an example of the first direction), A right-facing face image or 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, is registered in association with the driver's license ID. , vehicles C1, . A facial image (an example of a second facial image) and driving characteristic data are acquired, and among a plurality of registered frontal facial images (an example of a first registered facial image) transmitted from vehicles C1, . . . A frontal face image identical or similar to the frontal face image, and rightward-facing face images transmitted from vehicles C1, . Alternatively, a right-facing face image or a left-facing face image identical or similar to the left-facing face image is collated, respectively, and the front face images transmitted from the vehicles C1, . If it is determined that there is a right-facing face image or left-facing face image that is the same or similar to the right-facing face image or left-facing face image sent from The linked license ID and the driving characteristic data are linked and recorded. As a result, the driving characteristic server S1 according to the first embodiment is configured to store the transmitted front face images of the drivers captured by the vehicles C1, . . . The driver can be identified by matching the face with the front face image. Further, the driving characteristic server S1 repeats to each of the vehicles C1, . It can be executed repeatedly until

Further, as described above, when the driving characteristic server S1 according to Embodiment 1 determines that there is no front face image identical or similar to the front face images transmitted from the vehicles C1, . A new front face image is acquired, and it is determined again whether or not there is a front face image identical or similar to the new front face image among a plurality of registered front face images of the driver. If the driving characteristic server S1 determines that there is no right-facing facial image or left-facing facial image identical or similar to the right-facing facial image or left-facing facial image transmitted from the vehicles C1, . Acquiring a new right-facing face image or left-facing face image, and selecting a right-facing face image or left-facing face image identical or similar to the new right-facing face image or left-facing face image among a plurality of registered right-facing face images or left-facing face images of the driver It is determined again whether or not there is a face image. As a result, the driving characteristic server S1 according to the first embodiment can capture and transmit the right-facing face image or left-facing face image of the driver, which is captured by each of the vehicles C1, . . . The driver can be identified by matching the right-facing face images or left-facing face images of a plurality of drivers. Further, the driving characteristic server S1 performs a process of requesting transmission of the driver's right-facing face image or left-facing face image repeatedly to each of the vehicles C1, . . . can be repeatedly executed until the driver is identified. Furthermore, the driving characteristic server S1 according to Embodiment 1 performs not only face matching using a front face image, but also face matching using a right-facing face image or a left-facing face image, thereby making it possible to spoofing can be suppressed more effectively.

As described above, the car navigation device 10 according to the first embodiment is an on-vehicle device mounted on the vehicle C1, . (an example of a communication unit), an in-vehicle camera 13 (an example of a first acquisition unit) that acquires biological information of a driver who drives a vehicle C1, . 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 links and outputs biological information and driving characteristic data. The processor 12A outputs the linked biological information and the driving characteristic data to the communication device 11 and causes it to be transmitted to the driving characteristic server S1. The various sensors referred to here are, 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 exterior sensor/camera 19, the GPS sensor 20, etc. (see FIG. 2). .

As a result, the car navigation device 10 according to Embodiment 1 acquires the biological information for identifying the driver and the driving characteristic data used for driving evaluation, and stores the acquired biological information and the driving characteristic data. Since it is linked and transmitted to the driving characteristic server S1, it is possible to support the management of the driving characteristic data for each driver by the driving characteristic server S1 so that it can be collected and managed (recorded) more effectively.

As described above, the car navigation device 10 according to Embodiment 1 further includes a memory 12B (an example of a recording unit) that records vehicle IDs (an example of vehicle identification information) that can identify the vehicles C1, . The processor 12A associates the acquired biological information, the driving characteristic data, and the vehicle ID, outputs them to the communication device 11, and causes them to be transmitted to the driving characteristic server S1. As a result, the car navigation device 10 according to Embodiment 1 acquires the biological information for identifying the driver, the driving characteristic data used for driving evaluation, and the vehicle ID, and acquires the acquired biological information and driving. Since the characteristic data and the vehicle ID are linked to each other and transmitted to the driving characteristic server S1, even if one vehicle C1, . It is possible to support the management of each driving characteristic data to be collected and managed (recorded) more effectively.

As described above, the car navigation device 10 according to the first embodiment further includes the processor 12A (an example of the third acquisition unit) that acquires information on the driver getting on or off the vehicle C1. The processor 12A causes the in-vehicle camera 13 to start acquiring biological information and the acquisition of driving characteristic data by the gyro sensor 14 or various sensors from the timing when the driver's boarding information is acquired. As a result, the car navigation device 10 according to Embodiment 1 automatically performs the biometric information acquisition process and the driving characteristics from the timing when the driver's boarding information is acquired (that is, the timing when the driver's boarding is detected). Data acquisition process can be started. Therefore, since the car navigation device 10 can start acquiring the driving characteristic data without the driver's operation, it is possible to suppress the omission of acquiring the driving characteristic data due to the driver forgetting to start acquiring the driving characteristic data. .

As described above, the processor 12A in the car navigation device 10 according to the first embodiment acquires the biometric information by the in-vehicle camera 13 at the timing when the information on getting off the driver is acquired, and the driving characteristics by the gyro sensor 14 or various sensors. Terminate data acquisition. As a result, the car navigation device 10 according to Embodiment 1 automatically performs the biometric information acquisition process and the driving process at the timing when the driver's exit information is acquired (that is, at the timing when the driver's exit is detected). Acquisition processing of characteristic data can be ended.

As described above, the in-vehicle camera 13 in the car navigation device 10 according to Embodiment 1 is a camera that captures the driver's face. The biological information is a facial image of the driver captured by the in-vehicle camera 13 . Thus, the car navigation device 10 according to Embodiment 1 can capture the face of the driver with the in-vehicle camera 13 even while the driver is driving, and acquire the captured image as biometric information.

As described above, the processor 12A in the car navigation device 10 according to the first embodiment can detect that the face image of the driver captured by the in-vehicle camera 13 is facing a predetermined direction (for example, front, right, left, etc.). ), the facial image and the driving characteristic data are linked, output to the communication device 11, and transmitted to the driving characteristic server S1. As a result, the car navigation device 10 according to Embodiment 1 can select a facial image, and can more effectively suppress an increase in the amount of data communication required to transmit 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 Embodiment 1 accepts from the driving characteristic server S1 the direction of the face of the driver shown in the face image. When the processor 12A determines that the face orientation of the driver reflected in the face image is the specified face orientation of the driver, the processor 12A associates the face image with the driving characteristic data and outputs the result to the communication device 11. , to the driving characteristic server S1. As a result, the car navigation device 10 according to Embodiment 1 can select a face image to be used for face matching, and can more effectively suppress an increase in the amount of data communication required to transmit the face image to the driving characteristic server S1. .

As described above, the car navigation device 10 according to Embodiment 1 further includes the input unit 12D or the in-vehicle camera 13 (an example of the fourth acquisition unit) for acquiring the license ID of the driver. The processor 12A associates the acquired biometric information, vehicle ID, and driver's license ID, outputs them to the communication device 11, and causes them to be transmitted to the driving characteristic server S1. As a result, the car navigation device 10 according to the first embodiment associates the driver's biometric information, which is the initial registration data necessary for the driver's initial registration process, the vehicle ID, and the driver's license ID, to determine the driving characteristics. It can be sent to server S1. Therefore, the driving characteristic server S1 can perform face matching of the driver based on the driver's license ID transmitted from the car navigation device 10 of the vehicle C1, . In this case, the initial registration can be completed by linking the biometric information of the driver, the vehicle ID, and the driver's license ID and registering (storing) them in the driving characteristic table TB1. Further, after this initial registration process, if the driving characteristic server S1 determines that the biometric information transmitted from the same or another vehicle is the same or similar to the biometric information that has already been initially registered, the driving characteristic server S1 determines that the biometric information transmitted from the same or another vehicle The driver corresponding to the biometric information can be identified as the driver corresponding to the driver's license ID linked to the biometric information determined to be the same or similar, and the driving characteristic data transmitted from the same or another vehicle can be identified. , by recording in association with the driver's license ID, it is possible to collect and manage (record) the driving characteristic data for each driver.

(Background leading up to Embodiment 2)
In recent years, driving a vehicle is effective in reducing the risk of dementia and extending healthy life expectancy among the elderly. It has been shown to help people maintain healthy social participation. Therefore, there is a demand for a technology that extends the driving life of elderly drivers by suppressing the increase in accidents caused by driving operation mistakes and forgetting to confirm safety as they age.

Japanese Unexamined Patent Application Publication No. 2002-200002 discloses a technique for assisting driving, based on the relationship between a predetermined road parameter of the road on which the vehicle travels and the steering angle. and warns the driver when it is determined that safety confirmation has not been performed. Further, in Patent Document 3, a driving assistance device that assists a driver in driving learns the driving proficiency level of the driver based on the history of the driving operation of the driver, and adjusts the driving assistance level based on the driving proficiency level. Provide driving assistance as necessary. However, it is desirable for such a driving assistance device to perform dynamic driving assistance corresponding to the driving situation and the state of the driver.

