JP7081132B2 - Information processing method and information processing equipment - Google Patents

Description

The present invention relates to an information processing method and an information processing apparatus.

In a driving support system that provides driving support by vehicle control, a learning point within the evaluation target section is acquired in a configuration in which a point at which vehicle control should be executed is acquired as a learning point and vehicle control is performed when the vehicle travels again at the learning point. A method is known in which the learning rate obtained by dividing the number of times of control, which is the number of times vehicle control is performed in, by the number of points requiring control, which is the number of points where vehicle control should have been executed in the evaluation target section, is displayed on the display unit. (Patent Document 1).

Japanese Unexamined Patent Publication No. 2013-210328

In general, the driving performed when only the driver is on board may differ from the driving performed when there is a passenger other than the driver. In particular, when there are a plurality of passengers or when the passengers are young children or elderly people, there are increasing cases where the optimum driving characteristics differ depending on the number and age of the passengers. In the prior art, the passenger is not considered, and the driving support suitable for the driver's own driving characteristics is provided. Therefore, there is a problem that the optimum vehicle control parameters in consideration of passengers cannot be determined.

An object to be solved by the present invention is to provide an information processing method and an information processing apparatus capable of determining an optimum control parameter in consideration of a passenger.

The present invention acquires at least one of the captured image in the vehicle output from the camera that captures the interior of the vehicle and the audio information in the vehicle output from the microphone that acquires the sound in the vehicle interior, and uses the acquired information. Based on this, the relationship between the persons existing in the vehicle is estimated, the personnel composition in the vehicle in which the number of people in the vehicle and the relationship between the persons in the vehicle are related is estimated, and the vehicle is detected from the sensor that detects the running state of the vehicle. The control parameters related to the driving of the vehicle are acquired, the driving history of the vehicle in which the personnel configuration in the vehicle and the control parameters are associated is stored in the storage device, and the driver's driving for each personnel configuration in the vehicle specified from the accumulated driving history. By associating the characteristics with the control parameters corresponding to the driving characteristics, the control parameters corresponding to the personnel configurations in the vehicle are specified for each personnel configuration in the vehicle, thereby solving the above-mentioned problems.

According to the present invention, it is possible to determine the optimum control parameters in consideration of the passenger.

FIG. 1 is a diagram showing a block configuration diagram of a driving knowledge extraction system in the first embodiment. FIG. 2 is a diagram for explaining the in-vehicle personnel composition estimation process. FIG. 3 is a flowchart of the vehicle-mounted device transmitting vehicle travel history information to the data center. FIG. 4 is a flowchart for explaining a process for specifying an optimum control parameter for each personnel configuration. FIG. 5A is a flowchart for explaining the process from getting into the vehicle to providing the optimum control parameters for the personnel configuration in the vehicle. FIG. 5B is a flowchart for explaining the process from getting into the vehicle to providing the optimum control parameters for the personnel configuration in the vehicle.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

In the present embodiment, the case where the information processing device according to the present invention is applied to an in-vehicle device 100 mounted on a vehicle and an information providing processing system that cooperates with a data center 200 will be described as an example.

FIG. 1 is a diagram showing a block configuration of the information providing system 1. The information providing system 1 of the present embodiment includes an in-vehicle device 100 and a data center 200. The information providing system 1, the in-vehicle device 100, and each of the devices provided therein are computers including a CPU and other arithmetic processing devices and executing arithmetic processing.

First, the in-vehicle device 100 will be described. The in-vehicle device 100 of the present embodiment includes an in-vehicle camera 110, an in-vehicle microphone 120, an in-vehicle operating device group 130, an in-vehicle sensor group 140, an in-vehicle display 150, an in-vehicle communication device 160, and an in-vehicle control device 170. Each device constituting the vehicle-mounted device 100 is connected by a CAN (Controller Area Network) or other vehicle-mounted LAN in order to exchange information with each other.

The in-vehicle camera 110 is provided in the interior of the vehicle and captures the state of the interior. The vehicle-mounted camera 110 outputs the captured image to the vehicle-mounted control device 170. The installation position of the vehicle-mounted camera 110 and the number of the vehicle-mounted cameras 110 are not particularly limited. For example, the vehicle-mounted camera 110 is provided on the instrument panel and captures a person sitting in the front seat. Further, for example, the vehicle-mounted camera 110 is provided in the vicinity of the rear-view mirror and captures a person sitting in the rear seat.

The in-vehicle microphone 120 is provided in the interior of the vehicle and collects the voice generated in the vehicle. The vehicle-mounted microphone 120 converts the collected voice into a digital signal and outputs it as voice information to the vehicle-mounted control device 170. The installation position of the vehicle-mounted microphone 120 and the number of the vehicle-mounted microphone 120 are not particularly limited. For example, the vehicle-mounted microphone 120 is provided at a predetermined position on each seat to collect conversations in the vehicle.

The in-vehicle operating device group 130 is composed of operating devices that can be operated by the driver. The in-vehicle operation device group 130 includes a steering wheel, an accelerator pedal, a brake pedal, a shift lever, a turn signal switch that blinks left and right turn signal lamps (direction indicators), a hazard switch that blinks a hazard lamp, and a wiper for operating the wiper. Includes at least a wiper switch and a navigation device for setting the vehicle's travel path. The turn signal switch also has a function for operating a headlamp (also called a headlight). The in-vehicle operation device group 130 outputs the operation information operated by the driver to the in-vehicle control device 170.

Further, in the case of a vehicle in which the traveling characteristic mode of the vehicle can be changed, the vehicle-mounted operation device group 130 also includes an apparatus (for example, a switch) for setting the traveling characteristic mode of the vehicle. Examples of the vehicle driving characteristic mode include a normal mode, a snow mode, a sports mode, and a fuel-efficient mode (eco mode). When the driver sets the driving characteristic mode, the control parameters related to the traveling of the vehicle are set to values suitable for the driving scene corresponding to the set driving characteristic mode. The details of the control parameters related to the running of the vehicle will be described later.

For example, the snow mode is a traveling characteristic mode corresponding to traveling on a traveling road having a road surface friction coefficient of a predetermined value or less, including a snowy road and an icy road. When the snow mode is set, the gear ratio is set to the high speed side as compared with the normal mode, and the vehicle can run so that the driving force is small. Further, for example, the sports mode is a running characteristic mode corresponding to running on an uphill or a downhill. When set to sports mode, the engine speed is set to a higher speed side than in normal mode, and the vehicle can accelerate rapidly even on an uphill slope.

The in-vehicle sensor group 140 is composed of sensors, devices, and the like that detect the traveling state of the vehicle. The in-vehicle sensor group 140 includes a state detection device 141, a position detection device 142, and an object detection device 143. The in-vehicle sensor group 140 outputs the detection result detected by each sensor or each device to the in-vehicle control device 170.

