JP2019104354A - Information processing method and information processor - Google Patents

Abstract

To provide an information processing method and an information processor that can determine optimum control parameters in consideration of passengers.SOLUTION: The information processing method includes: acquiring at least one of a captured image of the inside of a vehicle output by a camera imaging a vehicle interior and voice information inside the vehicle output by a microphone acquiring voices in the vehicle interior; estimating relationships among persons existing in the vehicle on the basis of the acquired information; estimating personnel composition in the vehicle in which the number of persons in the vehicle and relationships among persons in the vehicle are associated with each other; acquiring, from a sensor detecting the traveling state of the vehicle, control parameters related to the traveling of the vehicle; accumulating, in a storage device, traveling histories of the vehicle in which the personnel composition in the vehicle and the control parameters are associated with each other; and specifying optimum control parameters depending on personnel composition in the vehicle by analyzing the accumulated traveling histories.SELECTED DRAWING: Figure 1

Description

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

  In a driving support system that performs driving support by vehicle control, a point for which vehicle control is to be performed is acquired as a learning point, and in a configuration in which vehicle control is performed when the vehicle travels the learning point again, a learning point in the evaluation target section There is known a method of displaying on the display unit a learning rate obtained by dividing the number of times of vehicle control performed by the control point, which is the number of points where vehicle control should be performed in the evaluation target section. (Patent Document 1).

JP, 2013-210328, A

  Generally, the driving performed when only the driver is riding may be different 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 more cases where the optimum driving characteristics differ depending on the number of passengers, the age, and the like. In the prior art, driving assistance suitable for the driver's own driving characteristics is provided without regard to the passenger. Therefore, there is a problem that it is not possible to determine an optimal control parameter of the vehicle in consideration of the passenger.

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

  The present invention acquires at least one of an in-vehicle captured image output from a camera for capturing an interior of a vehicle and at least one of in-car audio information output from a microphone for acquiring an audio of the vehicle interior. Based on the relationship between the persons present in the vehicle, the relationship between the number of persons in the vehicle and the relationship between the persons in the vehicle is estimated, and the personnel configuration in the vehicle is estimated. The control parameters related to the travel of the vehicle are acquired, the travel history of the vehicle in which the personnel configuration in the car is associated with the control parameter is stored in the storage device, and the control is optimized for each personnel configuration in the car by analyzing the accumulated travel history. The problem is solved by specifying the parameters.

  According to the present invention, an optimal control parameter can be determined in consideration of a passenger.

FIG. 1 is a block diagram of a driving knowledge extraction system according to a first embodiment. FIG. 2 is a diagram for explaining an in-vehicle personnel configuration estimation process. FIG. 3 is a flowchart until the in-vehicle device transmits the traveling history information of the vehicle to the data center. FIG. 4 is a flow chart for explaining a process of specifying an optimal control parameter for each personnel configuration. FIG. 5A is a flow chart for explaining a process from getting on the vehicle to providing the control parameter optimum for the personnel configuration in the vehicle. FIG. 5B is a flow chart for explaining a process from getting on the vehicle to providing the control parameter optimum for the personnel configuration in the vehicle.

  Hereinafter, embodiments of the present invention will be described based on the drawings.

  In the present embodiment, the information processing apparatus according to the present invention is applied to an on-vehicle apparatus 100 mounted on a vehicle and an information providing processing system cooperating with a data center 200 as an example.

  FIG. 1 is a block diagram of the information providing system 1. The information providing system 1 of the present embodiment includes an on-vehicle device 100 and a data center 200. The information providing system 1, the in-vehicle apparatus 100, and each of the apparatuses included in the information providing system 1 are arithmetic processing devices such as a CPU and a computer that executes arithmetic processing.

  First, the in-vehicle apparatus 100 will be described. The in-vehicle apparatus 100 according to the present embodiment includes an in-vehicle camera 110, an in-vehicle microphone 120, an in-vehicle operation 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. The respective devices constituting the in-vehicle device 100 are connected by a controller area network (CAN) or another in-vehicle LAN to exchange information with each other.

  The on-vehicle camera 110 is provided in the room of the vehicle and captures an image of the room. The on-vehicle camera 110 outputs the captured image to the on-vehicle control device 170. The installation position of the on-vehicle camera 110 and the number of the on-vehicle cameras 110 are not particularly limited. For example, the on-vehicle camera 110 is provided on an instrumental panel and captures an image of a person sitting in the front seat. Also, for example, the on-vehicle camera 110 is provided in the vicinity of the rearview mirror, and captures an image of a person sitting on the rear seat.

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

  The in-vehicle operation device group 130 is configured of operation devices that can be operated by the driver. A steering wheel, an accelerator pedal, a brake pedal, a shift lever, a turn signal switch that blinks left and right blinker lamps (direction indicators), a hazard switch that blinks a hazard lamp, a hazard switch that blinks a hazard lamp, and a wiper At least a wiper switch and a navigation device for setting a traveling route of a vehicle. The turn signal switch also has a function for operating a headlamp (also referred to as 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 capable of changing the traveling characteristic mode of the vehicle, the on-vehicle operation device group 130 also includes an apparatus (for example, a switch) for setting the traveling characteristic mode of the vehicle. Examples of the travel characteristic mode of the vehicle include a normal mode, a snow mode, a sport mode, and a low fuel consumption mode (eco mode). When the driver sets the traveling characteristic mode, the control parameter related to the traveling of the vehicle is set to a value suitable for the traveling scene corresponding to the set traveling characteristic mode. In addition, the detail of the control parameter regarding driving | running | working of a vehicle is mentioned later.