In addition, the driving support device that assists the driver in driving by automatic driving disclosed in Patent Document 4 is based on the environmental difficulty level required for the driver's driving operation due to the external environment of the vehicle and the driver's driving operation. Based on the driving skill and the driver's state of the driver in relation to the external environment, based on the driving skill and the driver's state (e.g., emotion, psychology, etc.), driving assistance content (e.g., automatic steering, automatic braking, etc.) Select and execute. However, driving assistance by automatic driving cannot assist the improvement of the driver's own driving characteristics (driving skill, safety confirmation, etc.).

Therefore, in the second embodiment 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 addition, in the following description, the same reference numerals are used for the same components as those in the first embodiment, and the description thereof will be omitted.

It should be noted that the driving characteristic data in the second embodiment will be described as an example including data indicating the driving characteristics of the driver and data indicating behavioral characteristics (for example, motion 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 action performed by the driver.

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

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

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

The driving characteristic data in Embodiment 2 is data indicating the driving characteristic of the driver, and is obtained from various sensors (for example, the in-vehicle camera 13A, the gyro sensor 14, the accelerator pedal 17A, the brake It 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 the driving characteristic data of the drivers of the vehicles C1A, . . . Based on data (hereinafter referred to as "emotional data") indicating a person's reaction (for example, driver's emotion, facial expression, heartbeat, etc.) and driving scene information indicating the driving scene in which the driving characteristics are acquired, the driving is performed. This is data for determining a support method for improving characteristics.

In addition, the driving scene here means not only any scene during driving (for example, lane change, right/left turn, forward or backward, etc.), but also the scene before driving and the driver getting into the vehicle, after driving, or Scenes before and after driving, such as scenes in which the driver or a fellow passenger exits the vehicle during a temporary stop, including scenes that require safety confirmation. In addition, the driving scene includes the road environment (eg, T-junction, crossroads, downhill, etc.), road conditions (eg, traffic congestion, etc.), and environmental information of the road during driving (eg, time of day, weather, etc.). , based on the number and frequency of accidents that have occurred on the road on which the vehicle is traveling, the degree of risk (score) based on the likelihood of an accident occurring, or the importance of safety confirmation, etc., may be set in advance.

Further, in the driving scene, a threshold may be set for the frequency with which the safety confirmation action is performed corresponding to the degree of danger (score). In such a case, each of the vehicles C1A, . good.

Each of the vehicles C1A, . Note that the wireless communication here is, for example, a wireless LAN represented by Wi-Fi (registered trademark), a cellular communication system (mobile communication system), or the like, and the type thereof is not particularly limited.

Each of the vehicles C1A, . Acquisition of the driving characteristic data shown and determination (identification) of the driving scene are started. Each of the vehicles C1A, . Acquire driver emotion data for driving characteristic improvement assistance.

Each of the vehicles C1A, . Each of the vehicles C1A, . The data and the 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 characteristic has improved is stored in the driving characteristic learning device 23 . Each of the vehicles C1A, . Update data such as data. Based on the improvement effect data transmitted from the driving characteristic improvement server S3, each of the vehicles C1A, . Each of the vehicles C1A, .

Each of the vehicles C1A, . The driving characteristic data of the person is extracted and transmitted to the wireless terminal device P1A, or the driving characteristic evaluation results are generated by evaluating the driving characteristics 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, . The driving characteristic improvement server S3 acquires the user ID of the driver, the driving characteristic data, the emotion data, and the driving scene information transmitted from each of the vehicles C1A, .

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

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

In addition, the driving characteristic improvement server S3, based on the control command requesting the driver's driving characteristic data or driving characteristic evaluation result transmitted from the wireless terminal device P1A, determines whether the driver stored in the database 54 (see FIG. 20) 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, .

Next, with reference to FIG. 18, an internal configuration example of vehicles C1A, . . . according to the second embodiment will be described. FIG. 18 is a block diagram showing an internal configuration example of vehicles C1A, . . . according to the second embodiment. The internal configuration of vehicles C1A, . . . shown in FIG. is omitted. Since each of the vehicles C1A, . . . has the same internal configuration, the internal configuration of the vehicle C1A will be described below.

The vehicle C1A includes 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 unit inside the vehicle C1A is connected by CAN or the like so as to be able to transmit and receive data.

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

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 smart phone, or the like, and is a device capable of receiving operations by the driver. Also, the terminal device 22 may be an IVI device capable of providing, for example, a car navigation function, a location information providing service function, an Internet connection function, a multimedia reproduction 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, DSP, or FPGA, and controls the operation of each section. The processor 22A cooperates with the memory 22B to collectively perform various processes and controls. Specifically, the processor 22A refers to the programs and data held in the memory 22B, and executes the programs to implement the functions of the units.

The processor 22A starts acquisition processing of driving characteristics and behavioral characteristics (driving characteristic data) and determination processing of driving situations at the timing of acquiring a control command from the in-vehicle sensor 24 or the communication device 11A indicating that the approach of the driver has been detected. do. After identifying the driving situation, the processor 22A executes driving characteristic improvement assistance based on the improvement effect data corresponding to the driving situation information of this driving characteristic. The processor 22A starts various processes such as acquisition of the driver's driving characteristics, behavioral characteristics, and emotion data for the driving characteristics improvement assistance that has been executed.

The processor 22A, via the ECU 16A, various sensors (for example, the vehicle interior camera 13A, 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 vehicle exterior sensor/camera 19A, the vehicle interior sensor 24, etc.). ) to acquire various driving characteristic data acquired by

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 the captured images or information acquired by the vehicle interior camera 13A, vehicle exterior sensor/camera 19A, GPS sensor 20, vehicle interior sensor 24, or the like.

The processor 22A controls the speaker 25 or the warning indicator light 26 based on the driving scene information of the determined driving scene and the improvement effect data corresponding to this driving scene information to assist the driver in improving the driving characteristics. (safety confirmation action support).

The processor 22A acquires a captured image captured by the in-vehicle camera 13A, detects the face of the driver appearing in the acquired captured image, and performs driving characteristic improvement support before and after the driving characteristic improvement support based on the detected facial expression of the driver. Analyze the emotion of the driver and generate emotion data.

Further, the processor 22A acquires an image captured by the in-vehicle camera 13A or the exterior sensor/camera 19A, analyzes the movement of the driver's body and eyes reflected in the acquired image, and detects the movement of the driver based on the analysis result. and driving characteristics data obtained by various sensors.

The processor 22A associates the driving scene information in which the driving characteristic improvement assistance was executed, the driver's emotion data regarding the driving characteristic improvement assistance, the driving characteristic data acquired by various sensors, and the user ID of the driver. are stored in the memory 15A and output to the communication device 11A to be transmitted to the driving characteristic improvement server S3. Note that the processor 22A may further link the determination result as to whether or not the driver has performed the safety confirmation action based on the acquired action data and transmit it to the driving characteristic improvement server S3.

The processor 22A also acquires the driving scene information and the 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.

When the processor 22A determines that the driver has gotten off the vehicle or has left the vehicle, the processor 22A performs acquisition processing of the driving characteristic data of the driver, determination processing of the driving scene, processing of driving characteristic improvement support, or acquisition processing of emotion data. , etc., are terminated.

The memory 22B has, for example, a RAM as a work memory used when executing each process of the processor 22A, and a ROM for storing programs and data defining the operation of the processor 22A. The RAM temporarily stores data or information generated or acquired by the processor 22A. 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 unit 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) and the like generated by the processor 22A.

The input unit 22D is a user interface configured integrally with the display unit 22C. The input unit 22D converts the received driver's operation into an electric signal (control command) and outputs it to the processor 22A. The input unit 22D receives a user ID input operation by the driver, an input operation requesting generation of a driving characteristic evaluation screen, a setting for enabling/disabling 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 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 action characteristic data indicating the movement of the driver's face, eyes or body. The processor 22A compares the generated behavioral characteristic data with one or more safe driving behaviors corresponding to the driving scene to determine whether the driver has performed a safety confirmation behavior that should be performed in the current driving scene. judge. It should be noted that the process of analyzing the driver's behavior characteristic data 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 performed by the processor 52 of the driving characteristic improvement server S3. may be performed by

In addition, 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 emotion of the driver, and generates emotion data. The emotion data generation process may be executed by the processor 52 of the driving characteristic improvement server S3.

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

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

In addition, the ECU 16A detects the approach of the driver to the own vehicle or the departure of the driver from the own vehicle (that is, the end of driving) based on the electric signal output from the in-vehicle sensor 24, and the detected Detected information is output to processor 22A. Although not described here, the ECU 16A may be capable of implementing various functions executed by the processor 22A, such as various processes necessary for driving characteristic improvement assistance and evaluation of driving characteristics of the driver.

The vehicle exterior sensor/camera 19A is one or more sensors such as radar and sonar installed in the vehicle C1A, and one or more cameras capable of imaging the surroundings (outside the vehicle) of the vehicle C1A. The camera referred to here may be a drive recorder. The sensor/camera 19A outside the vehicle detects the position of an object (for example, a wall, an obstacle, another vehicle, a person, etc.) existing around the vehicle C1A or an approaching object (for example, another vehicle, a motorcycle, a person, etc.). Also, the direction, signs, white lines on the road, the driver or fellow passenger getting off and away from the own vehicle, the driver or fellow passenger approaching and getting into the own vehicle, etc. are detected or imaged. The vehicle exterior sensor/camera 19A outputs the detected detection information or the captured image to the processor 22A.