The state detection device 141 is a device that detects the state of the vehicle. The state detection device 141 includes at least a steering angle sensor, an accelerator opening degree sensor, a brake opening degree sensor, a speed sensor, an acceleration sensor, and an attitude sensor. The steering angle sensor detects the steering angle, steering speed, and steering acceleration, the accelerator opening sensor detects the accelerator opening, and the brake opening sensor detects the brake opening. Further, the speed sensor detects the moving speed of the vehicle, and the acceleration sensor detects at least one of the acceleration in the front-rear direction of the vehicle and the acceleration in the lateral direction (left-right direction) of the vehicle. The posture sensor detects information about the posture of the vehicle such as the pitch angle of the vehicle, the yaw angle of the vehicle, the roll angle of the vehicle, and the suspension stroke amount.

Further, in the case of a vehicle in which the traveling characteristic mode of the vehicle can be changed, the state detection device 141 detects the type of the traveling characteristic mode of the vehicle set by the driver via the in-vehicle operating device group 130.

The position detection device 142 is a device that detects the position where the vehicle is traveling. The position detecting device 142 includes at least a device including a GPS (Global Positioning System). The position detecting device 142 refers to the map information and the road information provided in the navigation device described above, and detects the position where the vehicle is currently traveling. Map information is information in which points are associated with roads, structures, facilities, and the like. Road information is information in which location information is associated with information such as the curvature and slope of a road.

The object detection device 143 is a device that detects the situation around the vehicle. The object detection device 143 includes at least an image pickup device such as a camera, a sonar device, and a radar device. The image pickup device detects the existence of an object including an obstacle existing around the vehicle, the position of the object, and the distance between the own vehicle and the object. Objects include moving objects such as pedestrians, two-wheeled vehicles, and four-wheeled vehicles (other vehicles), stationary objects such as signs, and two-dimensional signs such as stop lines or lane boundaries displayed on the road surface. Sonar devices and radar devices have similar functions. Examples of radar devices include millimeter-wave radars, laser radars, ultrasonic radars, and the like. In the present embodiment, the object detection device 143 measures the distance between the own vehicle and the preceding vehicle (distance between the preceding vehicle) from the position where the own vehicle is traveling and the position where the preceding vehicle is traveling. do.

The in-vehicle display 150 is provided in the interior of the vehicle, and displays an image such as a screen for route guidance in a navigation system according to operation information from the in-vehicle operation device group 130.

Further, information for guiding the optimum control parameters for the current personnel configuration in the vehicle (hereinafter referred to as control parameter guidance information) is input to the vehicle-mounted display 150 from the data center 200 via the vehicle-mounted communication device 160 and the vehicle-mounted control device 170. Will be done. The in-vehicle display 150 presents control parameter guidance information to a person in the vehicle. The details of the control parameter guidance information transmitted from the data center 200 will be described later.

The in-vehicle communication device 160 is a device capable of communicating with the server communication device 210 of the data center 200 via a telephone line network, an Internet line network, or the like. Information on the personnel configuration in the vehicle and information on the travel history of the vehicle (hereinafter referred to as vehicle travel history information), which will be described later, are input to the in-vehicle communication device 160, and the in-vehicle communication device 160 transmits these information to the server. Send to device 210. The in-vehicle communication device 160 can include such information in the probe information, and may transmit the information as the probe information to the server communication device 210. Further, the vehicle-mounted communication device 160 receives control parameter guidance information from the server communication device 210, and outputs the received control parameter guidance information to the vehicle-mounted control device 170. The details of the information on the personnel composition in the vehicle and the travel history information of the vehicle will be described later.

Further, the information on the personnel configuration in the vehicle and the travel history information of the vehicle are input to the in-vehicle communication device 160 at asynchronous timing. The vehicle-mounted control device 170, which will be described later, outputs information on the personnel configuration in the vehicle to the vehicle-mounted communication device 160 at a timing when a predetermined time has elapsed since the vehicle started. On the other hand, the in-vehicle control device 170 outputs the travel history information of the vehicle to the in-vehicle communication device 160 at the timing when the ignition is turned off. That is, the in-vehicle communication device 160 transmits the information on the personnel configuration in the vehicle to the server communication device 210 in the data center 200 before transmitting the travel history information of the vehicle.

The in-vehicle control device 170 is a device for estimating the personnel configuration in the vehicle and generating travel history information of the vehicle. Specifically, the in-vehicle control device 170 executes the travel history generation process by executing the ROM (Read Only Memory) in which the program for executing the travel history generation process is stored and the program stored in the ROM. It is a computer equipped with a CPU (Central Processing Unit) as an operating circuit and a RAM (Random Access Memory) functioning as an accessible storage device.

Specifically, the vehicle-mounted control device 170 of the present embodiment generates vehicle travel history information by executing the following processing. The in-vehicle control device 170 has an in-vehicle person characteristic estimation process for estimating the characteristics of a person in the vehicle, an in-vehicle person relationship process for estimating the relationship between the persons in the vehicle, and an in-vehicle personnel composition estimation for estimating the personnel composition in the vehicle. The processing, the control parameter acquisition processing for acquiring the control parameters related to the traveling of the vehicle, and the traveling history generation processing for generating the traveling history information of the vehicle based on these processing results are executed.

The in-vehicle control device 170 executes each function in cooperation with the software for realizing each of the above functions or executing each process and the above-mentioned hardware.

First, the in-vehicle person feature estimation process will be described. The vehicle-mounted control device 170 estimates the characteristics of a person present in the vehicle based on the captured image of the vehicle-mounted camera 110. The characteristics of the person in the car include gender and age. For example, the vehicle-mounted control device 170 extracts a plurality of characteristic points (eyes, nose, mouth, hair, etc.) of a person appearing in the captured image by performing image processing on the captured image of the vehicle-mounted camera 110. Then, the in-vehicle control device 170 estimates the gender of the person in the vehicle by collating the extracted characteristic points of the person in the vehicle with the characteristic pattern for determining the gender, which is a predetermined characteristic pattern. be able to. Similarly, the in-vehicle control device 170 estimates the age of a person in the vehicle by collating the characteristic points of the person in the vehicle with a characteristic pattern for estimating the age, which is a predetermined characteristic pattern. Can be done.

The accuracy of the age estimated by the in-vehicle control device 170 is not particularly limited. The in-vehicle control device 170 can appropriately change the accuracy of the estimated age according to the image processing capability and the imaging accuracy of the in-vehicle camera 110. For example, the in-vehicle control device 170 stores in a storage device in advance a feature pattern categorized in units of 10 years, with the range of 10 to 19 years old being "teens" and the range of 20 to 29 years old being "20s". By doing so, the age of the person in the car can be estimated. The in-vehicle person feature estimation process is not limited to the above-mentioned method, and the in-vehicle control device 170 can appropriately use the in-vehicle person feature estimation process known at the time of filing the application of the present application.

Next, the in-vehicle person relationship estimation process will be described. The vehicle-mounted control device 170 estimates the relationship between the persons existing in the vehicle based on the voice information of the vehicle-mounted microphone 120. The relationship between people in a car is a relationship based on the driver, and is a relationship between the driver and a passenger.

The in-vehicle control device 170 first extracts only the conversation in the vehicle from the voice information. Then, each time the vehicle-mounted control device 170 detects a specific keyword from the conversation content, the vehicle-mounted control device 170 counts up the number of times the keyword is detected. A specific keyword is a keyword associated with a relationship between people. The in-vehicle control device 170 stores a specific keyword in a storage device such as a ROM in advance.