  For example, the snow mode is a traveling characteristic mode corresponding to traveling on a traveling road having a road surface friction coefficient including a snow road or a frozen road that is less than or equal to a predetermined value. When the snow mode is set, the transmission gear ratio is set to a high speed side compared to the normal mode, and the vehicle can travel so as to reduce the driving force. Further, for example, the sport mode is a traveling characteristic mode corresponding to traveling on an uphill or downhill. When the sport mode is set, the engine rotational speed is set to a high speed side as compared with the normal mode, and the vehicle can accelerate rapidly even on an uphill.

  The on-vehicle sensor group 140 is configured of sensors, devices, and the like that detect the traveling state of the vehicle. The on-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 sensor, a brake opening sensor, a speed sensor, an acceleration sensor, and an attitude sensor. The steering angle sensor detects a steering angle, a steering speed, and a steering acceleration, the accelerator opening sensor detects an accelerator opening, and the brake opening sensor detects a brake opening. In addition, the speed sensor detects the moving speed of the vehicle, and the acceleration sensor detects at least one of the acceleration in the longitudinal direction of the vehicle and the acceleration in the lateral direction (left and right direction) of the vehicle. The attitude sensor detects information on the attitude 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 capable of changing the traveling characteristic mode of the vehicle, the state detection device 141 detects the type of the traveling characteristic mode of the vehicle set by the driver via the on-vehicle operation device group 130.

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

  The object detection device 143 is a device that detects the situation around the vehicle. The object detection device 143 at least includes an imaging device such as a camera, a sonar device, and a radar device. The imaging device detects the presence of an object including an obstacle present around the vehicle, its location, and the distance from the vehicle to the object. The 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. The sonar device and the radar device have similar functions. As a radar apparatus, a millimeter wave radar, a laser radar, an ultrasonic radar etc. are mentioned as an example. In the present embodiment, the object detection device 143 measures the distance between the host vehicle and the preceding vehicle (the distance between the host vehicle and the preceding vehicle) from the position where the host vehicle is traveling and the position where the leading vehicle is traveling. Do.

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

  Also, information (hereinafter referred to as control parameter guidance information) for guiding a control parameter optimum for the present personnel configuration in the vehicle from the data center 200 via the in-vehicle communication device 160 and the in-vehicle control device 170 is input to the in-vehicle display 150 Be done. The on-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 that can communicate with the server communication device 210 of the data center 200 via a telephone network, the Internet network, or the like. The in-vehicle communication device 160 receives information on the configuration of personnel in the vehicle and information on the traveling history of the vehicle (hereinafter referred to as traveling history information on the vehicle), which will be described later. Send to device 210. The in-vehicle communication device 160 can include the information in the probe information, and may transmit the information as the probe information to the server communication device 210. Further, the in-vehicle communication device 160 receives control parameter guidance information from the server communication device 210, and outputs the received control parameter guidance information to the in-vehicle control device 170. In addition, the detail of the information of the personnel configuration in the car and the traveling history information of the vehicle will be described later.

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

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

  Specifically, the on-vehicle control device 170 according to the present embodiment generates the traveling history information of the vehicle by executing the following processing. The in-vehicle control device 170 estimates in-vehicle person feature estimation processing for estimating the feature of a person in the vehicle, in-vehicle person relationship processing for estimating a relationship between persons in the vehicle, and in-vehicle personnel configuration estimation for estimating the personnel configuration in the vehicle. A process, a control parameter acquisition process for acquiring control parameters related to traveling of the vehicle, and a traveling history generation process for generating traveling history information of the vehicle based on the processing results are executed.

  The on-vehicle control device 170 executes each function by the cooperation of the above-described hardware and software for executing the above-described functions or to execute each process.

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

  The accuracy of the age estimated by the on-board controller 170 is not particularly limited. The in-vehicle control device 170 can appropriately change the accuracy of the age to be estimated according to the image processing capability and the imaging accuracy of the in-vehicle camera 110. For example, the on-vehicle control device 170 stores in advance in the storage device a feature pattern categorized in units of 10 years, such as "10's" in the range of 10 to 19 years and "20's" in the range of 20 to 29 years. By doing this, it is possible to estimate the age of the person in the car. The in-vehicle person feature estimation process is not limited to the method described above, and the in-vehicle control device 170 can appropriately use the in-vehicle person feature estimation process known at the time of filing the present application.

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

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

  A keyword for estimating the relationship between persons will be described. For example, the storage device described above stores specific keywords for classifying conversation contents into “family relationship”, “job relationship”, “friend relationship”, and “other relationship”. Examples of keywords associated with "family relationship" include family calls (eg, "father", "mother", "old brother", "old sister", "grandpa", "grandma", etc.) as an example Be In addition, keywords associated with “job relationship” include job title (for example, “president”, “section manager”, “section manager”, etc.), company name (eg, “○ Co., Ltd., etc.”, business terms) For example, “Contract,” “Trading,” “Meeting,” “Promise,” “Delivery date,” etc. may be mentioned as an example. Also, as a keyword associated with "friendship", a television program name, a music title, a sports term, and a restaurant name may be mentioned as an example. Further, with regard to the keywords associated with the “other relationship”, specific keywords are appropriately set by the vehicle occupant or the system side.

