Driving assistance system, driving assistance processing method, and recording medium

Abstract

The present invention provides a driving assistance system for assisting with the driving of a vehicle, wherein the system calculates burden state values on the basis of vehicle measurement data including driver state information related to a burden state of a driver of a vehicle and passerby measurement data including passerby state information related to the burden state of a passerby, these data being measured in a predetermined specific travel scenario in which an overall optimum appears. The burden state values indicate changes in the burden state of each of a driver of another vehicle and the passerby present in the predetermined specific travel scenario while the vehicle to be assisted with is traveling in the predetermined specific travel scenario. The burden state values are a first burden state value for the case where the driver of the vehicle to be assisted with changes their driving behavior and a second burden state value for the case where the driver of the vehicle to be assisted with does not change their driving behavior. The system calculates an overall optimum evaluation value, which indicates the impact of the driving behavior of the vehicle to be assisted with on the overall optimum, on the basis of the difference between the first burden state value and the second burden state value.

Description

Driving assistance system, driving assistance processing method, and recording medium

[0001] The present disclosure relates to a driving assistance system, a driving assistance processing method, and a recording medium.

[0002] In situations involving multiple participants, there is a concept called total optimization, which indicates the optimal state for all participants. This concept of total optimization can also be applied to transportation environments involving multiple transportation participants.

[0003] For example, Patent Literature 1 proposes an environmental adjustment system that allows individual users to achieve their goals while also optimizing the overall environment to which the users belong. Specifically, Patent Literature 1 discloses an environmental adjustment system that includes an acquisition unit that acquires environmental information about an environment related to a user, a planning unit that plans an action plan to be recommended to the user based on the environmental information, a transmission unit that transmits the action plan to the user's terminal, and a confirmation unit that confirms whether the user has implemented the action plan, and when planning a new action plan for another user or the user, the planning unit uses the confirmation result by the confirmation unit.

[0004] Furthermore, Patent Literature 2 proposes a technology for optimizing the overall behavior of a large number of users. Specifically, Patent Literature 2 discloses a behavior control system that includes a content providing means for transmitting content that prompts some users to change their behavior to their terminal devices, a confirmation means for confirming whether or not users who have received the content have actually changed their behavior in accordance with the content, and a content effectiveness determining means for determining the characteristics and / or conditions of users who are likely to accept the content based on the confirmation result by the confirmation means and the characteristics and / or conditions of users stored in a database and recording the determination result in the database, and the content providing means determines users to select as recipients of the content based on the determination result recorded in the database the next time the content is provided.

[0005] JP 2019-117142 A JP 2017-59099 A

[0006] In a traffic environment involving multiple traffic participants, such as other vehicles, pedestrians, and bicycles, traffic troubles can be avoided by adopting altruistic driving behavior that does not burden other traffic participants. If such altruistic driving behavior is considered to be an overall optimal behavior that optimizes the overall situation of surrounding traffic participants, factors related to overall optimization are thought to include at least the psychological and physical burdens of the vehicle driver. Furthermore, when pedestrians and cyclists are present in the traffic environment, the psychological and physical burdens of pedestrians and cyclists are also thought to be related to overall optimization.

[0007] However, while the technologies disclosed in Patent Documents 1 and 2 consider congestion relief and optimization of energy supply as optimization of the overall environment, they do not consider the psychological and physical stress on vehicle drivers, pedestrians, and cyclists. Therefore, the technologies disclosed in Patent Documents 1 and 2 cannot achieve overall optimal driving that does not irritate other traffic participants.

[0008] Furthermore, the technologies disclosed in Patent Documents 1 and 2 are targeted at autonomous vehicles and take into account the difference between planned and executed driving behaviors, but do not focus on the difference in impact on overall optimization between cases where the driver changes his or her driving behavior and cases where he or she does not change it. For example, in a situation where a pedestrian is approaching a crosswalk, if it is known how much the overall optimization improves when a vehicle traveling straight passes the crosswalk without slowing down and when the vehicle slows down before the crosswalk, appropriate driving behaviors can be suggested to the driver of the vehicle.