The driving characteristic learning device 23 records the driving characteristic learning model and the 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 scene using the driving scene data recorded in the driving characteristic learning device 23 and the information acquired by various sensors, and generates the driving scene data indicating the driving scene of the vehicle C1A, . do.

The in-vehicle sensor 24 includes, for example, a sensor capable of receiving radio waves transmitted from a smart key of the vehicle, an open/close sensor provided at a door corresponding to each seat, a weight sensor provided at each seat, a seat belt wearing sensor, and the like. is. When the in-vehicle sensor 24 receives radio waves transmitted from the smart key, it generates an electric signal (control command) that notifies the driver of the approach and outputs it to the ECU 16A. When the in-vehicle sensor 24 cannot receive radio waves transmitted from the smart key, it generates an electric signal (control command) notifying that the driver has left the vehicle and outputs it to the ECU 16A. Further, the in-vehicle sensor 24 outputs to the ECU 16A detection information such as movement of the driver's body (weight), attachment/detachment of the seat belt, opening and closing of the driver's door, etc., by a weight sensor provided in the driver's seat.

At least one speaker 25 as an example of a safe driving support device is provided in each of the vehicles C1A, . Execute characteristic improvement support. As for the installation position and the number of the speakers 25 in the vehicles C1A, ... according to the second embodiment, an example in which two each are installed in the front and the rear of the vehicle as shown in FIG. 28 will be described. Needless to say, it is not limited to this. Moreover, the speaker 25 may be installed outside the vehicle as well as inside the vehicle.

The warning indicator light 26, which is an example of a safe driving support device, is an LED (Light Emitting Diode) provided on a pillar or the like in the vehicle, for example, and is controlled by the processor 22A or the ECU 16A to light up corresponding to the driving situation. , to perform driving characteristic improvement support for the driver. Needless to say, the installation positions and the number of warning indicator lamps 26 in vehicles C1A, . . . according to the second embodiment are not limited to the example shown in FIG. Also, 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, the driving characteristic history table TB3 recorded by each of the vehicles C1A, . . . will be described with reference to FIG. FIG. 19 is a diagram showing an example of the driving characteristic history table TB3. In the following description, the driving characteristic history table TB3 is used to describe various data or information recorded by each of the vehicles C1A, . , 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 the 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. , driving situation information "△△△", driving characteristic data, and improvement effect data are linked, and driving situation information "XXX", driving characteristic data, and improvement effect data are linked to the user ID "BBB". are linked and recorded respectively. As a result, the driving characteristic history table TB3 can be used even when the same vehicle is driven by a plurality of different drivers (for example, each of two users "AAA" and "BBB"). Driving characteristic data and improvement effect data can be recorded (managed) more efficiently for each person ID.

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

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

The communication unit 51 is connected to each of the vehicles C1A, .

The processor 52 is configured using, for example, a CPU, DSP, or FPGA, and controls the operation of each section. The processor 52 cooperates with the memory 53 to collectively perform various processes and controls. Specifically, the processor 52 refers to the programs and data held in the memory 53 and executes the programs, thereby implementing the functions of the support method generator 52A and the like. When the driving characteristic learning model or the driving scene data is updated, the processor 52 transmits the updated driving characteristic learning model or the driving scene data to each of the vehicles C1A, .

In addition, the processor 52 uses the driving characteristic data corresponding to each driving scene information transmitted from each of the vehicles C1A, . may be generated. The processor 52 generates teaching data used for generating an improvement effect learning model based on machine learning using driver emotion data for driving characteristic improvement assistance based on each improvement effect data transmitted from each of the vehicles C1A, . . . (learning data) may be generated.

Training to generate training data may be performed using one or more statistical classification techniques. Statistical classification techniques include, for example, multiple regression analysis, linear classifiers, support vector machines, quadratic classifiers, kernel estimation, decision trees ( Decision Trees, Artificial Neural Networks, Bayesian Techniques and/or Networks, Hidden Markov Models, Binary Classifiers , a multiclass classifier ( Multi-Class Classifiers, Clustering Technique, Random Forest Technique, Logistic Regression Technique, Linear Regression Technique, Gradient boosting (Gradient Boosting Technique) and the like. However, the statistical classification techniques used are not limited to these.

The support method generation unit 52A acquires the driving characteristic data, the driving scene information, the emotion data, and the user ID transmitted from each of the vehicles C1A, . The support method generation unit 52A collates the acquired user ID with each of the plurality of user IDs registered (stored) in the user database DB1 to identify the driver. If the support method generation unit 52A determines that the user ID identical to the acquired user ID is not registered in the user database DB1, the acquired user ID is used as a new user. It may be registered (stored) in the person database DB1.

Based on the acquired driving scene information, the support method generation unit 52A determines whether or not the driving scene requires safe driving and the degree of risk (score) corresponding to the driving scene is equal to or greater than a predetermined value. judge. Further, the support method generation unit 52A determines whether or not the driver is performing a safety confirmation action corresponding to the driving scene based on the action 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 emotion 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 obtained 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 driving characteristics of the driver have improved based on the acquired driving characteristics and the driving characteristics of the driver registered in the driving characteristics database DB3. The support method generation unit 52A determines the driving characteristic improvement method after the change based on the determination result as to whether the driving characteristic is improved and the acquired emotion data. The support method generation unit 52A generates improvement effect data indicating the driving characteristic improvement method after the change, and transmits the improvement effect data to the vehicles C1A, .

On the other hand, when the support method generation unit 52A determines that the driving characteristic improvement method does not need to be changed, the generation and update processing of new improvement effect data are omitted, and the acquired driving scene information is stored 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 has, for example, a RAM as a work memory that is used when executing each process of the processor 52, and a ROM that stores programs and data that define the operation of the processor 52. FIG. Data or information generated or obtained 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 situation database DB2, a driving characteristic database DB3, and an improvement effect database DB4. Each of the user database DB1, the driving scene database DB2, the driving characteristic database DB3, and the improvement effect database DB4 stores a set of data (user ID, driving scene information, driving scene information) transmitted from each of the vehicles C1A, . and the improvement effect data corresponding to the driving scene information) are recorded in a state of being associated with each other. The user database DB1, the driving scene database DB2, the driving characteristic database DB3, and the improvement effect database DB4 each store the acquired date and time information acquired from each of the vehicles C1A, . A set of data transmitted from each of C1A, . . . may be linked.

The user database DB1 registers (stores) user IDs 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 obtained from each of the plurality of vehicles C1A, . . . for each driving scene 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. The improvement effect database DB4 may register (store) the changed driving improvement data when the changed driving improvement data is generated. Further, when new improvement effect data is generated by the vehicles C1A, . Update to effective improvement data.

Next, the driving characteristic improvement management table TB4 recorded by each of the vehicles C1A, . . . will be described with reference to FIG. FIG. 19 is a diagram showing an example of the driving characteristic improvement management table TB4. In the following description, in order to facilitate understanding, 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) is stored using the driving characteristic improvement management table TB4. respectively), the driving characteristic improvement management table TB4 is not essential and may be omitted.

The driving characteristic improvement management table TB4 associates driving characteristic data corresponding to the driving scene information with the driving scene information and improvement effect data corresponding to the driving scene information, and records and manages them 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 linking the driving characteristic data and the improvement effect data to the driving situation information "XXX". The driving characteristic improvement management table TB4 records the driving situation information "XXX" of the user ID "BBB" in association with the driving characteristic data and the improvement effect data, and records the driving situation information "XXX" of the user ID "CCC". The driving characteristic data and the 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 vehicle C1A, . FIG. 22 is a diagram for explaining an example of safety confirmation behavior when turning left. Note that the example of confirming safe behavior shown in FIG. 22 is merely an example, and needless to say, the present invention is not limited to this. Further, in FIG. 22, an example in which the vehicle C1A determines whether or not the safety confirmation action is being performed will be described as an example. may be

FIG. 22 is a diagram showing the vehicle C1A in the driving scene "when turning left", showing the vehicle C1A immediately before turning left in the traveling direction D1 and the state inside the vehicle C1A at that time. In addition, each process performed by the terminal device 22 demonstrated henceforth may be performed by ECU16A.

The terminal device 22 shown in FIG. 22 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 "when turning left". For example, the terminal device 22 receives driving scene data, an image of the surroundings of the vehicle C1A captured by an external sensor/camera 19A, an accelerator pedal 17A, a brake pedal 17B, a turn lamp 17C, or a steering wheel 17D. Various information related to the driver's driving operation, destination (destination) information preset in the terminal device 22, current position information of the vehicle C1A acquired by the GPS sensor 20, etc. are used to determine the vehicle C1A is determined to be "when turning left".

The terminal device 22 associates the user ID corresponding to the 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 generates 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 for controlling the speaker 25 or the warning indicator light 26 based on the improvement effect data referred to, and outputs the command to the speaker 25 or the warning indicator light 26, respectively. When the terminal device 22 determines that the driving characteristic improvement support is unnecessary based on the improvement effect data referred to, the terminal device 22 omits the control of the speaker 25 or the warning indicator lamp 26 described above.