  When the number of times of detection of a specific keyword exceeds a predetermined number, the in-vehicle control device 170 estimates the relationship corresponding to the detected keyword as the relationship between persons in the vehicle. The predetermined number of times is not particularly limited, but is preferably an experimentally determined value. The method of specifying the relationship between persons in the vehicle from the detected keyword is not particularly limited. When a plurality of specific keywords are detected across a plurality of relationships, the in-vehicle control device 170 first detects the relationship corresponding to a keyword whose number of times of detection exceeds a predetermined number, and the relationship between persons in the vehicle It may be estimated. Further, the in-vehicle control device 170 estimates a relationship corresponding to a relationship in which the number of types of detected keywords is the largest or a relationship in which the total number of detected keywords is the largest as the relationship between persons in the vehicle. It is also good.

  Next, the on-vehicle control device 170 estimates closeness between persons in the vehicle. When the on-vehicle control device 170 estimates the relationship between persons in the vehicle from the conversation content, the in-vehicle control device 170 estimates closeness between persons in the vehicle. The closeness between persons in the vehicle is the closeness based on the driver, and is the closeness between the driver and the passenger (goodness between the driver and the passenger).

  The in-vehicle control device 170 extracts the speech of a specific person (from the start of the speech to the end of the speech) from the conversation content in the car. Then, the in-vehicle control device 170 estimates closeness between persons in the vehicle from the wording in the extracted statement. For example, the on-vehicle control device 170 stores, in a storage device such as a ROM, a feature pattern of wording that is a predetermined feature pattern of wording and can determine intimacy between persons. Then, the in-vehicle control device 170 can estimate closeness between persons in the vehicle by collating the speech of a specific person with the feature pattern of wording.

  A feature pattern of wording for estimating closeness between persons will be described. For example, in the above-described storage device, a feature pattern of wording for classifying the closeness into three patterns of “high”, “normal”, and “low” is stored. The better the relationship between the driver and the passenger, the higher the closeness is estimated. As characteristic patterns of wording, wording using honorifics (respect words, humble words, polite words), calling the other person when calling (for example, calling only by name, calling only by last name, adding job title to last name) Etc.) are given as an example.

  The on-vehicle control device 170 performs pattern matching of the speech of the specific person and the wording feature pattern, and estimates the closeness with a high matching ratio as the closeness between the persons in the vehicle. The method of estimating closeness from conversation content is not limited to the above-described method, and the on-vehicle control device 170 may appropriately use the closeness estimation method known at the time of filing the present application.

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

  An example of the processing result of the in-vehicle personnel configuration estimation process will be described with reference to FIGS. 2 (A) and 2 (B). FIGS. 2A and 2B are diagrams for explaining the in-vehicle personnel configuration estimation process. FIG. 2A shows the processing result of the on-vehicle control device 170 when four persons including the driver are on the vehicle. In this example, the in-vehicle control device 170 first detects from the captured image of the in-vehicle camera 110 that the number of people in the vehicle is four. Next, as shown in FIG. 2A, the in-vehicle control device 170 executes the above-described in-vehicle person feature estimation process for each of four people, and "20's male: 1 person, 30's woman" The characteristics of the person in the car are estimated as follows: 1 person, 50's male: 1 person, 60's male: 1 person, 4 people in total. Furthermore, the in-vehicle control device 170 estimates the relationship between persons in the vehicle as a family relationship from the conversation contents in the vehicle by the in-vehicle person relationship estimation processing described above, and the wording of each person makes the person in the vehicle It is estimated that closeness between them is high. Finally, the in-vehicle control device 170 associates the detection result and the estimation result with each other, saying, “20's male: 1 person, 30's female: 1 person, 50's male: 1 person, 60's male: 1 person in total 4 The name, the relationship between these persons is a family relationship, and the closeness is high.

  Moreover, FIG. 2 (B) has shown the process result of the vehicle-mounted control apparatus 170 in case two persons including a driver get on. 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-described in-vehicle person feature estimation process on the two detected persons, as shown in FIG. As shown in (B), the characteristics of the person in the car are estimated as "30's male: 1 person, 30's male: 1 person in total: 2". Then, the in-vehicle control device 170 estimates the relationship between persons in the vehicle as a work relationship by the above-described in-vehicle person relation estimation processing, and from the wording of each person, it is assumed that closeness between persons in the vehicle is low. presume. Finally, the in-vehicle control device 170 associates the detection result and the estimation result, saying that “30's male: 1 person, 30's male: 1 person: 4 people in total, the relationship between these persons is a work relationship. The intimacy is low, and estimate the personnel composition in the car.

  When the in-vehicle control unit 170 estimates the in-vehicle personnel configuration, the in-vehicle control device 170 transmits the in-vehicle personnel configuration information to the server communication device 210 of the data center 200 via the in-vehicle communication device 160. The in-vehicle control device 170 can also include the captured image itself of the in-vehicle camera 110 and the audio information itself of the in-vehicle microphone 120 in the information of the personnel configuration in the vehicle. Thereby, the server processing device 230 of the data center 200 described later can determine whether the passenger is a person who has a history of getting on in the past from the captured image or the voiceprint data of the voice information.