The keywords for estimating the relationship between people will be explained. For example, the above-mentioned storage device stores specific keywords for classifying conversation contents into "family relations", "work relations", "friend relations", and "other relations". Examples of keywords associated with "family relations" include family names (for example, "dad", "mother", "brother", "sister", "grandpa", "grandma", etc.). Be done. In addition, the keywords associated with "work-related" include job titles (for example, "president", "department manager", "section manager", etc.), company names (for example, "○○ Co., Ltd."), and business terms. (For example, "contract", "transaction", "meeting", "promise", "delivery date", etc.) can be mentioned as an example. In addition, examples of keywords associated with "friendship" include TV program names, music names, sports terms, and restaurant names. Further, for the keywords associated with "other relationships", specific keywords are appropriately set by the vehicle occupants and the system side.

When the number of times a specific keyword is detected exceeds a predetermined number of times, the in-vehicle control device 170 estimates the relationship corresponding to the detected keyword as the relationship between people in the vehicle. The predetermined number of times is not particularly limited, but is preferably an experimentally determined value. The method of identifying the relationship between the persons in the car from the detected keywords is not particularly limited. When a plurality of specific keywords are detected across a plurality of relationships, the in-vehicle control device 170 determines the relationship corresponding to the keyword whose number of detections first exceeds a predetermined number as the relationship between persons in the vehicle. You may estimate. Further, the in-vehicle control device 170 estimates that the relationship corresponding to the relationship having the largest number of detected keyword types or the relationship having the largest total number of detected keywords is the relationship between persons in the vehicle. May be good.

Next, the in-vehicle control device 170 estimates the intimacy between people in the vehicle. When the in-vehicle control device 170 estimates the relationship between the persons in the vehicle from the conversation content, the in-vehicle control device 170 estimates the intimacy between the persons in the vehicle. The intimacy between people in a car is the intimacy with respect to the driver, and is the intimacy between the driver and the passenger (friendship between the driver and the passenger).

The in-vehicle control device 170 extracts the remarks of a specific person (from the start of the remarks to the end of the remarks) from the conversation contents in the vehicle. Then, the in-vehicle control device 170 estimates the intimacy between the persons in the vehicle from the wording in the extracted remarks. For example, the in-vehicle control device 170 stores a predetermined wording feature pattern in a storage device such as a ROM, which can determine the intimacy between persons. Then, the in-vehicle control device 170 can estimate the intimacy between the persons in the vehicle by collating the remarks of a specific person with the characteristic pattern of the wording.

The characteristic pattern of wording for estimating the intimacy between people will be explained. For example, the above-mentioned storage device stores a characteristic pattern of wording for classifying intimacy into three patterns of "high", "normal", and "low". The closer the driver and the passenger are, the higher the intimacy is estimated. Characteristic patterns of wording include wording using honorifics (honorifics, humble words, polite words), wording when calling the other party (for example, calling only by name, calling only by surname, assigning a position to the surname). For example).

The in-vehicle control device 170 performs pattern matching between the remarks of a specific person and the wording feature pattern, and estimates that the intimacy with a high matching ratio is the intimacy between the persons in the vehicle. The method of estimating the intimacy from the conversation content is not limited to the above-mentioned method, and the in-vehicle control device 170 can appropriately use the intimacy estimation method known at the time of filing the application.

Next, the in-vehicle personnel composition estimation process will be described. The in-vehicle control device 170 estimates the personnel configuration in the vehicle based on the captured image of the in-vehicle camera 110, the processing result of the in-vehicle person feature estimation processing, and the processing result of the in-vehicle person relationship estimation processing. For example, the vehicle-mounted control device 170 detects the number of people in the vehicle from the captured image of the vehicle-mounted camera 110. Then, the in-vehicle control device 170 detects the number of people in the vehicle, the processing result (gender and age) of the in-vehicle person characteristic estimation processing, and the processing result of the in-vehicle person relationship processing (relationship between people in the vehicle, the person in the vehicle). Estimate the personnel composition in the car associated with the intimacy between).

An example of the processing result of the in-vehicle personnel composition estimation process will be described with reference to FIGS. 2 (A) and 2 (B). 2 (A) and 2 (B) are diagrams for explaining the in-vehicle personnel composition estimation process. FIG. 2A shows the processing result of the in-vehicle control device 170 when four people including the driver are on board. In this example, the vehicle-mounted control device 170 first detects that the number of people in the vehicle is four from the captured image of the vehicle-mounted camera 110. Next, the in-vehicle control device 170 executes the above-mentioned in-vehicle person characteristic estimation process for each of the four persons, and as shown in FIG. 2A, "male in his twenties: one person, female in his thirties". One person, one man in his fifties, one man in his sixties, one man in his sixties, for a total of four people. " Further, the in-vehicle control device 170 estimates the relationship between the persons in the vehicle as a family relationship from the conversation content in the vehicle by the above-mentioned in-vehicle person relationship estimation process, and also estimates the person in the vehicle from the wording of each person. It is estimated that the intimacy between them is high. Finally, the in-vehicle control device 170 correlates the detection result and the estimation result with "1 male in 20s, 1 female in 30s, 1 male in 50s, 1 male in 60s, total 4". First name, the relationship between these people is a family relationship, and the intimacy is high. "

Further, FIG. 2B shows the processing result of the in-vehicle control device 170 when two people including the driver are on board. Also in this example, the in-vehicle control device 170 detects that the number of people in the vehicle is two, and then executes the above-mentioned in-vehicle person characteristic estimation process for the detected two people, whereby FIG. As shown in (B), the characteristics of the person in the car are estimated as "a man in his thirties: one person and a man in his thirties: one person, for a total of two people". Then, the in-vehicle control device 170 estimates the relationship between the persons in the vehicle as a work relationship by the above-mentioned in-vehicle person relationship estimation process, and from the wording of each person, the intimacy between the persons in the vehicle is low. presume. Finally, the in-vehicle control device 170 correlates the detection result and the estimation result with "a male in his thirties: one person and a male in his thirties: one person, for a total of four people, and the relationship between these persons is a work relationship. , The intimacy is low, "estimates the personnel composition in the car.

When the in-vehicle control device 170 estimates the personnel configuration in the vehicle, the in-vehicle control device 170 transmits information on the personnel configuration in the vehicle to the server communication device 210 in the data center 200 via the in-vehicle communication device 160. The vehicle-mounted control device 170 can also include the captured image itself of the vehicle-mounted camera 110 and the voice information itself of the vehicle-mounted microphone 120 in the information on the personnel configuration in the vehicle. As a result, the server processing device 230 of the data center 200, which will be described later, can determine whether or not the passenger is a person who has a history of riding in the past from the captured image or the voiceprint data of the voice information.