[0009] The present disclosure has been made in consideration of the above-mentioned problems, and an object of the present disclosure is to provide a driving assistance system, a driving assistance control method, and a recording medium that assist in achieving overall optimal driving without placing a burden on other traffic participants.

[0010] In order to solve the above problem, according to an aspect of the present disclosure, there is provided a driving assistance system that assists driving of a vehicle, the system including: a collected data storage unit that stores vehicle measurement data transmitted from a first terminal mounted in each vehicle, the vehicle measurement data including driver state information relating to a load state of a driver of the vehicle, the vehicle measurement data being measured in a predetermined specific driving scene that is set in advance; and passerby measurement data transmitted from a second terminal carried by each passerby, the passerby state information being measured in the predetermined specific driving scene; and a processing unit that executes a process to assist driving of an assistance target vehicle based on the collected vehicle measurement data and passerby measurement data, the processing unit executing the process to assist driving of an assistance target vehicle based on the collected vehicle measurement data and passerby measurement data, A driving assistance system is provided that executes an overall optimization calculation process that calculates load state values ​​that indicate changes in the load state of each of the drivers of other vehicles and pedestrians present in the predetermined specific driving scene while the assisted vehicle is traveling in the predetermined specific driving scene, the load state values ​​being a first load state value when the driver of the assisted vehicle changes his / her driving behavior in the predetermined specific driving scene and a second load state value when the driver of the assisted vehicle does not change his / her driving behavior in the predetermined specific driving scene, and calculates an overall optimization evaluation value that indicates the influence of the driving behavior of the assisted vehicle on overall optimization based on the difference between the first load state value and the second load state value, and a driving assistance process that assists the driving of the assisted vehicle based on the overall optimization evaluation value.

[0011] Further, in order to solve the above-mentioned problem, according to another aspect of the present disclosure, there is provided a driving assistance processing method for assisting driving of a vehicle, in which a computer calculates a load status of a driver of the vehicle, the load status being measured in a predetermined specific driving scene and transmitted from a first terminal mounted in each vehicle, and a load status being measured in the predetermined specific driving scene and transmitted from a second terminal carried by each passerby, based on the vehicle measurement data including driver status information related to a load status of the driver of the vehicle, the load status being measured in the predetermined specific driving scene, and the load status being measured in the predetermined specific driving scene and transmitted from a second terminal carried by each passerby. a first load state value when the driver of the assisted vehicle changes his driving behavior in the predetermined specific driving scene and a second load state value when the driver of the assisted vehicle does not change his driving behavior in the predetermined specific driving scene; a global optimization evaluation value that indicates the influence of the driving behavior of the assisted vehicle on global optimization based on the difference between the first load state value and the second load state value; and assisting the driving of the assisted vehicle based on the global optimization evaluation value.

[0012] Furthermore, in order to solve the above problem, according to another aspect of the present disclosure, a computer is provided to calculate the load status of each of the drivers of other vehicles and the passersby present in the predetermined specific driving scene while the assistance target vehicle is traveling in the predetermined specific driving scene, based on vehicle measurement data transmitted from a first terminal mounted in each vehicle and including driver state information related to the load status of the driver of the vehicle, measured in a predetermined specific driving scene that is set in advance, and passerby measurement data transmitted from a second terminal carried by each passerby and including passerby state information related to the load status of the passersby, measured in the predetermined specific driving scene. A non-transitory tangible recording medium is provided that stores a computer program that performs the following operations: calculates load state values ​​that indicate changes in the load state, the load state values ​​being a first load state value when the driver of the assisted vehicle changes his driving behavior in the predetermined specific driving scene and a second load state value when the driver of the assisted vehicle does not change his driving behavior in the predetermined specific driving scene; calculates an overall optimization evaluation value that indicates the impact of the driving behavior of the assisted vehicle on overall optimization based on the difference between the first load state value and the second load state value; and assists the driving of the assisted vehicle based on the overall optimization evaluation value.

[0013] As described above, according to the present disclosure, it is possible to support the realization of overall optimal driving that does not place a burden on other traffic participants.