  Referring back to FIG. 1 again, control parameter acquisition processing of the on-vehicle control device 170 will be described. The on-vehicle control device 170 acquires control parameters related to the traveling of the vehicle from the on-vehicle sensor group 140. The control parameter in the present embodiment is a control parameter indicating the traveling state of the vehicle detected by the on-vehicle 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), the detection result of the sonar device (vehicle The distance between the vehicle and the surrounding object), the detection result of the radar device (the distance between the vehicle and the surrounding object), the inter-vehicle distance with the preceding vehicle, and the type of traveling characteristic mode are at least included. The type of traveling characteristic mode may specify the type of traveling characteristic mode set by the driver based on the operation information input from the in-vehicle operation device group 130.

  Next, traveling history generation processing will be described. The on-vehicle control device 170 generates a traveling history regarding control parameters of the vehicle as traveling history information of the vehicle based on the results of the above-described respective processes. First, the on-vehicle control device 170 acquires the traveling position of the vehicle from the position detection device 142 included in the on-vehicle sensor group 140. Next, the on-vehicle control device 170 sets information on the estimated in-vehicle personnel configuration, the specified control parameter of the vehicle, and the traveling position of the vehicle as traveling history information of the vehicle. The in-vehicle control device 170 transmits the traveling history information of the vehicle to the server communication device 210 of the data center 200 via the in-vehicle 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 in-vehicle communication device 160 of the in-vehicle device 100 via the telephone network or the Internet network. The server communication device 210 communicates with a plurality of in-vehicle communication devices 160 mounted in each of a plurality of vehicles, and receives information on the configuration of personnel in the vehicle and travel history information of the vehicles from each vehicle. The server communication device 210 outputs, to the server processing device 230, the information on the personnel configuration in the vehicle received from each vehicle and the travel history information of the vehicle.

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

  The server processing device 230 includes a ROM storing a program for specifying an optimal control parameter for each personnel configuration in the vehicle, a CPU executing the program stored in the ROM, and a RAM functioning as an accessible storage device. And consists of The server processing device 230 executes a program stored in the ROM by the CPU to execute a travel history storage process of storing travel history information of the vehicle transmitted from the in-vehicle device 100, and the driver's A driving characteristic analysis process for analyzing driving characteristics and an information providing process for providing control parameter guidance information to the on-vehicle apparatus 100 are executed based on the personnel configuration in the vehicle on which the on-vehicle apparatus 100 is mounted.

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

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

  An example of the driving characteristic will be described. The driving characteristics include driving characteristics attributed to the traveling position, driving characteristics attributed to the other vehicle, and driving characteristics attributed to the road condition. As a driving characteristic resulting from the traveling position, a speed change at the time of tunnel traveling and a speed change at the intersection right and left turns are mentioned as an example. Further, as the driving characteristic caused by the other vehicle, followability to the preceding vehicle (inter-vehicle distance from the preceding vehicle) can be mentioned as an example. Further, as a driving characteristic caused by the road condition, a speed change on a slope road (slope) and a speed change due to a change in vehicle width can be mentioned as an example.

  First, the server processing device 230 executes clustering processing on the traveling history information of the vehicle, and groups the traveling history information for each traveling position of the vehicle. For example, the server processing device 230 groups traveling history information for each traveling position, such as traveling history information around an intersection, and traveling history information on a slope with slopes. This makes it possible to identify an optimal control parameter for each personnel configuration in the vehicle with respect to a specific location. In addition, how to group is not particularly limited, and may be grouped by road type (highway, general road, etc.), or even if it is grouped with a specific place (such as an intersection) Good.

  Next, the server processing device 230 executes clustering processing on the grouped travel history information, and for each of the parameters constituting the information of the personnel configuration in the car (by number of people, by gender, by age, between persons) Per group relationship, per group closeness). Then, the server processing device 230 executes statistical processing for each of the grouped and analyzes the tendency of the driving characteristic. The server processing device 230 calculates a combination of the number of persons in the car, the gender, the age, the relation between the persons, and the closeness between the persons according to the specific driving characteristic as the feature value. The server processing device 230 calculates the feature amount for each driving characteristic by repeating the above-described processing for each driving characteristic.

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

  In addition, the server processing device 230 repeats the above-described analysis process every predetermined cycle, that is, whenever the latest travel history information of the vehicle is accumulated in the database 220. This makes it possible to learn the relationship between the personnel configuration of the vehicle and the control parameters. Then, when the distribution of the analysis result in each period falls within the predetermined range, the server processing device 230 determines that the fluctuation of the tendency of the control parameter has converged, and the relationship among the number, gender, age, person, An optimal control parameter is specified according to the combination of closeness between persons. In addition, the analysis method of travel history information of a vehicle is not limited to the method mentioned above, The server processing apparatus 230 can use the technique of the analysis method at the time of this application application suitably.

  When the analysis of the traveling history information of the vehicle is completed, the server processing device 230 determines the control parameter optimal for each personnel configuration in the vehicle, the feature amount in each driving characteristic (number of persons, gender, age, relationship between persons, and persons) Each combination of intimacy) is stored in the database 220.