Returning to FIG. 1, the control parameter acquisition process of the in-vehicle control device 170 will be described. The in-vehicle control device 170 acquires control parameters related to the running of the vehicle from the in-vehicle sensor group 140. The control parameter in the present embodiment is a control parameter indicating the running state of the vehicle detected by the vehicle-mounted sensor group 140. The control parameters include the detection result of the steering angle sensor (steering angle, etc.), the detection result of the accelerator opening sensor (accelerator opening), the detection result of the brake opening sensor (brake opening), and the detection result of the sonar device (vehicle). The distance to the object around the vehicle), the detection result of the radar device (distance to the object around the vehicle), the distance to the preceding vehicle, and the type of driving characteristic mode are included at least. Regarding the type of the traveling characteristic mode, the vehicle-mounted control device 170 may specify the type of the traveling characteristic mode set by the driver based on the operation information input from the vehicle-mounted operating device group 130.

Next, the travel history generation process will be described. The in-vehicle control device 170 generates travel history related to vehicle control parameters as vehicle travel history information based on the results of each of the above-mentioned processes. First, the vehicle-mounted control device 170 acquires the traveling position of the vehicle from the position detection device 142 included in the vehicle-mounted sensor group 140. Next, the in-vehicle control device 170 uses information associating the estimated personnel configuration in the vehicle, the specified control parameter of the vehicle, and the traveling position of the vehicle as the traveling history information of the vehicle. The vehicle-mounted control device 170 transmits vehicle travel history information to the server communication device 210 of the data center 200 via the vehicle-mounted communication device 160.

Next, the data center 200 will be described. The data center 200 is a facility in which various computers and devices such as data communication are installed. As shown in FIG. 1, the data center 200 includes a server communication device 210, a database 220, and a server processing device 230.

The server communication device 210 can communicate with the vehicle-mounted communication device 160 of the vehicle-mounted device 100 via a telephone line network, an Internet line network, or the like. The server communication device 210 communicates with a plurality of vehicle-mounted communication devices 160 mounted on each of the plurality of vehicles, and receives information on the personnel configuration in the vehicle and travel history information of the vehicle from each vehicle. The server communication device 210 outputs the information on the personnel configuration in the vehicle and the travel history information of the vehicle received from each vehicle to the server processing device 230.

The database 220 is a database that stores the traveling history of vehicles acquired from a plurality of vehicles. Since the vehicle travel history information is sequentially input to the database 220 from the server communication device 210 via the server processing device 230, the vehicle travel history information is accumulated in the database 220 with the passage of time.

The server processing device 230 includes a ROM that stores a program for specifying the optimum control parameters for each personnel configuration in the vehicle, a CPU that executes the program stored in the ROM, and a RAM that functions as an accessible storage device. It is composed of and. The server processing device 230 has a running history storage process for storing the running history information of the vehicle transmitted from the in-vehicle device 100 by executing a program stored in the ROM by the CPU, and a driver's personnel configuration for each personnel configuration in the car. The driving characteristic analysis process for analyzing the driving characteristic and the information providing process for providing the control parameter guidance information to the vehicle-mounted device 100 based on the personnel configuration in the vehicle on which the vehicle-mounted device 100 is mounted are executed.

First, the travel history storage process will be described. The server processing device 230 stores the travel history information of the vehicle input from the server communication device 210 in the database 220. Further, the server processing device 230 has a database for each gender, each age, each number of people, relationships between people in the vehicle, and intimacy between people in the vehicle, based on the personnel composition included in the travel history information of the vehicle. Statistical processing such as rearranging the travel history information accumulated in 220 can be executed. Further, the server processing device 230 stores the travel history information stored in the database 220 for each travel position (for example, an intersection, a highway, a general road, etc.) based on the vehicle travel position included in the vehicle travel history information. Statistical processing such as grouping can also be executed.

Next, the operation characteristic analysis process will be described. The server processing device 230 analyzes the travel history information stored in the database 220 to identify the optimum control parameters for each personnel configuration in the vehicle. The server processing device 230 analyzes the driving characteristics of each personnel configuration in the vehicle based on the control parameters before identifying the optimum control parameters for each personnel configuration in the vehicle.

An example of operating characteristics will be described. The driving characteristics include driving characteristics caused by the traveling position, driving characteristics caused by other vehicles, and driving characteristics caused by the road condition. Examples of driving characteristics caused by the traveling position include a speed change when driving in a tunnel and a speed change when turning left or right at an intersection. Further, as an example of driving characteristics caused by other vehicles, followability to the preceding vehicle (distance between the preceding vehicle and the vehicle) can be mentioned as an example. Further, as an example of driving characteristics caused by the road condition, a speed change on a slope road (slope) and a speed change due to a vehicle width change can be mentioned as an example.

First, the server processing device 230 executes a clustering process on the travel history information of the vehicle, and groups the travel history information for each travel position of the vehicle. For example, the server processing device 230 groups travel history information for each travel position, such as travel history information around an intersection and travel history information on a slope with a slope. This makes it possible to specify the optimum control parameters for each personnel configuration in the vehicle with respect to a specific location. The grouping method is not particularly limited, and may be grouped by road type (expressway, general road, etc.) or by a specific place (intersection, etc.) and other areas. good.

Next, the server processing device 230 executes a clustering process on the grouped travel history information for each parameter (for each number of people, each gender, each age, between people) that constitutes the information of the personnel composition in the vehicle. By relationship, by intimacy between people), and further group. Then, the server processing device 230 executes statistical processing for each grouped group to analyze the tendency of the operating characteristics. The server processing device 230 calculates a combination of the number of people in the vehicle, gender, age, relationships between people, and intimacy between people according to a specific driving characteristic as a feature amount. The server processing device 230 calculates the feature amount for each operation characteristic by repeating the above-mentioned processing for each operation characteristic.

Then, the server processing device 230 associates the operation characteristics with the control parameters by specifying the control parameters corresponding to each operation characteristic.

Further, the server processing device 230 repeats the above-mentioned analysis process at predetermined cycles, that is, every time the latest vehicle travel history information is accumulated in the database 220. This makes it possible to learn the relationship between the personnel composition of the vehicle and the control parameters. Then, when the distribution of the analysis results in each cycle falls within a predetermined range, the server processing device 230 determines that the fluctuation of the tendency of the control parameters has converged, and determines the number of people, gender, age, and the relationship between persons. Identify the optimal control parameters according to the combination of intimacy between people. The method of analyzing the travel history information of the vehicle is not limited to the above-mentioned method, and the server processing device 230 can appropriately use the technique of the analysis method at the time of filing the application.

When the analysis of the vehicle travel history information is completed, the server processing device 230 has the optimum control parameters for each personnel configuration in the vehicle, feature quantities in each driving characteristic (number of people, gender, age, relationships between persons, and interpersonal relationships). Each of the combinations of intimacy) is stored in the database 220.