In addition, 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 situation information "when turning left" of the vehicle C1A. The terminal device 22 determines whether or not the driver has performed a safety confirmation action corresponding to the driving situation information, based on information on one or more safety confirmation actions and behavior characteristic data of the driver acquired by various sensors. determine whether In the example shown in FIG. 22, the vehicle C1A determines whether or not the driver has performed each of the 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 perform driving characteristic improvement support that prompts the driver to visually check the rear of the vehicle C1A through the rearview mirror RM, and also outputs from the in-vehicle camera 13A Based on the captured image, it is determined whether or not the movement of the driver's face or line of sight is directed in the direction AC11 (that is, whether or not the driver visually confirms the rear of the vehicle C1A through the rearview mirror RM) (1 second judgment).

In addition, the terminal device 22 controls the speaker 25 or the warning indicator lamp 26, and assists in driving characteristic improvement by prompting the driver to visually check the left side and the left rear of the vehicle C1A through the left side mirror SM1 corresponding to the traveling direction D1. Along with execution, based on the imaged image output from the in-vehicle camera 13A, it is determined whether or not the movement of the driver's face or line of sight is directed in the direction AC12 (that is, whether the driver is looking through the left side mirror SM1 corresponding to the traveling direction D1). (second determination).

In addition, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to perform driving characteristic improvement support that prompts the driver to visually check the rear of the vehicle C1A, and based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether or not the movement of the driver's body, face, or line of sight is directed in the direction AC13 (that is, whether or not the driver visually confirms the rear of the vehicle C1A) (third determination).

In the case where execution determination is made for each of two or more safety confirmation actions, and the order of determination is set in advance for each of these safety confirmation actions, the terminal device 22 executes each safety confirmation action. Along with the determination, it may be determined whether or not each safety confirmation action has been performed in the set order.

The terminal device 22 detects the emotion of the driver based on the captured image captured by the in-vehicle camera 13A from the timing when the driving characteristic improvement support is started to the timing when the execution determination processing for each of the three safety confirmation actions is completed. to parse The terminal device 22 generates emotion data based on the analysis result. Note that the terminal device 22 may generate emotion data for each driving characteristic improvement assistance corresponding to each safety confirmation action, or may generate emotion data for each driving characteristic improvement assistance executed in the driving scene “when turning left”. may generate one emotion data.

The terminal device 22 acquires 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 to the timing when the execution judgment of each of the three safety confirmation actions is completed. and the emotion data corresponding to the driving characteristic improvement support are respectively generated, linked to the user ID, recorded in the memory 15A, and transmitted to the driving characteristic improvement server S3. to record it in the database 54.

With reference to FIG. 23, a specific example of the process of determining whether or not the vehicle C1A, . FIG. 23 is a diagram for explaining an example of safety confirmation behavior when turning right. Note that the example of confirming safe behavior shown in FIG. 23 is an example, and needless to say, the present invention is not limited to this. Further, in FIG. 23, an example in which the vehicle C1A determines whether or not the safety confirmation action is being performed will be described as an example. may be

FIG. 23 is a diagram showing the vehicle C1A in the driving scene "when turning right", showing the vehicle C1A immediately before turning right in the traveling direction D2 and the state inside 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 "when turning right".

The terminal device 22 associates the user ID corresponding to the driver stored in the driving characteristic history table TB3 based on the determined driving scene information "when turning right" of the vehicle C1A, and the driving scene information. The improvement effect data (that is, the driving characteristic improvement support method) corresponding to "when turning right" is referred to. The terminal device 22 generates a control command for controlling the speaker 25 or the warning indicator light 26 based on the improvement effect data referred to, and outputs the command to the speaker 25 or the warning indicator light 26, respectively. When the terminal device 22 determines that the driving characteristic improvement support is unnecessary based on the improvement effect data referred to, the terminal device 22 omits the control of the speaker 25 or the warning indicator lamp 26 described above.

In addition, 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 situation information "when turning right" of the vehicle C1A. The terminal device 22 determines whether or not the driver has performed a safety confirmation action corresponding to the driving situation information, based on information on one or more safety confirmation actions and behavior 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 or not the driver has performed each of the three safety confirmation actions corresponding to the driving scene information "when turning right".

For example, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to perform driving characteristic improvement support that prompts the driver to visually check the rear of the vehicle C1A through the rearview mirror RM, and also outputs from the in-vehicle camera 13A Based on the captured image, it is determined whether or not the movement of the driver's face or line of sight is directed in the direction AC21 (that is, whether or not the driver visually confirms the rear of the vehicle C1A through the rearview mirror RM) (1 second judgment).

In addition, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to assist the driver in improving driving characteristics by urging the driver to visually check the right side and the right rear of the vehicle C1A through the right side mirror SM2 corresponding to the direction of travel D2. Along with execution, based on the captured image output from the in-vehicle camera 13A, it is determined whether or not the movement of the driver's face or line of sight is directed in the direction AC22 (that is, whether or not the driver is looking through the right side mirror SM2 corresponding to the traveling direction D2). (second determination).

In addition, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to perform driving characteristic improvement support that prompts the driver to visually check the rear of the vehicle C1A, and based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether or not the movement of the driver's body, face, or line of sight is directed in the direction AC23 (that is, whether or not the driver visually confirms the rear of the vehicle C1A) (third determination). As shown in FIG. 23, when vehicle C1A has a driver's seat on the right side (that is, a right-steering vehicle), the driver's right side and right rear of vehicle C1A are blocked by the driver's door. In such a case, the terminal device 22 determines whether or not the driver's head turns toward the right side of the vehicle C1A by 90° or more from the direction of travel D2 based on the driver's behavior characteristic data. may be used to determine whether or not the driver has visually confirmed the area behind the vehicle C1A.

The terminal device 22 detects the emotion of the driver based on the captured image captured by the in-vehicle camera 13A from the timing when the driving characteristic improvement support is started to the timing when the execution determination processing for each of the three safety confirmation actions is completed. to parse The terminal device 22 generates emotion data based on the analysis result. The terminal device 22 acquires 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 to the timing when the execution judgment of each of the three safety confirmation actions is completed. and the emotion data corresponding to the driving characteristic improvement support are respectively generated, linked to the user ID, recorded in the memory 15A, and transmitted to the driving characteristic improvement server S3. to record it in the database 54.

With reference to FIG. 24, a specific example of the process of determining whether or not the vehicle C1A, . FIG. 24 is a diagram for explaining an example of safety confirmation behavior when backing up. Note that the example of confirming safe behavior shown in FIG. 24 is an example, and needless to say, the present invention is not limited to this. Further, in FIG. 24, an example in which the vehicle C1A determines whether or not the safety confirmation action is being performed will be described as an example. may be

FIG. 24 is a diagram showing the vehicle C1A in the "reversing" driving scene, showing the vehicle C1A immediately before it reverses in the traveling direction D3 and the state inside 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 associates the user ID corresponding to the driver stored in the driving characteristic history table TB3 based on the determined driving scene information "reversing" of the vehicle C1A, and sets the driving scene information. Refer to the improvement effect data (that is, driving characteristic improvement support method) corresponding to "reversing". The terminal device 22 generates a control command for controlling the speaker 25 or the warning indicator light 26 based on the improvement effect data referred to, and outputs the command to the speaker 25 or the warning indicator light 26, respectively. When the terminal device 22 determines that the driving characteristic improvement support is unnecessary based on the improvement effect data referred to, the terminal device 22 omits the control of the speaker 25 or the warning indicator lamp 26 described above.

In addition, 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 situation information "reversing" of the vehicle C1A. The terminal device 22 determines whether or not the driver has performed a safety confirmation action corresponding to the driving situation information, based on information on one or more safety confirmation actions and behavior characteristic data of the driver acquired by various sensors. determine whether In the example shown in FIG. 24, an example will be described in which the driver of vehicle C1A determines whether or not each of the three safety confirmation actions corresponding to the driving situation information "reversing" has been performed.

For example, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to perform driving characteristic improvement support that prompts the driver to visually check the rear of the vehicle C1A through the rearview mirror RM, and also outputs from the in-vehicle camera 13A Based on the captured image, it is determined whether or not the movement of the driver's face or line of sight is directed in the direction AC31 (that is, whether or not the driver visually confirms the rear of the vehicle C1A through the rearview mirror RM) (1 second judgment).

In addition, the terminal device 22 controls the speaker 25 or the warning indicator light 26, and assists the driver in improving driving characteristics by urging the driver to visually check the right side and the right rear of the vehicle C1A through the right side mirror SM2 corresponding to the traveling direction D3. Along with executing this, based on the captured image output from the in-vehicle camera 13A, it is determined whether or not the movement of the driver's face or line of sight is directed in the direction AC32 (that is, whether or not the driver is looking through the right side mirror SM2 corresponding to the traveling direction D3). (second determination).