[0014] 1 is a schematic diagram showing a basic configuration of a driving assistance system according to a first embodiment of the present disclosure. FIG. 1 is an explanatory diagram showing an example of a specific driving scene in which the driving behavior of a vehicle affects overall optimization. FIG. 2 is an explanatory diagram showing another example of a specific driving scene in which the driving behavior of a vehicle affects overall optimization. FIG. 3 is an explanatory diagram showing another example of a specific driving scene in which the driving behavior of a vehicle affects overall optimization. FIG. 4 is a block diagram showing an example of a configuration of a mobile terminal of the driving assistance system according to the embodiment. FIG. 5 is a flowchart showing processing operations by the mobile terminal of the driving assistance system according to the embodiment. FIG. 6 is a schematic diagram showing an example of a configuration of a vehicle to which the driving assistance system of the embodiment can be applied. FIG. 7 is a block diagram showing an example of a configuration device of the driving assistance system according to the embodiment. FIG. 8 is a flowchart showing a main routine of processing operations by the driving assistance device of the driving assistance system according to the embodiment. FIG. 9 is a flowchart showing assistance processing by the driving assistance device of the driving assistance system according to the embodiment. FIG. 10 is a flowchart showing pre-passage processing by the driving assistance device of the driving assistance system according to the embodiment. FIG. 11 is a flowchart showing post-passage processing by the driving assistance device of the driving assistance system according to the embodiment. FIG. 12 is a block diagram showing an example of a configuration of a management server of the driving assistance system according to the embodiment. FIG. 13 is a flowchart showing processing operations by the management server of the driving assistance system according to the embodiment. FIG. 14 is a flowchart showing pre-passage assistance information setting processing by the management server of the driving assistance system according to the embodiment. 1 is a flowchart illustrating a process of calculating an overall optimal evaluation value by a management server of the driving assistance system according to the embodiment. FIG. 2 is a block diagram illustrating a configuration example of a driving assistance device of the driving assistance system according to the second embodiment. FIG. 3 is a flowchart illustrating a pre-passing process by the driving assistance device of the driving assistance system according to the embodiment.

[0015] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0016] In the embodiments described below, a "specific driving scene" refers to a driving scene that is predefined as a driving scene in which the driving behavior of a vehicle affects the overall optimization of surrounding traffic participants. The "specific driving scene" may be predefined at the system design stage, or may be arbitrarily defined by the vehicle user.

[0017] "Pedestrians" refers not only to pedestrians but also to people other than vehicle occupants, such as cyclists. "Traffic participants" refers to vehicles and pedestrians present in a specific driving scene, including not only other vehicles but also supported vehicles. "Surrounding traffic participants" refers to traffic participants present around any one of the traffic participants (supported vehicle) when that vehicle is used as the reference. "First terminal" refers to a driving assistance device installed in a vehicle participating in the system. "Second terminal" refers to a mobile terminal carried by a passerby participating in the system.

[0018] The "load state of passersby" and the "load state of driver" indicate either or both of the psychological load and the physical load, respectively.

[0019] The "psychological state of passersby" and the "psychological state of the driver" indicate the state of psychological stress, and are classified into 11 levels, for example, from minus 5 to plus 5, with a larger absolute value of the positive value indicating a more positive psychological state. The "psychological state of passersby" and the "psychological state of the driver" are considered to change to a negative psychological state, for example, if the driving behavior of the vehicle violates traffic rules or traffic etiquette, or if the driving behavior is dangerous. Furthermore, the "psychological state of passersby" and the "psychological state of the driver" are considered to change to a positive psychological state, for example, if the driving behavior of the vehicle gives priority to other vehicles or passersby.

[0020] The "physical load of pedestrians" and the "physical load of drivers" are expressed, for example, as the amount of calories burned per unit time, and the larger the absolute value of the positive value, the greater the physical load. The "physical load of pedestrians" is thought to increase, for example, when a sudden avoidance action is required due to the influence of the vehicle's driving behavior. The "physical load of drivers" is thought to increase when the driver depresses the brake pedal to decelerate or operates the steering wheel to change lanes.