Next, the information provision process will be described. First, the server processing device 230 determines from the information transmitted from the in-vehicle device 100 whether or not there is a person who has previously boarded the vehicle in the current vehicle. The server processing device 230 determines whether or not there is an experienced rider from at least one of the captured image of the vehicle-mounted camera 110 and the voice information of the vehicle-mounted microphone 120 in the personnel configuration in the vehicle, and the ride-experienced person excluding the driver. When even one passenger is included as a passenger, the personnel composition in the vehicle including the passenger who has experienced the ride is extracted from the database 220. Then, the server processing device 230 extracts a control parameter having a transmission history to the in-vehicle device 100 from the control parameters corresponding to the extracted personnel configuration. The server processing device 230 identifies the extracted control parameters as the optimum control parameters and uses them as control parameter guidance information.

Next, a case where there is no experienced rider in the current vehicle will be described. In this case, the server processing device 230 identifies the optimum control parameter for the current personnel configuration in the vehicle and uses it as control parameter guidance information. For example, when the information on the current personnel configuration in the vehicle is input from the in-vehicle device 100, the server processing device 230 refers to the analysis result of the vehicle travel history information stored in the database 220. Then, when the analysis result includes the optimum control parameter for the current personnel configuration in the vehicle, the server processing device 230 specifies the control parameter as the optimum control parameter.

On the contrary, when the analysis result of the travel history information for the vehicle does not include the optimum control parameter, the server processing device 230 controls the optimum control for the personnel configuration in the vehicle similar to the current personnel configuration in the vehicle. Determine if the parameter exists. The server processing device 230 identifies and controls the optimal control parameters for the current in-vehicle personnel configuration based on at least one of the current in-vehicle relationships and the intimacy between the current in-vehicle personnel. It is used as guidance information.

For example, as shown in the example shown in FIG. 2A, the current personnel composition in the car is "1 male in 20s, 1 female in 30s, 1 male in 50s, 1 male in 60s". A total of four people, the relationship between these people is a family relationship, and the intimacy is high. " If the optimum control parameter corresponding to this personnel configuration does not exist in the database 220, the server processing device 230 changes either the relationship between the persons in the vehicle or the intimacy between the persons in the vehicle to present. Generate a personnel composition similar to the personnel composition in the car. Then, the server processing device 230 determines whether or not there is an optimum control parameter for the generated similar personnel configuration. In the case of the above example, for example, the server processing device 230 changes the intimacy from "high" to "normal" and "male in his twenties: one, female in his thirties: one, male in his fifties: one". , Male in his 60s: 1 person, 4 people in total, the relationship between these people is a family relationship, and the intimacy is normal. " Then, when the analysis result includes the optimum control parameter for the personnel configuration similar to the current personnel configuration in the vehicle, the server processing device 230 specifies the control parameter as the optimum control parameter.

Further, when either one of the relationship between the persons in the vehicle and the intimacy between the persons in the vehicle transmitted from the in-vehicle device 100 is missing for some reason, the server processing device 230 performs the above-mentioned processing. , Can be complemented for missing parameters. As a result, even if information on either one of the current relationship between people in the car and the intimacy between the current people in the car is missing, or even if the estimation accuracy is low, the current number of people in the vehicle The optimum control parameters for the configuration can be specified.

The server processing device 230 transmits the control parameter guidance information obtained by each of the above-mentioned processes to the in-vehicle device 100 via the server communication device 210. By displaying the received control parameter guidance information on the vehicle-mounted display 150, the vehicle-mounted device 100 displays information on the optimum control parameters for the current personnel configuration in the vehicle or the optimum control provided in the past to the person in the vehicle. Parameter information can be presented.

The method of presenting the control parameter guidance information is not particularly limited. As an example of the presentation method, there is a method of presenting as specific driving support to the driver, "Please reduce the vehicle speed to XX km / h". In addition, as an example of the presentation method, "It is recommended to reduce the vehicle speed to XX km / h. Do you want to reduce the vehicle speed to the recommended speed?" Be done. In the case of this example, when the driver selects to change the control parameter via the in-vehicle operating device group 130, the in-vehicle control device 170 automatically changes to the optimum control parameter in the in-vehicle operating device group 130. Each included drive may be controlled.

Next, with reference to FIG. 3, the operation until the vehicle-mounted device 100 transmits the travel history information of the vehicle to the data center 200 will be described. FIG. 3 is a flowchart of the vehicle-mounted device 100 transmitting vehicle travel history information to the data center 200. The processing of the flowchart shown in FIG. 3 is executed by the in-vehicle device 100 mounted on each vehicle. Further, the in-vehicle device 100 repeatedly executes the operation of the flowchart shown in FIG. 3 at predetermined cycles.

First, in step S101, the vehicle-mounted control device 170 acquires an image captured in the vehicle from the vehicle-mounted camera 110, and acquires voice information from the vehicle-mounted microphone 120. When a plurality of vehicle-mounted cameras 110 are provided in the vehicle-mounted device 100, the vehicle-mounted control device 170 acquires a captured image from each vehicle-mounted camera 110. Further, when a plurality of vehicle-mounted microphones 120 are provided for each seat, the vehicle-mounted control device 170 acquires voice information from each vehicle-mounted microphone 120.

In step S102, the vehicle-mounted control device 170 estimates the characteristics of a person existing in the vehicle based on the captured image in the vehicle acquired in step S101. The characteristics of the person in the car include the gender of the person in the car and the age of the person in the car. When a plurality of people are present in the vehicle, the in-vehicle control device 170 estimates the characteristics one by one. Further, in this step, the in-vehicle control device 170 detects a person existing in the vehicle from the captured image and calculates the number of people in the vehicle.

In step S103, the vehicle-mounted control device 170 estimates the relationship between the persons existing in the vehicle based on the voice information in the vehicle acquired in step S101. Further, in this step, the in-vehicle control device 170 estimates the intimacy between the persons existing in the vehicle based on the voice information in the vehicle acquired in step S101. Since the accuracy of estimating the relationship and intimacy between people in the vehicle is relatively high when there are many conversations, the in-vehicle control device 170 processes this step after a predetermined elapsed time has elapsed from step S102. It is preferable to carry out.

In step S104, the in-vehicle control device 170 estimates the personnel configuration in the vehicle. The personnel composition in the car includes the number of people in the car calculated in step S102, the characteristics of the person in the car estimated in the same step, the relationship between the people in the car estimated in step S103, and the number of people in the car. Intimacy is associated (see FIGS. 2A and 2B).

In step S105, the vehicle-mounted control device 170 acquires control parameters related to the traveling of the vehicle. The in-vehicle control device 170 acquires control parameters based on the detection results from the in-vehicle sensor group 140. Further, in this step, the in-vehicle control device 170 acquires the position information of the vehicle from, for example, the navigation device based on the travel path of the vehicle that has been traveled so far.

In step S106, the vehicle-mounted control device 170 generates vehicle travel history information. The in-vehicle control device 170 correlates the personnel configuration in the vehicle estimated in step S104, the control parameters of the vehicle specified in step S105, and the traveling position of the vehicle acquired in the same step, and obtains the traveling history information of the vehicle. As a result, the personnel composition in the vehicle and the control parameters in the personnel composition are associated with each other.

In step S107, the vehicle-mounted control device 170 transmits the travel history information of the vehicle generated in step S106 to the data center 200. When step S107 is completed, the process until the vehicle-mounted device 100 transmits the vehicle travel history information to the data center 200 is completed.