In addition, the terminal device 22 controls the speaker 25 or the warning indicator light 26 to perform driving characteristic improvement support that prompts the driver to visually check the rear of the vehicle C1A, and based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether or not the movement of the driver's body, face or line of sight is directed in the direction AC33 (that is, whether or not the driver visually confirms the rear of the vehicle C1A) (third determination). When the seatbelt wearing sensor, which is an example of the in-vehicle sensor 24, detects that the driver has unfastened the seatbelt while checking the rear, the terminal device 22 determines whether the seatbelt has been put on again after the rear is checked. It may also be possible to determine whether or not the driver is in the seat belt, or to execute driving characteristic improvement support that prompts the driver to refasten the seatbelt. It should be noted that the determination as to whether or not the driver has visually confirmed the rear of the vehicle is made based on the captured image captured by the back monitor (an example of the sensor/camera 19A outside the vehicle) that captures the rear of the vehicle. Alternatively, a surround view monitor (360° camera video, top view image, etc.) that is an overhead view of the own vehicle based on a plurality of captured images acquired using a plurality of exterior sensors/cameras 19A. may be generated and executed based on the generated surround view monitor or the like.

The terminal device 22 detects the emotion of the driver based on the captured image captured by the in-vehicle camera 13A from the timing when the driving characteristic improvement support is started to the timing when the execution determination processing for each of the three safety confirmation actions is completed. to parse The terminal device 22 generates emotion data based on the analysis result. The terminal device 22 acquires 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 to the timing when the execution judgment of each of the three safety confirmation actions is completed. and the emotion data corresponding to the driving characteristic improvement support are respectively generated, linked to the user ID, recorded in the memory 15A, and transmitted to the driving characteristic improvement server S3. to record it in the database 54.

With reference to FIG. 25, a specific example of the process of determining whether or not the vehicle C1A, . FIG. 25 is a diagram for explaining an example of safety confirmation behavior when driving forward on a long-distance straight road. Note that the example of confirming safe behavior shown in FIG. 25 is an example, and needless to say, the present invention is not limited to this. Further, in FIG. 25, an example in which the vehicle C1A determines whether or not the safety confirmation action is being performed will be described as an example. may be

FIG. 25 is a diagram showing the vehicle C1A in the driving scene "driving forward on a long-distance straight road", 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 whether the driving scene of the vehicle C1A is "driving forward on a long-distance straight road". Determine that there is.

The terminal device 22 associates the user ID corresponding to the driver stored in the driving characteristics history table TB3 based on the determined driving situation information of the vehicle C1A "driving 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 situation information "driving forward on a long straight road" is referred to. The terminal device 22 generates a control command for controlling the speaker 25 or the warning indicator light 26 based on the improvement effect data referred to, and outputs the command to the speaker 25 or the warning indicator light 26, respectively. When the terminal device 22 determines that the driving characteristic improvement support is unnecessary based on the improvement effect data referred to, the terminal device 22 omits the control of the speaker 25 or the warning indicator lamp 26 described above.

Further, the terminal device 22 refers to the information of one or more safety confirmation actions to be executed by the driver, corresponding to the determined driving situation information of the vehicle C1A "driving forward on a long-distance straight road". The terminal device 22 determines whether or not the driver has performed a safety confirmation action corresponding to the driving situation information, based on information on one or more safety confirmation actions and behavior characteristic data of the driver acquired by various sensors. determine whether In the example shown in FIG. 25, the vehicle C1A determines whether or not the driver has performed one safety confirmation action corresponding to the driving situation information "driving 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 perform driving characteristic improvement assistance that prompts the driver to visually check the rear of the vehicle C1A, and based on the captured image output from the in-vehicle camera 13A. Then, it is determined whether or not the movement of the driver's body, face, or line of sight is directed in the direction AC41 (that is, whether or not the driver visually confirms the rear of the vehicle C1A).

Note that when one driving scene continues for a first predetermined time or a first travel distance or more, as in the driving scene information "driving forward on a long-distance straight road" shown in FIG. may be repeatedly performed periodically (for example, every predetermined time, every predetermined distance).

The terminal device 22 analyzes the emotion of the driver based on the captured images captured by the in-vehicle camera 13A from the timing when the driving characteristic improvement support is started to the timing when the safety confirmation action execution determination process is finished. The terminal device 22 generates emotion data based on the analysis result. The terminal device 22 acquires the driving characteristic data, the driving scene information, and the determination of each of the three safety confirmation actions from the timing when the judgment of the driving situation is started to the timing when the execution judgment of the safety confirmation action is finished. Safety confirmation action data indicating the result and emotion data corresponding to the driving characteristic improvement support are generated respectively, linked to the user ID and recorded in the memory 15A, transmitted to the driving characteristic improvement server S3, and stored in the database 54. to record.

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

The safety confirmation behavior table TB5 shown in FIG. 26 is a table that associates driving scene information, safety confirmation behavior that should be executed by the driver, and examples of sensors that sense the safety confirmation behavior, corresponding to the driving scene information. Note that the safety confirmation behavior table TB5 is a table for making it easy to understand the explanation of examples of the driver's safety confirmation behavior sensed for each driving scene, and is not essential and may be omitted.

For example, in the safety confirmation action table TB5 shown in FIG. 26, the terminal device 22 uses the in-vehicle sensor 24 through wireless communication such as Bluetooth (registered trademark) to detect radio waves transmitted from the smart key or smart phone of the vehicle possessed by the driver. is received, and it is determined that the approach of the driver 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. I judge. When the terminal device 22 determines that the driving scene is "before getting into the vehicle", the sensor/camera 19A outside the vehicle detects the presence or absence of an obstacle in the forward or backward direction of the vehicle (that is, the front-rear direction of the vehicle), Safety confirmation by visually confirming the presence or absence of contact by opening and closing the door of at least one seat of the own vehicle by the in-vehicle sensor 24 (for example, a door open/close sensor that detects whether each door is open or closed) Determine whether the action is being executed.

Based on the information acquired by various sensors such as the in-vehicle camera 13A and the in-vehicle sensor 24 (door open/close sensor) and the driving scene data recorded in the driving characteristic learning device 23, the driving scene is determined as "before getting out of the vehicle. , the terminal device 22 detects the forward or backward direction of the vehicle (i.e., the front-rear direction of the vehicle) using the vehicle interior camera 13A, vehicle exterior sensor/camera 19A, vehicle interior sensor 24 (door open/close sensor), etc. presence or absence of an obstacle in the vehicle, presence or absence of a contact due to the opening and closing of the door of at least one seat of the vehicle by the in-vehicle sensor 24 (for example, a door open/close sensor that detects whether each door is open or closed), etc. It is determined whether or not the safety confirmation action of visually confirming is being performed.

In addition, based on the information obtained by various sensors such as the in-vehicle camera 13A and the in-vehicle sensor 24 (door open/close sensor) and the driving scene data recorded in the driving characteristic learning device 23, the driving scene is determined as follows: When the terminal device 22 judges that it is "before getting off the car", the terminal device 22 detects the forward direction or the backward direction of the own vehicle (that is, the the presence or absence of an obstacle in the front-rear direction), and at least one seat in the own vehicle (for example, a sensor that detects whether the door is open or closed) detected by an in-vehicle sensor 24 (for example, a door open/close sensor that detects whether each door is open or closed) It is determined whether or not the safety confirmation action of visually confirming the presence or absence of contact by opening and closing the door of the passenger's seat) is being performed.

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 vehicle interior camera 13A, the vehicle exterior sensor/camera 19A, etc. to determine whether the vehicle is moving forward or backward (i.e., in the longitudinal direction of the vehicle), or whether the vehicle is approaching from the surroundings. It is determined whether or not a safety confirmation action of visually confirming the presence or absence of objects (for example, pedestrians, other vehicles, two-wheeled vehicles, etc.) is being executed.

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 braking". If the terminal device 22 determines that the It is determined whether or not the safety confirmation action of visually confirming the presence or absence is being executed.

Based on the information acquired by various sensors such as the in-vehicle camera 13A, 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 determined to be "before changing lanes." If the terminal device 22 determines that the A judgment is made as to whether or not the safety confirmation action of visually confirming the presence or absence of a two-wheeled vehicle, etc., is being performed.

Further, when it is determined that the driving scene is "when going 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 visually confirms the presence or absence of objects (for example, pedestrians, other vehicles, two-wheeled vehicles, etc.) approaching from behind the own vehicle or from the surroundings of the own vehicle using the in-vehicle camera 13A, the outside sensor/camera 19A, and the like. Determine whether confirmation action is being performed.

Further, 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 "before making a left or right turn", the terminal device 22 detects objects (for example, pedestrians , other vehicles, motorcycles, etc.) is being executed.

Based on the information acquired by various sensors such as the in-vehicle camera 13A, the accelerator pedal 17A, the brake pedal 17B, etc., 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 an obstacle, the terminal device 22 detects the obstacle in the forward or backward direction of the vehicle (i.e., the front-rear direction of the vehicle) using the vehicle interior camera 13A, vehicle exterior sensor/camera 19A, vehicle interior sensor 24 (door open/close sensor), etc. Determining whether or not a safety confirmation action is being performed to visually confirm the presence of objects, the presence of contact objects by opening and closing the door of at least one seat of the vehicle (for example, the seat of a passenger getting off the vehicle). do.