[0021] <<1. First embodiment>> <1-1. Overview of driving assistance system> First, an example of an overview of a driving assistance system according to an embodiment of the present disclosure will be described.

[0022] 1 is an explanatory diagram showing an example of the basic configuration of a driving assistance system 100. The driving assistance system 100 includes a first terminal (driving assistance device) 50 mounted on each of a plurality of vehicles 1, a second terminal (mobile terminal) 130 carried by one or more passersby H, and a management server 110. The number of vehicles 1 and passersby H participating in the driving assistance system 100 is arbitrary and is not particularly limited. Also, for ease of understanding, one management server 110 is illustrated, but a plurality of management servers 110 may be provided.

[0023] The driving assistance device 50 and the mobile terminal 130 are each communicably connected to the management server 110 via one or more communication networks 105. For example, the driving assistance device 50 and the mobile terminal 130 are connected to the management server 110 via a mobile communication network.

[0024] The mobile terminal 130 is, for example, a smartphone, a smart watch, or another wearable device. The mobile terminal 130 detects its position information at a predetermined processing cycle and calculates the direction and speed of movement of the mobile terminal 130 based on the change in the position of the mobile terminal 130 over time. The mobile terminal 130 also measures passerby state information related to at least one of the psychological state and physical load of the passerby H holding the mobile terminal 130.

[0025] The mobile terminal 130 has a configuration capable of transmitting information about the position, moving direction, and moving speed of the mobile terminal 130, as well as passerby status information, along with identification information for identifying the mobile terminal 130, to the management server 110. In this embodiment, the identification information of the mobile terminal 130, the information about the position, moving direction, and moving speed of the mobile terminal 130, and the passerby status information correspond to passerby measurement data.

[0026] The driving assistance device 50 is mounted on the vehicle 1 participating in the system, detects position information of the vehicle 1 at a predetermined processing cycle, and calculates the direction of movement of the vehicle 1 based on changes in the position of the vehicle 1 over time. The driving assistance device 50 also measures the running state and energy consumption of the vehicle 1 and accumulates the data as time-series data. The driving assistance device 50 also detects driver state information related to at least one of the psychological state and physical load of the vehicle driver.

[0027] The driving assistance device 50 is configured to be able to transmit, to the management server 110, identification information for identifying the driver, as well as information on the position, direction of movement, and driving state of the vehicle 1, and driver status information. In this embodiment, the driver's identification information, the information on the position, direction of movement, energy consumption, and driving state of the vehicle 1, and the driver status information correspond to vehicle measurement data. Note that, hereinafter, the information on the position, direction of movement, and driving state of the vehicle 1 may be collectively referred to as "vehicle status information."

[0028] Furthermore, the driving assistance device 50 acquires notification information for assisting the driving of the vehicle 1 from the management server 110, and notifies the driver of the vehicle 1 of the acquired notification information. In this embodiment, the driving assistance device 50 acquires notification information from the management server 110 before and after the vehicle 1 passes through a predetermined specific driving scene, and notifies the driver of the acquired notification information.

[0029] The management server 110 is an information processing device that is communicatively connected to the mobile terminal 130 and the driving assistance device 50 via the communication network 105 using, for example, cloud computing technology. The management server 110 receives vehicle measurement data from the driving assistance device 50. The received vehicle measurement data includes information indicating that the vehicle 1 is passing through a predetermined specific driving scene. The management server 110 identifies the mobile terminal 130 that is present within a predetermined area corresponding to the position of the vehicle 1 passing through the specific driving scene, and transmits a data transmission request message to the mobile terminal 130.

[0030] The management server 110 also identifies other vehicles present within a predetermined area corresponding to the position of the vehicle 1 passing through the specific driving scene, and identifies the vehicle measurement data received from the other vehicles. The management server 110 sets notification information to assist the driving of the assisted vehicle 1 based on the vehicle measurement data and passerby measurement data acquired from surrounding traffic participants present in the specific driving scene, and transmits the notification information to the driving assistance device 50 of the vehicle 1.