Next, with reference to FIG. 4, the operation of specifying the optimum control parameter for each personnel configuration will be described. FIG. 4 is a flowchart for explaining a process of specifying the optimum control parameter for each personnel configuration. The processing of the flowchart shown in FIG. 4 is executed by the server processing device 230 of the data center 200.

In step S201, the server processing device 230 collects the vehicle travel history information transmitted from the vehicle-mounted device 100 and stores it in the database 220.

In step S202, the server processing device 230 analyzes the driving characteristics of the driver for each personnel configuration from the vehicle traveling history information for each traveling position of each vehicle stored in the database 220 in step S201. For example, the server processing device 230 executes a clustering process on the travel history information of the vehicle for a specific travel position, and for each parameter (for each number of people, for each gender, for each age, which constitutes the information of the personnel composition in the vehicle). Relationships between people in the car, intimacy between people in the car) Group. Then, the server processing device 230 analyzes the tendency of the driving characteristics for each grouped group, and the number of people, the gender, the age, the relationship between the persons, and the intimacy between the persons according to one driving characteristic. Calculate the feature amount for one driving characteristic that can be expressed by the combination of. The server processing device 230 calculates the feature amount for each operation characteristic by executing the above-mentioned processing for each operation characteristic. The server processing device 230 associates the operation characteristics with the control parameters by specifying the control parameters corresponding to each operation characteristic.

In step S203, the server processing device 230 identifies the optimum control parameter for each personnel configuration based on the analysis result obtained in step S202.

In step S204, the server processing apparatus 230 stores the analysis result obtained in step 202 and the optimum control parameters for each personnel configuration specified in step S203 in the database 220. When step S204 is completed, the process of the server processing device 230 specifying the optimum control parameter for each personnel configuration is completed.

Next, with reference to FIGS. 5A and 5B, the process from getting into the vehicle to providing the optimum control parameters for the personnel configuration in the vehicle will be described. 5A and 5B are flowcharts for explaining the process from getting into the vehicle to providing the optimum control parameters for the personnel configuration in the vehicle. The processes of steps S301 to S306 and S308 shown in FIG. 5A and the processes of steps S313 to S315 shown in FIG. 5B are executed by the vehicle-mounted device 100 mounted on the specific vehicle. Further, the processes of steps S307 and steps S309 to S312 shown in FIG. 5B are executed by the server processing device 230 of the data center 200.

In step S301, the vehicle-mounted control device 170 acquires the current captured image of the vehicle interior from the vehicle-mounted camera 110. Further, the vehicle-mounted control device 170 acquires the current voice information in the vehicle from the vehicle-mounted microphone 120. The in-vehicle control device 170 acquires the current captured image of the inside of the vehicle from the in-vehicle camera 110 and the voice information from the in-vehicle microphone 120, for example, at the timing when one or more people get on the vehicle or when the vehicle starts. start. This step corresponds to step S101 in FIG.

In step S302, the vehicle-mounted control device 170 estimates the characteristics of a person present in the current vehicle based on the image captured in the current vehicle acquired in step S301. This step corresponds to step S102 in FIG.

In step S303, the in-vehicle control device 170 determines whether or not a person who has boarded in the past is on board from at least one of the current captured image and voice information in the vehicle acquired in step S301. If no person with past riding experience is detected in the current vehicle, the process proceeds to step S304, and if a person with past riding experience is detected, the process proceeds to step S309.

In step S304, the in-vehicle control device 170 estimates the relationship between the people in the current vehicle based on the voice information in the current vehicle acquired in step S301. Further, in this step, the in-vehicle control device 170 estimates the intimacy between people in the current vehicle. This step corresponds to step S103 in FIG.

In step S305, the in-vehicle control device 170 estimates the current personnel configuration in the vehicle. This step corresponds to step S104 in FIG.

In step S306, the vehicle-mounted control device 170 transmits the information on the current personnel configuration in the vehicle estimated in step S305 to the data center 200.

If a person who has boarded in the past is detected in step S303, the process proceeds to step S309. In step S309, the vehicle-mounted control device 170 transmits the information of the person who has a riding experience detected in step S303 to the data center 200.

When step 306 or step S309 is completed, the vehicle-mounted device 100 waits until a response from the data center 200 arrives.

In step S306, when the information on the current personnel configuration in the vehicle is transmitted from the vehicle-mounted device 100 to the data center 200, the process proceeds to step S307. In step S307, the server processing device 230 receives the information on the current personnel configuration in the vehicle transmitted from the vehicle-mounted device 100 in step S306 via the server communication device 210.

In step S308, the server processing device 230 extracts the optimum control parameters from the database 220 for the current personnel configuration in the vehicle received in step S307. The server processing device 230 uses the extracted optimum control parameters as control parameter guidance information.

When the information of the person who has a riding experience is transmitted from the vehicle-mounted device 100 to the data center 200 in step S309, the process proceeds to step S310. In step S310, the server processing device 230 receives the information of a person who has a riding experience transmitted from the vehicle-mounted device 100 in step S309 via the server communication device 210.

In step S310, the server processing device 230 extracts information on the personnel composition in the vehicle including a person who has experience of riding from the database 220. The server processing device 230 extracts a control parameter having a transmission history to the in-vehicle device 100 from the extracted control parameters corresponding to the personnel configuration in the vehicle. The server processing device 230 uses the optimum control parameters provided in the past as control parameter guidance information.

In step S312, the server processing device 230 transmits the control parameter guidance information created in step S308 or step S311 to the vehicle-mounted device 100.

In step S313, the vehicle-mounted control device 170 receives control parameter guidance information from the data center 200 via the vehicle-mounted communication device 160.

In step S314, the vehicle-mounted control device 170 displays on the vehicle-mounted display 150 that the control parameter guidance information has been received, and prompts a person in the vehicle to select whether or not to use the control parameters included in the control parameter guidance information. For example, the vehicle-mounted control device 170 causes the vehicle-mounted display 150 to display various control parameters included in the control parameter guidance information and display a selection screen for whether or not to use the vehicle-mounted control device 170. If the person in the vehicle selects to use the control parameter guidance information, the process proceeds to step S315 , and if the person in the vehicle selects not to use the control parameter guidance information, the information provision process ends.

In step S315, the in-vehicle control device 170 outputs the control parameter guidance information received in step 313. The in-vehicle control device 170 outputs the optimum control parameters included in the control parameter guidance information to the in-vehicle operation device group 130. For example, when the passenger includes an elderly person, the in-vehicle control device 170 controls the brake pedal so as to decelerate by a predetermined speed further than the legal speed when turning left or right at an intersection. This makes it possible to realize driving without imposing an excessive load on the elderly passengers. Further, the information providing system 1 of the present embodiment has the following effects not only for the passenger but also for the driver. For example, when the passenger is a friend, the in-vehicle control device 170 changes the driving characteristic mode of the vehicle so as to switch from the normal mode to the sports mode in the scene of traveling on a mountain road. This makes it possible to realize driving that allows the driver to enjoy driving.