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

It goes without saying that the arrangement position of each of the two warning indicator lamps 26A and 26B shown in FIG. 27 is an example and is not limited to this. Also, in the example shown in FIG. 27, two warning indicator lights 26A and 26B are mounted, respectively, but the number of warning indicator lights mounted on each of the vehicles C1A, . . . may be three or more.

For example, the warning indicator light 26 may be provided on any of the B-pillar, C-pillar, D-pillar, etc. of the vehicle C1A. The B pillars referred to here are a pair of pillars provided in the central portion of the vehicle body of the vehicle C1A between the driver's seat, the front passenger's seat, and the second seat. Further, the C-pillars are a pair of pillars provided in the central portion of the vehicle body provided in the rear portion of the vehicle body of the vehicle C1A, . . . between the second seat and the third seat. The D pillars are a pair of pillars provided behind the second seat or the third seat and behind 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 windshields of the vehicles C1A, . Each of the warning indicator lamps 26A and 26B lights, blinks, or goes out in a predetermined color (eg, yellow, orange, red, etc.) based on a control command from the terminal device 22 or the ECU 16A.

The terminal device 22 may light or flash the warning indicator light 26 in different colors based on the degree of danger (score) of the driving scene 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 risk of the driving scene is high, the warning indicator light 26 may blink in red, and if it determines that the risk of the driving scene is not high, The warning indicator light 26 may flash orange at longer intervals.

Further, for example, when the terminal device 22 supports the driver's visual confirmation of the rear of the vehicle C1A, . Execute. Further, when the terminal device 22 supports the driver's visual confirmation of the rear side of the vehicle C1A, . . As a result, 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) corresponding to the driving situation by turning on or blinking the warning indicator light 26B. .

Further, for example, when the terminal device 22 detects a pedestrian, another vehicle, a two-wheeled vehicle, or the like on the left side or right side of the vehicle C1A, the terminal device 22 executes driving characteristic improvement support that prompts the driver to visually confirm the right side of the vehicle C1A. . Specifically, the terminal device 22 lights or blinks warning indicator lights 26A and 26B arranged on the left side or right side of the detected pedestrian, other vehicle, motorcycle, etc. in a predetermined color to support driving characteristic improvement. to run.

In addition, for example, the terminal device 22 can detect the distance between the vehicle and the detected pedestrian, other vehicle, two-wheeled vehicle, etc., the approach speed between the pedestrian, other vehicle, two-wheeled vehicle, etc. approaching the vehicle, and the like. 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 flashing pattern of the warning indicator light 26A or 26B in accordance with the degree of danger of the driving scene. , blink rate, etc.

Specifically, when the terminal device 22 determines that the vehicle does not need to be operated such as decelerating 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 is flashed in orange, or when it is determined that the vehicle does not require driving operations such as deceleration or stopping, the warning indicator lamp 26A or 26B is flashed in red at shorter intervals. As a result, the driver can intuitively grasp the importance of the safety confirmation action at a glance based on the color, blinking pattern, blinking speed, etc. of the warning indicator light 26A or 26B.

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

In the example shown in FIG. 28, four speakers 25A, 25B, 25C, and 25D are mounted inside vehicles C1A, . The speaker 25A is mounted on the dashboard DSB of each of the vehicles C1A, . . . near the left A-pillar or the left side mirror SM1. The speaker 25B is mounted on the dashboard DSB of each of the vehicles 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. It goes without saying that the arrangement position of each of the four speakers 25A, 25B, 25C, and 25D shown in FIG. 28 is an example, and the present invention is not limited to this.

When an object approaching the vehicle (for example, a pedestrian, another vehicle, a two-wheeled vehicle, etc.) or an obstacle around the vehicle is detected by 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 caused to output a sound indicating that the approaching object or obstacle has been detected.

For example, the terminal device 22 operates in the driving scene "at the time of changing lanes" in which the vehicle is currently traveling in a lane changing to a lane on the right side in the direction of travel. Other vehicles approaching from the rear right side of the own vehicle are detected by various sensors such as. In such a case, the terminal device 22 outputs a sound from the speaker 25D arranged in the direction in which the other vehicle is detected (here, right rear), thereby executing driving characteristic improvement assistance and confirming the safety of the right rear. to the driver.

Further, for example, the terminal device 22 detects the approach of a pedestrian from the front of the vehicle in the traveling direction using various sensors such as the vehicle interior camera 13A and the vehicle exterior sensor/camera 19A in the driving scene "when turning left". In such a case, the terminal device 22 executes driving characteristic improvement assistance by outputting a sound from the speaker 25B arranged in the direction in which the pedestrian is detected (here, left front), and confirms the safety of the left front. to the driver.

Further, for example, when the terminal device 22 determines that it is necessary to visually confirm the area behind the vehicle using various sensors such as the vehicle interior camera 13A and the vehicle exterior sensor/camera 19A, the terminal device 22 uses the two speakers 25C, Driving characteristic improvement support is executed by outputting a sound from each of 25D, and the driver is urged to confirm the safety behind.

In addition, the terminal device 22 analyzes approaching objects or obstacles detected by various sensors such as the in-vehicle camera 13A and the exterior sensor/camera 19A, and determines the types of detected approaching objects or obstacles (for example, pedestrians, etc.). vehicle, two-wheeled vehicle, etc.) may be output from each of the speakers 25A to 25D. For example, when the terminal device 22 detects that a pedestrian is approaching from the sidewalk, the terminal device 22 may say, "A pedestrian is approaching from the sidewalk." is approaching." is output from each of the speakers 25A to 25D to execute driving characteristic improvement support.

Next, with reference to FIG. 29, a modification 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 assistance. It should be noted that the example of the driving characteristic improvement support method and the modified example of the driving characteristic improvement support shown in FIG. 29 are only examples, and the present invention is not limited to this.

The driving characteristic improvement server S3 calculates the frequency of the driver's previous safety confirmation behavior based on the driving characteristic data (specifically, the behavioral characteristic data) in the driving scene associated with the user ID of the driver, and the vehicle C1A. , … based on the driving characteristic data (specifically, behavioral characteristic data) in the driving scene acquired from … and the frequency of the latest safety confirmation behavior of the driver, respectively, and improvement effect data corresponding to the driving scene information A change in the frequency of the driver's safety confirmation behavior before and after the driving characteristic improvement assistance executed based on is determined.

Specifically, the driving characteristic improvement server S3 determines whether the driver's safety confirmation behavior is increasing in this driving scene based on the frequency of the previous safety confirmation behavior and the frequency of the latest safety confirmation behavior ( That is, it is determined whether or not the driving characteristics are improved. The driving characteristic improvement server S3 generates this driving scene information based on the acquired emotion data and the determination result as to whether or not the frequency of safety confirmation behavior is increasing (that is, whether or not the driving characteristic is improving). 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, . The driving characteristic improvement server S3 may periodically (for example, one day, one week, one month, etc.) perform the improvement effect data generation process.

The driving characteristic improvement server S3 indicates that the acquired emotion data of the driver indicates a positive emotion of "comfort" and that the frequency of safety confirmation behavior after driving characteristic improvement assistance has increased (that is, , the driving characteristics are improving), the driving characteristics of the driver are improving, and the driving characteristics improvement support method indicated by the improvement effect data corresponding to the driving characteristics information (that is, the speaker 25 or the warning display control method of the lamp 26) is 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 associates the improvement effect data with the other driving scene information. Register (update) in the database DB4.

On the other hand, the driving characteristic improvement server S3 indicates that the acquired emotion data of the driver indicates "comfort", which is a positive emotion, and the frequency of safety confirmation behavior after driving characteristic improvement assistance has not increased. (that is, the driving characteristics have not improved), the driving characteristics of the driver have not improved, but the driving characteristics improvement support method indicated by the improvement effect data corresponding to the driving characteristics information (that is, the speaker 25 Alternatively, it is determined that the control method of the warning indicator lamp 26 is effective. In such a case, the driving characteristic improvement server S3 generates new improvement effect data by increasing the frequency of driving characteristic improvement support indicated by the improvement effect data corresponding to the driving scene information, and registers the new improvement effect data in the improvement effect database DB4. (Update.

Further, the driving characteristic improvement server S3 indicates that the acquired emotion data of the driver indicates "uncomfortable", which is a negative emotion, and the frequency of safety confirmation behavior after the driving characteristic improvement assistance has increased. (that is, the driving characteristics have improved), the driving characteristics of this driver have improved, but the currently set driving characteristics improvement support method (that is, the speaker 25 or the warning indicator light 26) control method) is necessary. 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) in the improvement effect database DB4 as new improvement effect data of this driving scene information. ) and registers (updates) in the improvement effect database DB4 as new improvement effect data of other driving scene information.

On the other hand, the driving characteristic improvement server S3 indicates that the acquired emotion data of the driver indicates "comfort", which is a positive emotion, and the frequency of safety confirmation behavior after driving characteristic improvement assistance has not increased. (That is, the driving characteristics have not improved), the driving characteristics of this driver have not improved, and the currently set driving characteristics improvement support method (that is, the speaker 25 or the warning indicator light 26 control method) is not effective. 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) in the improvement effect database DB4 as new improvement effect data of this driving scene information. )do.