[0031] 2 to 4 are explanatory diagrams showing examples of specific driving scenes in which the driving behavior of vehicles affects overall optimization. Fig. 2 shows a scene in which three vehicles 200a to 200c are driving toward the crosswalk from the right on a road with a pedestrian crossing, one vehicle 200d is driving toward the crosswalk from the left, and a pedestrian 202 is approaching the crosswalk. The specific driving scene in Fig. 2 is defined as, for example, a "driving scene in which vehicles pass through a crosswalk without traffic lights."

[0032] In the example shown in FIG. 2 , if vehicle 200d slows down to allow pedestrian 202 to cross the crosswalk, vehicle 200a also slows down or stops, thereby encouraging pedestrian 202 to cross the crosswalk smoothly. In this case, it is considered that at least the driver of vehicle 202d and pedestrian 202 will change to a positive psychological state. However, if vehicle 200a suddenly decelerates, it is considered that the drivers of vehicles 200b and 200c will change to a negative psychological state, or the physical load of the drivers of the following vehicles 200a to 200c will increase. On the other hand, if vehicle 200a continues traveling without slowing down, it is considered that the driver of vehicle 202d and pedestrian 202 will change to a negative psychological state. Furthermore, if pedestrian 202 is forced to suddenly stop in front of the crosswalk due to the influence of vehicle 202a passing through the crosswalk, it is considered that the physical load of pedestrian 202 will increase.

[0033] 3 and 4 are examples of specific driving scenes in which no pedestrians are present, and show a scene in which vehicles 210a to 210g traveling in different lanes merge at a lane merging point on a two-lane road. The specific driving scenes in Fig. 3 and 4 are defined as, for example, "driving scenes passing through a lane merging point."

[0034] FIG. 3 illustrates a "zipper merge" in which vehicles traveling in two lanes merge by yielding to each other at the leading edge of the merger. In a zipper merge, the drivers of vehicles 210b and 210e at the leading edge of the merger yield to each other and change lanes (changing their driving behavior) to merge. Meanwhile, FIG. 4 illustrates how, just before the merging point, vehicles 200e-200g traveling in the merging lane cut in between vehicles 200a-200d traveling in the destination lane at any point. In the merging method illustrated in FIG. 4, the drivers of vehicles 210a-210g at appropriate positions slow down or change lanes (changing their driving behavior) to allow vehicles 200a-200g to merge.

[0035] The merging method shown in Fig. 3 is a merging method that does not irritate the drivers of the respective vehicles 200a to 200g, compared to the merging method shown in Fig. 4, and is thought to not negatively change the psychological states of the drivers of the vehicles 200a to 200g. Furthermore, with the merging method shown in Fig. 4, if the drivers of the vehicles 210c and 210d traveling in the lane where the vehicles are to merge suddenly decelerate due to the influence of the vehicles 210f and 210g cutting in, it is thought that the physical burden on the drivers of the vehicles 210c and 210d will increase.

[0036] The driving assistance system 100 according to this embodiment focuses on changes in the psychological state and physical load of surrounding traffic participants due to the driving behavior of a vehicle traveling in a specific driving scene, and is constructed as a system that aims for overall optimization in a specific driving scene.

[0037] The following provides a specific description of the functional configurations and operations of the mobile terminal 130, the driving assistance device 50, and the management server 110. In the following description, for ease of understanding, a specific vehicle is referred to as an assistance target vehicle 1, and vehicles other than the assistance target vehicle 1 are referred to as other vehicles.

[0038] <1-2. Portable Terminal> First, the portable terminal 130 will be described in detail. The portable terminal 130 is a terminal device held by a passerby H. As described above, the passerby H is not limited to a pedestrian, but may be a person other than a passenger of the vehicle 1, such as a bicycle user.

[0039] (1-2-1. Functional Configuration) FIG. 5 is a block diagram showing the functional configuration of the mobile terminal 130. The mobile terminal 130 includes a communication unit 131, a processing unit 133, a storage unit 139, and a position detection sensor 141. The communication unit 131 is an interface for communicating with the management server 110 via the communication network 105. The position detection sensor 141 receives satellite signals transmitted from positioning satellites of the GNSS (Global Navigation Satellite System), typified by the GPS (Global Positioning System). The satellite signals include position information that indicates the position of the mobile terminal 130 on map data. For example, the position information of the mobile terminal 130 is represented as longitude and latitude data. The position detection sensor 141 outputs the acquired position information of the mobile terminal 130 to the processing unit 133.