Further, in this step, the vehicle-mounted control device 170 may output the optimum control parameter guidance information provided in the past to the vehicle-mounted operating device group 130. When step S315 is completed, the process from boarding to the provision of the optimum control parameters for the personnel configuration in the vehicle is completed.

As described above, in the present embodiment, the in-vehicle device 100 acquires the captured image in the vehicle from the in-vehicle camera 110 that captures the interior of the vehicle, and obtains the audio information in the vehicle from the in-vehicle microphone 120 that collects the audio in the interior of the vehicle. Based on the voice information in the car, it estimates the relationship between the people in the car, estimates the personnel composition in the car in which the number of people in the car and the relationship between the people in the car are related, and the in-vehicle sensor. The control parameters related to the traveling in the vehicle are acquired from the group 140, and the traveling history information of the vehicle in which the personnel configuration in the vehicle and the control parameters are associated with each other is transmitted to the data center 200. In the data center 200, the server processing device 230 stores the vehicle travel history information in the database 220, and analyzes the accumulated vehicle travel history information to specify the optimum control parameters for each personnel configuration in the vehicle. This makes it possible to determine the optimum control parameters of the vehicle in consideration of the passenger.

Further, in the present embodiment, the in-vehicle device 100 estimates the number of people in the vehicle and the gender and age of the person in the vehicle based on the captured image in the vehicle, and the relationship between the persons in the vehicle is based on the voice information in the vehicle. Estimate gender and intimacy between people in the car. Then, the in-vehicle device 100 uses the estimated information as information on the personnel configuration in the vehicle. Thereby, for example, even in a vehicle not equipped with the in-vehicle camera 110 or a vehicle not equipped with the in-vehicle microphone 120, it is possible to estimate the outline of the personnel composition in the vehicle. Further, in a vehicle equipped with both an in-vehicle camera 110 and an in-vehicle microphone 120, it is possible to accurately estimate the personnel configuration in the vehicle.

Further, in the present embodiment, the vehicle-mounted control device 170 acquires the traveling position of the vehicle from the position detection device 142. The control parameters acquired by the vehicle-mounted control device 170 from the vehicle-mounted sensor group 140 include steering angle, accelerator opening, brake opening, sonar sensor detection result, radar sensor detection result, vehicle speed, acceleration, and distance to the preceding vehicle. Distance and driving characteristic modes are included. Then, the in-vehicle control device 170 uses information related to the control parameters indicating the traveling states of these vehicles, the personnel configuration in the vehicle, and the traveling position of the vehicle as the traveling history information of the vehicle. As a result, in the data center 200, the optimum control parameters for each personnel configuration in the vehicle in various driving scenes can be stored in the database 220.

Further, in the present embodiment, the vehicle-mounted device 100 acquires the captured image of the current vehicle interior from the vehicle-mounted camera 110, acquires the voice information of the current vehicle interior from the vehicle-mounted microphone 120, and is based on the voice information of the current vehicle interior. Estimate the relationship between people in the current car, estimate the current personnel composition in the car in which the relationship between the current number of people in the car and the current person in the car is related, and information on the current personnel composition in the car. To the data center 200. In the data center 200, the server processing device 230 selects the optimum control parameter for the current personnel configuration in the vehicle from the optimum control parameters stored in the database 220 and specified for each personnel configuration in the vehicle. It is transmitted to the device 100. In the in-vehicle device 100, the in-vehicle control device 170 outputs to each drive device the control parameters optimal for the current personnel configuration received from the data center 200. As a result, it is possible to drive with the optimum control parameters in consideration of the passenger.

Further, in this embodiment, the server processing device 230 is optimal for the current in-vehicle personnel configuration based on at least one of the current in-vehicle relationships and the current in-vehicle intimacy. The control parameters are extracted from the database 220. Thereby, for example, even if any one of these information is missing for some reason, the optimum control parameter for the current personnel configuration in the vehicle can be extracted.

Further, in the present embodiment, when the in-vehicle device 100 detects a person who has a riding experience in the past from the captured image in the vehicle captured by the in-vehicle camera 110, the in-vehicle device 100 transmits the information of the person who has the riding experience to the data center 200. .. In the data center 200, information on the personnel composition in the vehicle including a person who has experience of riding is extracted from the database 220. Then, the server processing device 230 transmits to the vehicle-mounted device 100 as the optimum control parameter having a transmission history to the vehicle-mounted device 100 among the extracted optimum control parameters corresponding to the personnel configuration in the vehicle. In the vehicle-mounted device 100, the vehicle-mounted control device 170 causes the vehicle-mounted display 150 to display the control parameter guidance information provided in the past. As a result, it is possible to omit the estimation process of the personnel composition in the vehicle for passengers who have experience of riding, and to provide the optimum control parameter guidance information in the vehicle without spending more time after boarding. can.

Further, in the present embodiment, the in-vehicle device 100 prompts a person in the vehicle to select whether or not to provide the optimum control parameter guidance information received from the data center 200 in the vehicle. As a result, the person in the vehicle can use the control parameter guidance information from the data center 200 as needed.

It should be noted that the embodiments described above are described for facilitating the understanding of the present invention, and are not described for limiting the present invention. Therefore, each element disclosed in the above-described embodiment is intended to include all design changes and equivalents belonging to the technical scope of the present invention.

For example, in the above-described embodiment, as a method of presenting the control parameter guidance information, a selection screen for displaying the control parameter guidance information on the in-vehicle display 150 or prompting the driver to select whether or not to use the optimum control parameter is displayed. Although the configuration of displaying on the in-vehicle display 150 has been described as an example, the method of presenting the control parameter guidance information is not limited to this. For example, when the vehicle has a function of automatically driving, the in-vehicle device 100 may output the optimum control parameters received from the data center 200 to each drive device that automatically drives. As a result, the vehicle can be optimally driven for the personnel composition in the specific vehicle in the specific driving scene.

Further, for example, in the above-described embodiment, the configuration for estimating the relationship between the persons in the vehicle based on the voice information from the in-vehicle microphone 120 has been described as an example, but the estimation of the relationship between the persons in the vehicle has been described. A terminal device owned by a person in the vehicle may be used for the above. Examples of terminal devices include devices that can connect to the Internet, such as mobile phones, smartphones, laptop computers, and tablet computers. These terminal devices have ID information that can identify the owner. Since the terminal device can communicate with the data center 200 via the Internet connection, the server processing device 230 identifies the relationship between the persons in the vehicle from the personal information registered as the ID information possessed by the terminal device. Can be done. This makes it possible to improve the accuracy of estimating the relationship between people in the vehicle.

Further, for example, in the above-described embodiment, the server processing device 230 may change the optimum control parameters in the operation characteristic analysis processing based on predetermined predetermined operation rules. For example, when the server processing device 230 determines that the driving characteristics in a specific vehicle personnel configuration tend not to be recognized as driving by a good driver, the server processing device 230 changes the optimum control parameter for the personnel configuration in the vehicle. be able to. This can prevent non-model driving from being performed.