For example, when the current improvement effect data is a support method for executing a safety confirmation action using the speaker 25 and the warning indicator light 26, the driving characteristic improvement server S3 uses either the speaker 25 or the warning indicator light 26. When generating new improvement effect data for executing safety confirmation action using the warning indicator light 26, or when the current improvement effect data is a support method for executing safety confirmation action using the warning indicator light 26, safety confirmation using the speaker 25 Generate new improvement effect data for executing actions.

As described above, the driving characteristic improvement server S3 according to the second embodiment is configured based on the driving characteristic improvement state corresponding to the frequency of the driver's safety confirmation behavior and the driver's reaction (emotional data) due to the driving characteristic improvement support. , a driving characteristic improvement support method more suitable for the driver can be set.

Next, operation procedures of 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 flow chart showing an operation procedure example of the driving characteristic improvement support system 200 according to the second embodiment. FIG. 31 is a flow chart for explaining 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, . For example, each of the vehicles C1A, .

If each of the vehicles C1A, . sensor) to start sensing the driver's driving characteristics and behavioral characteristics (that is, driving characteristic data) (St53).

On the other hand, when each of the vehicles C1A, . It waits in a sleep state (St51).

Each of the vehicles C1A, . Each of the vehicles C1A, . (St55).

In the processing of step St55, each of the vehicles C1A, . (St55, YES), based on the acquired driving characteristic data (specifically, behavioral characteristic data), it is determined whether or not execution of safety confirmation behavior by the driver has been detected (St56). . Note that there may be a plurality of safety confirmation actions corresponding to the driving scene. Further, when there are a plurality of safety confirmation actions corresponding to the driving scene and the execution order is determined, each of the vehicles C1A, . You can judge whether

If each of the vehicles C1A, . St56, YES), the acquired driving characteristic data, the driving scene information, the emotion data for the driving characteristic improvement support corresponding to the driving scene information, and the user ID are linked and transmitted to the driving characteristic improvement server S3. , is stored in the memory 15A. Each of the vehicles C1A, . (St57).

On the other hand, in the process of step St56, each of the vehicles C1A, . If so (St56, NO), driving characteristic improvement assistance is executed based on the current driver's driving characteristic data (that is, driving skill) and improvement effect data corresponding to the driving scene information (St58).

Each of the vehicles C1A, . 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, . Each of the vehicles C1A, . (St59).

On the other hand, in the processing of step St55, each of the vehicles C1A, . 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 execution of the safety confirmation action by the driver has been detected (St60 ).

If each of the vehicles C1A, . St60, YES), the acquired driving characteristic data, the driving scene information, the driver's emotion data for driving characteristic improvement assistance, and the user ID are linked and transmitted to the driving characteristic improvement server S3, and the memory 15A. memorize to Each of the vehicles C1A, . (St57).

On the other hand, in the process of step St60, each of the vehicles C1A, . 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 scene), driving characteristic improvement support is executed to provide safety corresponding to the driving scene. It is determined whether or not to prompt a confirmation action (St61).

Specifically, in the process of step St61, each of the vehicles C1A, . Each of the vehicles C1A, . judge.

For example, if the driving scene is "driving on a straight road" and the risk (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, .

Further, for example, when the driving scene is "when changing lanes" and the degree of risk (score) corresponding to this driving scene is "high", the threshold for the frequency of safety confirmation actions is set to 1/2. be. In such a case, each of the vehicles C1A, .

If each of the vehicles C1A, . YES), driving characteristic improvement assistance is executed based on the current driver's driving characteristic data (that is, driving skill) and improvement effect data corresponding to the driving scene information (St58). Specifically, for each of the vehicles C1A, . If so, it is determined that driving characteristic improvement support is to be executed to encourage safety confirmation behavior corresponding to the driving situation (St61, YES).

On the other hand, when each of the vehicles C1A, . (St61, NO), the acquired driving characteristic data, the driving scene information, the driver's emotion data regarding the driving characteristic improvement support, and the user ID are linked and transmitted to the driving characteristic improvement server S3, and the memory 15A. Each of the vehicles C1A, . (St57). Specifically, each of the vehicles C1A, . If it is determined that there is, it is determined that the driving characteristic improvement support is not to be executed and the safety confirmation action corresponding to the driving scene is not prompted (St61, NO).

Each of the vehicles C1A, . . . determines whether it has detected that the driver has finished driving (St). It should be noted that the end of driving referred to here may be when the driver gets off the vehicle and moves away from the own vehicle by a predetermined distance or more.

When each of the vehicles C1A, . Wait (St51).

On the other hand, each of the vehicles C1A, . determines again whether or not the current driving scene 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, . It can help improve characteristics (driving skills). In addition, the driving characteristic improvement server S3 in the second embodiment provides the driver with a 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 management method of the driving characteristic improvement support data executed by the driving characteristic improvement server S3 is the management method of the driving characteristic improvement effect data executed by one or more computers capable of communicating with at least one vehicle C1A. There are a plurality of driving scene information indicating driving scenes of the vehicles C1A, . example) and the driving characteristic data of the driver in the driving scene information are linked to each of the user IDs of a plurality of drivers (an example of the driver ID), and the driving scene information and the improvement effect data are respectively registered. are linked and transmitted to the vehicles C1A, . . . , the user ID of the driver who drives the vehicle C1A, . and matching the user IDs of the plurality of drivers with the acquired user IDs, and the driving characteristic data linked to the matched user IDs and the acquired driving Based on the characteristic data and the emotion data, new improvement effect data corresponding to the acquired driving scene information is generated, and the acquired driving scene information among the plurality of driving scene information linked to the collated user ID is generated. The improvement effect data linked to the same driving scene information as the scene information is updated to the generated new improvement effect data. The computer referred to here includes at least the driving characteristic improvement server S3.

As a result, the driving characteristic improvement server S3 according to the second embodiment uses the improvement effect data transmitted in advance to each of the vehicles C1A, . It is possible to acquire the characteristics and the driver's emotion data for driving characteristic improvement assistance (an example of safety confirmation behavior assistance) indicated by the improvement effect data. The driving characteristic improvement server S3 generates new improvement effect data based on the obtained current state of the driver (that is, the driver's driving characteristic (driving skill) and emotion), and also generates new improvement effect data. data, driving scene information, driving characteristic data, and emotion data used to generate the new improvement effect data are linked to the user ID, so that the improvement effect data for each user ID can be processed more efficiently. can be managed to

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 or not the driving characteristic of the driver in the driving situation has 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. As a result, the driving characteristic improvement server S3 according to the second embodiment can generate improvement effect data more suitable for the current state of the driver (that is, the driver's driving characteristic (driving skill) and emotion).

Further, as described above, when the driving characteristic improvement server S3 according to the second embodiment determines that the emotion data is positive and the driving characteristic is improved, the The improvement effect data linked to a plurality of pieces of driving scene information are updated to the generated new improvement effect data. As a result, the driving characteristic improvement server S3 according to the second embodiment determines that the driving characteristic of the driver has improved, and furthermore, the improvement effect data (that is, driving Improvement effect data indicating a driving characteristic improvement support method that is more suitable for the driver by continuing the driving characteristic improvement support method) in the current driving situation and generating and updating new improvement effect data in other driving situations. more efficient management of

Further, as described above, when the driving characteristic improvement server S3 according to the second embodiment determines that the emotion data is positive and the driving characteristic is not improved, the driving situation information corresponding to the acquired driving situation information New improvement effect data is generated in which the frequency of support is increased more than the improvement effect data, and the improvement effect data linked to the same driving scene information as the acquired driving scene information is added to the generated new improvement effect data. Update to data. As a result, the driving characteristic improvement server S3 according to the second embodiment provides a new improvement that increases the frequency of assistance in the improvement effect data (that is, the driving characteristic improvement support method) that the driver feels comfortable (that is, positively). By generating and updating the effect data, more efficient management of the improvement effect data indicating driving characteristic improvement assistance methods more suitable for the driver can be performed.

Further, as described above, when the driving characteristic improvement server S3 according to Embodiment 2 determines that the emotion data is negative and the driving characteristic is improved, the improvement effect corresponding to the acquired driving scene information Generate new improvement effect data different from the data, update the improvement effect data linked to other driving scene information different from the acquired driving scene information to the generated new improvement effect data, and acquire The modification of the improvement effect data linked to the same driving scene information as the driving scene information is omitted. As a result, the driving characteristic improvement server S3 according to the second embodiment determines that the driving characteristic of the driver has improved, and furthermore, the improvement effect data (that is, driving characteristic improvement support method) is generated and updated as new improvement effect data for the same driving situation, and the improvement effect data different from the improvement effect data that the driver feels uncomfortable (that is, negative) in other driving situations. is generated as new improvement effect data and updated, more efficient management of the improvement effect data indicating the driving characteristic improvement support method more suitable for the driver can be executed.