[0040] The storage unit 139 includes one or more memories communicably connected to the processing unit 133, and stores computer programs executed by the processing unit 133, various parameters used in the arithmetic processing, and information on the results of the arithmetic processing. The storage unit 139 may be a storage element such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a flash memory such as an SSD (Solid State Drive), or another recording medium.

[0041] The processing unit 133 is configured to include one or more central processing units (CPUs). The processing unit 133 includes a data processing unit 135 and a communication control unit 137. The functions of these units are realized by the execution of a computer program by a processor. The data processing unit 135 calculates the moving speed and moving direction of the mobile terminal 130 based on the position information input from the position detection sensor 141 in a predetermined processing cycle. For example, the data processing unit 135 can calculate the moving speed and moving direction of the mobile terminal 130 based on the time change in the position information input in each predetermined processing cycle.

[0042] Furthermore, the data processing unit 135 measures at least one of the psychological state and physical load of the passerby H holding the mobile terminal 130 based on information input from the biosensor 143 and the camera 145 in a predetermined processing cycle. The data processing unit 135 estimates the psychological state of the passerby H from, for example, the facial muscles of the passerby H acquired from image data of the camera 145. The camera 145 that captures the face of the passerby H may be a camera mounted on a smartphone, or may be a camera communicably connected to the mobile terminal 130 and worn by the passerby H.

[0043] Furthermore, the data processing unit 135 estimates the physical load of the passerby H based on, for example, the myoelectric potential signal output from the biosensor 143. The biosensor 143 for measuring the physical load of the passerby H may be a contact-type biosensor mounted on a smartphone, or may be a biosensor communicably connected to the mobile terminal 130 and worn by the passerby H.

[0044] The communication control unit 137 transmits to the management server 110 the passerby measurement data including the position information of the mobile terminal 130 input from the position detection sensor 141, information on the moving speed and moving direction of the mobile terminal 130 calculated by the data processing unit 135, and driver condition information related to at least one of the psychological state and physical load of the passerby H. In this embodiment, the communication control unit 137 transmits the passerby measurement data to the management server 110 when it receives a data transmission request from the management server 110.

[0045] (1-2-2. Processing Operation) Next, a specific description will be given of the processing operation of the mobile terminal 130. Fig. 6 shows a flowchart of the processing operation by the mobile terminal 130. The flowchart shown in Fig. 6 is executed continuously while the mobile terminal 130 is participating in the system of the present disclosure.

[0046] The data processing unit 135 of the processing unit 133 measures passerby state information and records it in the storage unit 139 (step S11). Specifically, the data processing unit 135 identifies the face of the passerby H based on the image data generated by the camera 145, and estimates the psychological state of the passerby H from the facial muscles. If the face of the passerby H cannot be identified in the image data of the camera 145, the data processing unit 135 skips estimating the psychological state of the passerby H. In addition, the data processing unit 135 calculates the physical load of the passerby H based on the myoelectric potential signal output from the biosensor 143.

[0047] Next, the data processing unit 135 acquires the position information of the mobile terminal 130 output from the position detection sensor 141, calculates the moving direction and moving speed of the mobile terminal 130, and records them in the storage unit 139 (step S13). Specifically, the data processing unit 135 calculates the moving speed by differentiating the moving distance with respect to time based on the position information input at each predetermined processing cycle. The data processing unit 135 also calculates a moving vector (moving direction) on the map data based on the position information input at each predetermined processing cycle.

[0048] Next, the data processing unit 135 transmits the location information together with the identification information of the mobile terminal 130 to the management server 110 (step S15). Next, the communication control unit 137 determines whether or not a data transmission request has been received from the management server 110 (step S17). If the communication control unit 137 determines that a data transmission request has not been received from the management server 110 (S17 / No), the process returns to step S11, and the data processing unit 135 repeats measuring and recording passerby status information and acquiring and transmitting location information.