  Next, information provision processing will be described. First, the server processing device 230 determines, based on the information transmitted from the in-vehicle device 100, whether or not there is a person who has experienced riding in the past in the current vehicle. The server processing device 230 determines whether or not an experienced passenger is present from at least one of the captured image of the on-vehicle camera 110 and the voice information of the on-vehicle microphone 120 in the personnel configuration in the vehicle. Is extracted as a passenger, the database 220 extracts the personnel configuration in the vehicle including the passenger who has experienced the boarding. Then, the server processing device 230 extracts control parameters having a transmission history to the in-vehicle device 100 among the control parameters corresponding to the extracted personnel configuration. The server processing device 230 specifies the extracted control parameter as an optimal control parameter, and uses it as control parameter guidance information.

  Next, the case where there is no passenger experienced in the current car will be described. In this case, the server processing device 230 specifies a control parameter that is optimal for the current personnel configuration in the vehicle, and uses it as control parameter guidance information. For example, when the information of the present 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 traveling history information of the vehicle stored in the database 220. Then, when the analysis result includes a control parameter that is optimal for the current personnel configuration in the vehicle, the server processing device 230 specifies the control parameter as the optimal control parameter.

  On the contrary, when the analysis result of the travel history information for the vehicle does not include the optimal control parameter, the server processing device 230 performs the optimal control for the in-vehicle personnel configuration similar to the current in-vehicle personnel configuration. Determine if the parameter is present. The server processing device 230 specifies a control parameter that is most suitable for the current personnel configuration in the vehicle based on at least one of the current relationship between persons in the vehicle and the intimacy between people in the current vehicle, and the control parameter It will be guidance information.

  For example, as shown in FIG. 2 (A), for example, the present personnel composition in the car is as follows: "20's male: 1 person, 30's female: 1 person, 50's male: 1 person, 60's male: 1 person The relationship between these persons is a family relationship, and the intimacy is high. " If there is no optimal control parameter corresponding to this personnel configuration in the database 220, the server processing device 230 changes either the relationship between persons in the vehicle or the intimacy between persons in the vehicle, Create a staffing structure similar to the one in the car. Then, the server processing device 230 determines whether or not there is an optimal control parameter for the generated similar personnel configuration. In the case of the example described above, for example, the server processing device 230 changes the intimacy degree from “high” to “normal”, and “male in twenties: one, female in thirties: one, male in 50s: one , 60's male: 1 person in total, the relationship between these persons is a family relationship, and the familiarity is "normal" is a personnel composition similar to the current personnel composition in the car. Then, when the analysis result includes a control parameter optimal for the personnel configuration similar to the current personnel configuration in the vehicle, the server processing device 230 specifies the control parameter as the optimal control parameter.

  If any one of the relationship between persons in the vehicle and the intimacy between persons in the vehicle transmitted from the in-vehicle device 100 is missing for some reason, the server processing device 230 performs the process described above. , Can be supplemented for missing parameters. As a result, the current personnel of the vehicle may be lost even if one of the information on the relationship between the people in the current car and the intimacy between the people in the current car is missing, or if the estimation accuracy is low. Control parameters that are optimal for the configuration can be identified.

  The server processing device 230 transmits the control parameter guidance information obtained by each process described above to the on-vehicle device 100 via the server communication device 210. The in-vehicle apparatus 100 displays the received control parameter guidance information on the in-vehicle display 150 to provide information on control parameters optimal for the current personnel configuration in the vehicle or optimal control provided in the past to the person in the vehicle. Parameter information can be presented.

  In addition, the presentation method of control parameter guidance information is not specifically limited. As a presentation method, there is a method of presenting as a specific driving support to the driver as "Please lower the vehicle speed to ○ km / h" as an example. In addition, as a presentation method, it is recommended to lower the vehicle speed to kmkm / h. Do you want to reduce the vehicle speed to the recommended speed? Be 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 the control parameter to the optimal control parameter. Each included drive may be controlled.

  Next, with reference to FIG. 3, an operation until the in-vehicle apparatus 100 transmits the traveling history information of the vehicle to the data center 200 will be described. FIG. 3 is a flowchart until the in-vehicle device 100 transmits the traveling history information of the vehicle to the data center 200. The processes of the flowchart shown in FIG. 3 are respectively executed by the on-vehicle devices 100 mounted on the respective vehicles. Further, the in-vehicle device 100 repeatedly executes the operation of the flowchart shown in FIG. 3 at predetermined intervals.

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

  In step S102, the on-vehicle control device 170 estimates features of a person present in the vehicle based on the in-vehicle captured image 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. The in-vehicle control device 170 estimates features one by one when there are a plurality of persons in the vehicle. Also, in this step, the in-vehicle control device 170 detects a person present in the vehicle from the captured image, and calculates the number of people in the vehicle.

  In step S103, the in-vehicle control device 170 estimates the relationship between persons present in the vehicle based on the in-vehicle audio information acquired in step S101. Also, in this step, the in-vehicle control device 170 estimates the closeness between persons present in the vehicle based on the in-vehicle audio information acquired in step S101. It should be noted that the in-vehicle control device 170 performs the processing of this step after a predetermined elapsed time has elapsed from step S102 since the relationship between persons in the vehicle and the estimation accuracy of the intimacy relatively easily increase if there are many conversations. It is preferable to carry out.