Further, for example, in the above-described embodiment, the relationship between the persons in the vehicle and the intimacy between the persons in the vehicle are estimated based on the voice information of the in-vehicle microphone 120, but based on the captured image of the in-vehicle camera 110. The relationship and the intimacy may be estimated. For example, the in-vehicle control device 170 may estimate the relationship between the persons in the vehicle from the facial expressions of the persons included in the captured image.

Further, for example, in the above-described embodiment, on the vehicle-mounted device 100 side, a configuration for estimating the relationship and intimacy between people in the vehicle and estimating the personnel composition in the vehicle has been described as an example. The data center 200 may be used to estimate the relationships and intimacy between people in the vehicle and to estimate the personnel composition in the vehicle. For example, the vehicle-mounted device 100 transmits the captured image in the vehicle captured by the vehicle-mounted camera 110 and the voice information in the vehicle collected by the vehicle-mounted microphone 120 to the data center 200, and the server processing device 230 side has a relationship between people in the vehicle. And intimacy, and the personnel composition in the car may be estimated.

Further, for example, in the above-described embodiment, the information processing device according to the present invention has been described by taking the configuration of the vehicle-mounted control device 170, the database 220, and the server processing device 230 constituting the information providing system 1 as an example. The present invention is not limited to this. For example, the in-vehicle device 100 may include the database 220 and the server processing device 230 included in the data center 200.

Further, for example, in the above-described embodiment, the controller according to the present invention has been described by taking the configuration of the in-vehicle control device 170 and the server processing device 230 as an example, but the present invention is not limited thereto.

1 ... Information provision system 100 ... In-vehicle device 110 ... In-vehicle camera 120 ... In-vehicle microphone 130 ... In-vehicle operation device group 140 ... In-vehicle sensor group 150 ... In-vehicle display 160 ... In-vehicle communication device 200 ... Data center 210 ... Server communication device 220 ... Database 230 … Server processing device

Claims (11)

An information processing method executed by a controller using a storage device.
At least one of the captured image inside the vehicle output from the camera that captures the interior of the vehicle and the audio information inside the vehicle output from the microphone that acquires the sound inside the vehicle is acquired.
Based on the acquired information, the relationship between the persons existing in the vehicle is estimated, and the relationship is estimated.
Estimate the personnel composition in the vehicle in which the number of people in the vehicle and the relationship between the persons in the vehicle are related.
The control parameters related to the running of the vehicle are acquired from the sensor that detects the running state of the vehicle, and the control parameters are acquired.
The traveling history of the vehicle in which the personnel configuration in the vehicle and the control parameter are associated with each other is stored in the storage device.
By associating the driver's driving characteristics for each personnel configuration in the vehicle specified from the accumulated travel history with the control parameters corresponding to the driving characteristics, the control parameters corresponding to the personnel configurations in the vehicle are associated with each other. An information processing method for specifying each of the personnel configurations in the vehicle . The information processing method according to claim 1.
The personnel composition in the vehicle includes the number of people in the vehicle, the gender and age of the person in the vehicle, the relationship between the persons in the vehicle, and the intimacy between the persons in the vehicle.
Based on the captured image in the car, the number of people in the car and the gender and age of the person in the car are estimated.
An information processing method for estimating the relationship between people in a vehicle and the intimacy between people in the vehicle based on the voice information in the vehicle. The information processing method according to claim 2.
The traveling position of the vehicle is acquired from the sensor, and the traveling position of the vehicle is acquired.
The control parameters are the detection result of the steering angle sensor, the detection result of the accelerator opening sensor, the detection result of the brake opening sensor, the detection result of the sonar device, the detection result of the radar device, and the detection result of the speed sensor. And the detection result of the acceleration sensor, the distance between the vehicle and the preceding vehicle, and information on at least one of the driving characteristic modes.
The travel history is an information processing method including the personnel configuration in the vehicle, the control parameters, and the travel position. The information processing method according to any one of claims 1 to 3.
An information processing method for estimating a relationship between people in a vehicle based on a terminal device owned by the person in the vehicle. The information processing method according to any one of claims 1 to 4.
At least one of the image captured in the current vehicle output from the camera and the audio information in the current vehicle output from the microphone is acquired.
Based on the acquired information, the current relationship between the persons in the car is estimated, and
Estimate the current personnel composition in the vehicle in which the current number of people in the vehicle and the current relationship between the persons in the vehicle are related.
From the control parameters specified for each personnel configuration in the vehicle, select the control parameter corresponding to the current personnel configuration in the vehicle.
An information processing method that outputs the selected control parameter. The information processing method according to claim 5 .
When a person who has been in the vehicle in the past is detected from the captured image in the current vehicle or the voice information in the current vehicle, the person in the current vehicle is based on the relationship between the persons in the vehicle estimated in the past. An information processing method that estimates the relationships between people. The information processing method according to claim 5 or 6 .
The control parameter corresponding to the current personnel configuration in the vehicle is output according to the selection by the person existing in the vehicle as to whether or not to use the control parameter corresponding to the current personnel configuration in the vehicle. Information processing method to switch whether to do or not. The information processing method according to any one of claims 5 to 7.
Based on at least one of the captured image in the current vehicle and the audio information in the current vehicle, it is determined whether or not there is a rider who has experience in the vehicle in the past.
When it is determined that there is an experienced rider other than the driver, there is a transmission history to the device mounted on the vehicle among the control parameters corresponding to the personnel configuration in the vehicle including the experienced rider. The control parameter is specified as the control parameter corresponding to the current personnel configuration in the vehicle.
If it is determined that the rider does not exist, it is based on at least one of the relationship between the persons in the current vehicle and the intimacy between the persons in the current vehicle included in the personnel composition in the current vehicle. An information processing method for specifying the control parameter corresponding to the current personnel configuration in the vehicle. The information processing method according to claim 8.
When it is determined that the rider does not exist and the control parameter corresponding to the personnel configuration in the current vehicle does not exist, the relationship between the persons in the current vehicle and the person in the current vehicle are present. An information processing method in which one of the intimacy is changed to create a personnel composition similar to the personnel composition in the current vehicle. The information processing method according to claim 9.
An information processing method for specifying the control parameter corresponding to the personnel configuration similar to the current personnel configuration in the vehicle as the control parameter corresponding to the current personnel configuration in the vehicle. A controller that executes information processing and
Equipped with a storage device
The controller
Acquire at least one of the captured image in the vehicle output by the camera that captures the interior of the vehicle or the audio information in the vehicle output by the microphone that acquires the audio in the interior of the vehicle.
Based on the acquired information, the relationship between the persons existing in the vehicle is estimated, and the relationship is estimated.
Estimate the personnel composition in the vehicle that associates the number of people in the vehicle with the relationship.
The control parameters related to the running control of the vehicle are acquired from the sensor that detects the running state of the vehicle, and the control parameters are acquired.
The traveling history in which the personnel configuration in the vehicle and the control parameters are associated with each other is stored in the storage device.
By associating the driver's driving characteristics for each personnel configuration in the vehicle specified from the accumulated travel history with the control parameters corresponding to the driving characteristics, the control parameters corresponding to the personnel configurations in the vehicle are associated with each other. An information processing device that specifies the above for each personnel configuration in the vehicle .

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