Further, as described above, when the driving characteristic improvement server S3 according to the second embodiment determines that the emotion data is negative and the driving characteristic is not improved, the driving situation information corresponding to the acquired driving situation information New improvement effect data different from the improvement effect data is generated, and the 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 characteristic improvement server S3 according to the second embodiment determines that the driving characteristic of the driver has not improved, and furthermore, the improvement effect data (that is, , 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 (i.e., negative) in other driving situations. By generating and updating improvement effect data that differs from the improvement effect data felt by the driver as new improvement effect data, 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 improvement effect data generated by the driving characteristics improvement server S3 according to the second embodiment is installed in the vehicles C1A, . 26 (an example of safe driving support equipment). 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 lamp 26 in the driving characteristic improvement assistance executed in each of the vehicles C1A, .

Further, as described above, the improvement effect data generated by the driving characteristic improvement server S3 according to the second embodiment is provided in the vehicles C1A, . and if the emotion data is negative, generate new improvement effect data for performing support by 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, By generating and updating new improvement effect data for the changed support method, more efficient management of the improvement effect data indicating the driving characteristic improvement support method more suitable for the driver can be executed. For example, when the current improvement effect data is a support method for executing a safety confirmation action using the speaker 25 and the warning indicator light 26, the driving characteristic improvement server S3 uses either the speaker 25 or the warning indicator light 26. When generating new improvement effect data for executing safety confirmation action using the warning indicator light 26, or when the current improvement effect data is a support method for executing safety confirmation action using the warning indicator light 26, safety confirmation using the speaker 25 Generate new improvement effect data for executing actions.

Further, as described above, the improvement effect data generated by the driving characteristic improvement server S3 according to the second embodiment is provided in the vehicles C1A, . When the emotion data is negative, new improvement effect data is generated in which the frequency of support by voice or light is reduced from that of 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 assistance method based on the current improvement effect data, the driving characteristic improvement server S3 By generating and updating new improvement effect data with reduced frequency of improvement support, more efficient management of the improvement effect data indicating the driving characteristic improvement support method more suitable for the driver can be executed.

As described above, the vehicles C1A, . The improvement effect data for supporting behavior improvement and the driver's user ID are linked and stored, and the driver's driving characteristic data in the driving scene information and the improvement effect data corresponding to the driving scene information are used for support. Emotional data of the driver is acquired by various sensors (an example of a sensor), and the acquired driving characteristic data and emotional data, the driving scene information from which the driving characteristic data and emotional data are acquired, and the user ID are linked. and transmit it to an external device, acquire new improvement effect data corresponding to the driving scene information transmitted from the external device, and convert the improvement effect data linked to the driving scene information to the acquired new improvement effect Update to data. Also, the one or more computers mounted on the vehicles C1A, .

As a result, the vehicles C1A, . , and the driver's emotion data for driving characteristic improvement support (an example of safety confirmation action support) are transmitted to the driving characteristic improvement server S3, so that the current state of the driver (that is, the driver's current driving characteristic data, You can acquire new improvement effect data based on emotion data). Each of the vehicles C1A, . By linking, the improvement effect data can be managed more efficiently.

Although various embodiments have been described above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is obvious that a person skilled in the art can conceive of various modifications, modifications, substitutions, additions, deletions, and equivalents within the scope of the claims. It is understood that it belongs to the technical scope of the present disclosure. In addition, the constituent elements of the various embodiments described above may be combined arbitrarily without departing from the gist of the invention.

INDUSTRIAL APPLICABILITY The present disclosure is useful as a management method of driving characteristic improvement data that can more efficiently manage driving characteristic improvement support data based on driving characteristic data and emotion data.

10, 12 car navigation device 11, 11A communication device 12A, 32, 42, 52 processor 12B, 15, 33, 43, 53 memory 12C, 22C display unit 12D, 22D input unit 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 wheel 18 Speed sensor 19, 19A Outside sensor/camera 20 GPS sensor 24 Inside sensor 25, 25A, 25B, 25C, 25D Speakers 26, 26A, 26B Warning indicator light 31, 41, 51 communication unit 52A support method generation unit 54 database 100 driving characteristic management system C1, C1A vehicle NW, NWA network S3 driving characteristic improvement server TB3 driving characteristic history table TB4 driving characteristic improvement management table

Claims (11)

A method for managing driving characteristic improvement support data executed by one or more computers capable of communicating with at least one vehicle,
a plurality of pieces of driving scene information indicating driving scenes of the vehicle; support data corresponding to the driving scene information and supporting improvement of safety confirmation behavior of a driver who drives the vehicle; and the driver in the driving scene information. and registering the driving characteristic data in association with each driver ID of the plurality of drivers,
linking the driving scene information and the support data, respectively, and transmitting the information to the vehicle;
acquiring a driver ID of a driver who drives the vehicle, driving characteristic data of the driver corresponding to the driving scene information, and emotion data of the driver with respect to assistance based on the assistance data;
matching the driver ID of each of the plurality of drivers with the acquired driver ID;
New support data corresponding to the acquired driving scene information is generated based on the driving characteristic data linked to the verified driver ID, and the acquired driving characteristic data and emotion data. ,
The support data linked to the same driving scene information as the acquired driving scene information among a plurality of pieces of driving scene information linked to the collated driver ID is added to the generated new assistance. update the data,
A method of managing driving characteristic improvement support data. determining whether the driving characteristics of the driver in the driving scene have improved using the acquired driving characteristics data and the registered driving characteristics data;
generating the new assistance data based on the emotion data and a determination result as to whether the driving characteristics have improved;
The method for managing driving characteristic improvement support data according to claim 1 . When it is determined that the emotion data is positive and the driving characteristics have improved, the support data linked to the plurality of pieces of driving scene information linked to the verified driver ID is transferred. , updating to the new assistance data generated;
The method for managing driving characteristic improvement support data according to claim 2. When it is determined that the emotion data is positive and that the driving characteristics have not improved, the new driver increases the frequency of the assistance from that of the assistance data corresponding to the acquired driving scene information. generate support data,
updating the support data linked to the same driving scene information as the acquired driving scene information to the generated new support data;
The method for managing driving characteristic improvement support data according to claim 2. generating the new improvement effect data different from the support data corresponding to the acquired driving scene information when it is determined that the emotion data is negative and the driving characteristics have improved;
updating support data linked to other driving scene information different from the acquired driving scene information to the generated new support data;
omitting the change of the support data linked to the same driving scene information as the acquired driving scene information;
The method for managing driving characteristic improvement support data according to claim 2. generating the new improvement effect data different from the support data corresponding to the acquired driving scene information when it is determined that the emotion data is negative and the driving characteristics have not improved;
updating the support data linked to the same driving scene information as the acquired driving scene information to the generated new support data;
The method for managing driving characteristic improvement support data according to claim 2. The assistance data is a control command for controlling driving safety assistance equipment that is mounted on the vehicle and performs the assistance by voice or light.
The method for managing driving characteristic improvement support data according to claim 1 . The assistance data is a control command for controlling driving safety assistance equipment that is mounted on the vehicle and executes the assistance by voice or light,
if the emotion data is negative, generating the new assistance data that causes the assistance to be performed by either the voice or the light;
7. The method for managing driving characteristic improvement support data according to claim 5 or 6. The assistance data is a control command for controlling driving safety assistance equipment that is mounted on the vehicle and executes the assistance by voice or light,
when the emotion data is negative, generating the new support data in which the frequency of the support by the voice or the light is reduced compared to the support data corresponding to the acquired driving scene information;
7. The method for managing driving characteristic improvement support data according to claim 5 or 6. A method for managing driving characteristic improvement support data executed by a vehicle, comprising:
a plurality of pieces of driving scene information indicating driving scenes of the vehicle; support data corresponding to the driving scene information and supporting improvement of safety confirmation behavior of the driver who drives the vehicle; and a driver ID of the driver. is linked and stored,
obtaining, by a sensor, the driving characteristic data of the driver in the driving scene information and the emotion data of the driver with respect to assistance based on the assistance data corresponding to the driving scene information;
linking the acquired driving characteristic data and the emotion data, the driving scene information from which the driving characteristic data and the emotion data were acquired, and the driver ID, and transmitting the result to an external device;
Acquiring new support data corresponding to the driving scene information transmitted from the external device;
updating the support data linked to the driving scene information to the new support data obtained;
A method of managing driving characteristic improvement support data. A method for managing driving characteristic improvement support data executed by one or more computers mounted on a vehicle,
a plurality of pieces of driving scene information indicating driving scenes of the vehicle; support data corresponding to the driving scene information and supporting improvement of safety confirmation behavior of the driver who drives the vehicle; and a driver ID of the driver. is linked and stored,
obtaining, by a sensor, the driving characteristic data of the driver in the driving scene information and the emotion data of the driver with respect to assistance based on the assistance data corresponding to the driving scene information;
linking the acquired driving characteristic data and the emotion data, the driving scene information from which the driving characteristic data and the emotion data were acquired, and the driver ID, and transmitting the result to an external device;
Acquiring new support data corresponding to the driving scene information transmitted from the external device;
updating the support data linked to the driving scene information to the new support data obtained;
A method of managing driving characteristic improvement support data.

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