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

  In step S105, the on-vehicle control device 170 acquires control parameters related to the traveling of the vehicle. The on-vehicle control device 170 acquires control parameters based on the detection result from the on-vehicle sensor group 140. In addition, in this step, the on-vehicle control device 170 acquires, for example, position information of the vehicle from the navigation device based on the traveling route of the vehicle which has traveled so far.

  In step S106, the on-vehicle control device 170 generates traveling history information of the vehicle. The on-vehicle control device 170 associates the in-vehicle personnel configuration estimated in step S104, the control parameters of the vehicle identified in step S105, and the traveling position of the vehicle acquired in the same step, and sets the travel history information of the vehicle. In this way, the personnel configuration in the vehicle is associated with control parameters in the personnel configuration.

  In step S107, the in-vehicle control device 170 transmits the traveling history information of the vehicle generated in step S106 to the data center 200. When step S107 ends, the process until the onboard apparatus 100 transmits the traveling history information of the vehicle to the data center 200 ends.

  Next, with reference to FIG. 4, an operation of specifying an optimal control parameter for each personnel configuration will be described. FIG. 4 is a flow chart for explaining a process of specifying an optimal control parameter for each personnel configuration. The processing of the flowchart illustrated 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 traveling history information of the vehicle transmitted from the in-vehicle device 100, and stores the information in the database 220.

  In step S202, the server processing device 230 analyzes the driving characteristic of the driver for each personnel configuration from the traveling history information of the vehicle for each traveling position of each vehicle accumulated in the database 220 in step S201. For example, the server processing device 230 executes clustering processing on travel history information of a vehicle at a specific travel position, and for each parameter constituting information on the personnel configuration in the vehicle (for each person, for each gender, for each age, Relationship between people in the car, closeness between people in the car) grouping. Then, the server processing device 230 analyzes the tendency of the driving characteristic for each of the grouped, and the number of persons, gender, age, relationship between persons, and closeness between persons according to one driving characteristic. Calculate the feature value 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-described processing for each operation characteristic. The server processing device 230 associates the operation characteristic with the control parameter by specifying the control parameter corresponding to each operation characteristic.

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

  In step S204, the server processing device 230 stores, in the database 220, the analysis result obtained in step 202 and the optimal control parameter for each personnel configuration identified in step S203. When step S204 ends, the process in which the server processing device 230 specifies an optimal control parameter for each personnel configuration ends.

  Next, with reference to FIGS. 5A and 5B, a process from getting on the vehicle to providing a control parameter optimal for the personnel configuration in the vehicle will be described. FIG. 5A and FIG. 5B are flowcharts for explaining the process from getting on the vehicle to providing the control parameter optimum 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 on-vehicle apparatus 100 mounted on a specific vehicle. Further, the processing of step S307 and steps S309 to S312 shown in FIG. 5B is executed by the server processing device 230 of the data center 200.

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

  In step S302, the on-vehicle control device 170 estimates the feature of the person present in the current car based on the current captured image in the car 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 a ride experience in the past is on the basis of at least one of the captured image and the voice information in the vehicle currently acquired in step S301. If a person who has a ride experience in the past is not detected in the current car, the process proceeds to step S304. If a person who has a ride experience in the past is detected, the process proceeds to step S309.

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

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

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

  If it is determined in step S303 that a person having boarding experience in the past is detected, the process proceeds to step S309. In step S309, the in-vehicle control device 170 transmits, to the data center 200, the information of the person who has the boarding experience detected in step S303.

  When step 306 or step S309 ends, the on-vehicle apparatus 100 waits for a response from the data center 200.

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

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

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

  In step S310, the server processing device 230 extracts, from the database 220, information on the personnel configuration in the car including the person who has the experience of getting in the vehicle. The server processing device 230 extracts a control parameter having a transmission history to the in-vehicle device 100 among the control parameters corresponding to the extracted personnel configuration in the vehicle. The server processing device 230 uses the optimal 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 in-vehicle device 100.

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

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

  In step S315, the in-vehicle control device 170 outputs the control parameter guidance information received in step S313. The in-vehicle control device 170 outputs the optimum control parameter 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 on-vehicle control device 170 controls the brake pedal so as to reduce the speed further than the legal speed by a predetermined speed in a scene where the intersection is turned to the left or right. This makes it possible to realize driving that does not place an excessive load on the elderly passenger. Further, the information providing system 1 of the present embodiment exhibits the following effects not only to the passenger but also to the driver. For example, when the passenger is a friend, the on-vehicle control device 170 changes the traveling characteristic mode of the vehicle so as to switch from the normal mode to the sport mode in a scene traveling on a mountain road. This makes it possible to realize driving that allows the driver to enjoy driving.

  Further, in this step, the on-vehicle control device 170 may output the optimum control parameter guidance information provided in the past to the on-vehicle operation device group 130. When step S315 is finished, the process from getting on to providing the control parameter optimal for the personnel configuration in the car is finished.

  As described above, in the present embodiment, the in-vehicle device 100 acquires a captured image of the in-vehicle from the in-vehicle camera 110 that captures an interior of the vehicle, and collects in-vehicle audio information from the in-vehicle microphone 120 that collects audio in the in-vehicle. Acquire and estimate the relationship between people in the vehicle based on voice information in the vehicle, estimate the personnel configuration in the vehicle with which the relationship between the number of people in the vehicle and the person in the vehicle is associated, and the in-vehicle sensor The control parameters relating to the in-vehicle travel are acquired from the group 140, and the travel history information of the vehicle associated with the in-vehicle personnel configuration and the control parameters is transmitted to the data center 200. In the data center 200, the server processing device 230 stores the travel history information of the vehicle in the database 220, and analyzes the travel history information of the stored vehicle to specify the optimum control parameter for each personnel configuration in the vehicle. Thereby, the optimal control parameter of the vehicle in consideration of the passenger can be determined.

  Further, in the present embodiment, the on-vehicle apparatus 100 estimates the number of people in the car and the gender and age of the person in the car based on the captured image in the car, and the relationship between the people in the car based on voice information in the car. Estimate sex and closeness between people in the car. Then, the on-vehicle apparatus 100 uses the estimated information as information on the personnel configuration in the vehicle. Thus, for example, even in a vehicle in which the on-vehicle camera 110 is not mounted or a vehicle in which the on-vehicle microphone 120 is not mounted, it is possible to estimate the outline of the personnel configuration in the vehicle. Further, in a vehicle in which both the on-vehicle camera 110 and the on-vehicle microphone 120 are mounted, it is possible to accurately estimate the personnel configuration in the vehicle.

  Furthermore, in the present embodiment, the on-vehicle control device 170 acquires the traveling position of the vehicle from the position detection device 142. The control parameters acquired by the in-vehicle control device 170 from the in-vehicle sensor group 140 include the steering angle, the accelerator opening degree, the brake opening degree, the detection result of the sonar sensor, the detection result of the radar sensor, the vehicle speed, acceleration, and the distance to the preceding vehicle. The distance and the driving characteristic mode are included. Then, the on-vehicle control device 170 uses information in which the control parameters indicating the traveling state of the vehicle, the personnel configuration in the vehicle, and the traveling position of the vehicle are associated with each other as traveling history information of the vehicle. As a result, in the data center 200, it is possible to store in the database 220 optimal control parameters for each personnel configuration in the vehicle in various traveling scenes.

  Further, in the present embodiment, the in-vehicle apparatus 100 acquires a captured image of the current in-vehicle from the in-vehicle camera 110, acquires audio information of the current in-vehicle from the in-vehicle microphone 120, and based on the in-vehicle audio information. Estimate the relationship between people in the current car, estimate the current staff configuration in the car with which the relationship between the number of people in the current car and the people in the current car is associated, and the information on the staff composition in the current car Are sent to the data center 200. In the data center 200, the server processing device 230 selects an optimal control parameter for the current personnel configuration in the vehicle from among the optimal control parameters stored in the database 220 and specified for each personnel configuration in the vehicle, Send to device 100. In the in-vehicle apparatus 100, the in-vehicle control apparatus 170 outputs, to each drive apparatus, the control parameter optimal for the current personnel configuration received from the data center 200. Thus, it is possible to perform the operation with the optimal control parameter in consideration of the passenger.

  Furthermore, in the present embodiment, the server processing device 230 is optimal for the current personnel configuration in the vehicle based on at least one of the current relationship between the persons in the vehicle and the current intimacy between the persons in the vehicle. Control parameters are extracted from the database 220. Thereby, for example, even if any one of these pieces of information is missing for some reason, it is possible to extract a control parameter that is optimal for the current personnel configuration in the vehicle.

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

  Further, in the present embodiment, the on-vehicle apparatus 100 urges a person in the vehicle to select whether to provide the optimum control parameter guidance information received from the data center 200 in the vehicle. Thereby, a person in the vehicle can use the control parameter guidance information from the data center 200 as needed.

  The embodiments described above are described to facilitate the understanding of the present invention, and are not described to limit the present invention. Therefore, each element disclosed in the above embodiment is intended to include all design changes and equivalents that fall within the technical scope of the present invention.

  For example, in the above-described embodiment, as a method of presenting control parameter guidance information, a selection screen for displaying control parameter guidance information on the on-vehicle display 150 or prompting the driver to select whether to use an optimal control parameter is displayed. Although the configuration for displaying on the in-vehicle display 150 has been described as an example, the method of presenting the control parameter guide information is not limited to this. For example, when the vehicle has a function of automatically driving, the on-vehicle apparatus 100 may output the optimal control parameter received from the data center 200 to each driving device that performs automatic driving. Thus, the vehicle can perform the optimal driving for the specific in-vehicle personnel configuration in the specific traveling scene.

  Further, for example, in the above-described embodiment, the configuration for estimating the relationship between persons in the vehicle has been described as an example based on the voice information from the in-vehicle microphone 120. However, estimation of the relationship between persons in the vehicle is described. A terminal device owned by a person in the car may be used for Examples of the terminal device include devices that can be connected to the Internet, such as a mobile phone, a smartphone, a notebook computer, and a tablet computer. These terminal devices have ID information that can identify the owner. Since the terminal device can communicate with the data center 200 by Internet connection, the server processing device 230 specifies the relationship between persons in the vehicle from personal information registered as ID information of the terminal device. Can. This can improve the accuracy of estimating the relationship between persons in the car.

  Also, for example, in the above-described embodiment, the server processing device 230 may change the optimal control parameter based on a predetermined operation rule predetermined in the operation characteristic analysis process. For example, the server processing device 230 changes the control parameter optimum for the personnel configuration in the corresponding vehicle, when it is determined that the driving characteristic in the specific vehicle interior configuration tends not to be recognized as the superior driver's driving. be able to. This can prevent the driving that is not an example from being performed.

  Further, for example, in the above-described embodiment, the relationship between persons in the vehicle and the closeness between 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 closeness may be estimated. For example, the on-vehicle control device 170 may estimate the relationship between persons in the vehicle from the expression of the person included in the captured image.

  Further, for example, in the above-described embodiment, the on-vehicle apparatus 100 has described the configuration in which the relationship between people in the vehicle and the intimacy are estimated or the configuration of the personnel in the vehicle is estimated. The estimation of the relationship and closeness between persons in the vehicle and the estimation of the personnel configuration in the vehicle may be the data center 200. For example, the in-vehicle apparatus 100 transmits the in-vehicle captured image captured by the in-vehicle camera 110 and the in-vehicle audio information collected by the in-vehicle microphone 120 to the data center 200, and the server processing device 230 You may estimate closeness and in-vehicle personnel composition.

  Further, for example, in the above-described embodiment, the information processing apparatus according to the present invention has been described using the on-vehicle control device 170, the database 220, and the server processing device 230 that constitute the information providing system 1 as an example. The present invention is not limited to this. For example, the in-vehicle apparatus 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 configurations of the on-vehicle control device 170 and the server processing device 230 as an example, but the present invention is not limited thereto.

DESCRIPTION OF SYMBOLS 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 unit

Claims (10)

An information processing method using a controller and a storage device, comprising
Obtaining at least one of an in-vehicle captured image output from a camera for capturing an interior of the vehicle and at least voice information in the vehicle output from a microphone for acquiring an audio of the vehicle interior;
Based on the acquired information, estimate the relationship between the persons present in the vehicle,
Estimating the in-vehicle personnel configuration in which the number of people in the vehicle and the relationship between persons in the vehicle are associated;
Acquiring control parameters related to traveling of the vehicle from a sensor that detects the traveling state of the vehicle;
Causing the storage device to store a travel history of a vehicle associated with the in-vehicle personnel configuration and the control parameter;
An information processing method for specifying the control parameter optimal for each personnel configuration in the vehicle by analyzing the accumulated travel history. The information processing method according to claim 1, wherein
The personnel configuration in the vehicle includes the number of people in the vehicle, the sex and age of the person in the vehicle, the relationship between the people in the vehicle, and the closeness between the people in the vehicle.
The number of people in the car and the gender and age of the person in the car are estimated based on the captured image of the car,
An information processing method for estimating a relation between persons in the car and a closeness between persons in the car based on voice information in the car. The information processing method according to claim 2,
Acquiring the traveling position of the vehicle from the sensor;
The control parameters include 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 at least one of the following: a detection result of the acceleration sensor, an inter-vehicle distance to the preceding vehicle, and a traveling characteristic mode,
The information processing method, wherein the travel history includes personnel configuration in the vehicle, the control parameter, and the travel position. The information processing method according to any one of claims 1 to 3, wherein
The information processing method which estimates the relationship between the persons in the said vehicle based on the terminal device which the person in the said vehicle owns. The information processing method according to any one of claims 1 to 4, wherein
Obtaining at least one of a current captured image in the car output from the camera and audio information in the current car output from the microphone;
Based on the acquired information, estimate the relationship between people in the current car,
Estimating the current personnel composition in the vehicle associated with the relationship between the current number of people in the vehicle and the person in the current vehicle;
From the optimal control parameters specified for each in-vehicle personnel configuration, select the optimal control parameters for the current in-vehicle personnel configuration,
An information processing method for outputting selected optimal control parameters. The information processing method according to claim 5, wherein
The present in-vehicle personnel composition includes the current number of people in the vehicle, the gender and age of the current in-vehicle person, the relationship between the current in-vehicle person, and the current parent in the vehicle Including density
An information processing method for selecting a control parameter most suitable for the current personnel configuration in the vehicle based on at least one of the current relationship between persons in the vehicle and the intimacy between people in the current vehicle. The information processing method according to claim 5 or 6,
When a person who has experienced riding in the vehicle in the past is detected from the current captured image in the vehicle or voice information in the current vehicle, the person in the current vehicle is estimated from the relationship between persons in the vehicle estimated in the past Information processing method to estimate the relationship between The information processing method according to any one of claims 5 to 7, wherein
An information processing method for switching whether or not to output the optimal control parameter according to the selection of a person present in the vehicle. The information processing method according to any one of claims 5 to 8, wherein
An information processing method for changing the optimal control parameter, when the present personnel composition in the vehicle corresponds to a predetermined personnel composition set in advance. A controller that executes information processing;
With storage
The controller
Acquiring at least one of an in-car captured image output by a camera for capturing an interior of the vehicle and at least one of in-car audio information output by a microphone for acquiring an audio of the vehicle interior;
Based on the acquired information, estimate the relationship between the persons present in the vehicle,
Estimate the personnel composition in the car that associates the relationship with the number of people in the car,
Acquiring control parameters related to travel control of the vehicle from a sensor that detects the travel state of the vehicle;
Causing the storage device to store a travel history in which the personnel configuration in the vehicle and the control parameter are associated;
An information processing apparatus that identifies the control parameter optimal for each personnel configuration in the vehicle by analyzing the accumulated travel history.

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