[0049] On the other hand, if the communication control unit 137 determines that it has received a data transmission request from the management server 110 (S17 / Yes), it transmits the passerby measurement data recorded during a predetermined period to the management server 110 (step S19). The passerby measurement data includes location information, moving speed and moving direction information of the mobile device 130, and passerby status information. The data transmission request transmitted from the management server 110 includes information specifying the period during which each data was recorded. The specified period is, for example, the period during which the support target vehicle passes through a specific driving scene. The communication control unit 137 extracts the data recorded during the specified period from the respective data recorded in the storage unit 139 and transmits the data to the management server 110.

[0050] The mobile terminal 130 repeatedly executes the above-described processing of steps S11 to S19 for each predetermined processing cycle.

[0051] <1-3. Driving Assistance Device> (1-3-1. Vehicle) Next, before describing the functional configuration of the driving assistance device 50, an example of the overall configuration of the vehicle 1 equipped with the driving assistance device 50 will be described. The driving assistance device 50 may be equipped in all vehicles 1 participating in the system of the present disclosure.

[0052] 7 is a schematic diagram showing an example configuration of a vehicle 1 equipped with a driving assistance device 50. The vehicle 1 is configured as a two-wheel drive four-wheel vehicle in which a driving torque output from a driving force source 9 that generates driving torque is transmitted to a left front wheel and a right front wheel. The driving force source 9 may be an internal combustion engine such as a gasoline engine or a diesel engine, a driving motor, or both an internal combustion engine and a driving motor.

[0053] Vehicle 1 may be a four-wheel drive vehicle that transmits drive torque to the front and rear wheels. Vehicle 1 may also be an electric vehicle equipped with two drive motors, for example, a front-wheel drive motor and a rear-wheel drive motor, or an electric vehicle equipped with drive motors corresponding to the respective wheels. If vehicle 1 is an electric vehicle or hybrid electric vehicle, vehicle 1 is equipped with a secondary battery that stores power supplied to the drive motors, and a motor or a generator such as a fuel cell that generates power to charge the battery.

[0054] The vehicle 1 is equipped with a driving force source 9, an electric steering device 15, and brake devices 17LF, 17RF, 17LR, and 17RR (hereinafter collectively referred to as "brake devices 17" unless a distinction is required) as devices used to control the operation of the vehicle 1. The driving force source 9 outputs driving torque that is transmitted to the front-wheel drive shaft 5F via a transmission and a differential mechanism 7 (not shown). The operation of the driving force source 9 and the transmission is controlled by a vehicle control unit 41 that includes one or more electronic control units (ECUs: Electronic Control Units).

[0055] The front-wheel drive shaft 5F is provided with an electric steering device 15. The electric steering device 15 includes an electric motor and a gear mechanism (not shown), and is controlled by a vehicle control unit 41 to adjust the steering angle of the front wheels. During manual driving, the vehicle control unit 41 controls the electric steering device 15 based on the steering angle of the steering wheel 13 operated by the driver. During automatic driving, the vehicle control unit 41 controls the electric steering device 15 based on a set steering angle or steering angular velocity.

[0056] Brake devices 17LF, 17RF, 17LR, and 17RR apply braking force to the respective wheels. Brake devices 17 are configured as, for example, hydraulic brake devices. Vehicle control unit 41 adjusts the hydraulic pressure supplied to each brake device 17 by controlling the drive of hydraulic unit 16. If vehicle 1 is an electric vehicle or a hybrid electric vehicle, brake devices 17 are used in combination with regenerative braking using a drive motor.

[0057] The vehicle control unit 41 includes one or more electronic control devices that control the driving of the driving force source 9, the electric steering device 15, and the hydraulic unit 16. If the vehicle 1 is equipped with a transmission that changes the speed of the output from the driving force source 9 and transmits it to the wheels 3, the vehicle control unit 41 has a function of controlling the driving of the transmission.

[0058] The vehicle 1 also includes front imaging cameras 31LF, 31RF, a rear imaging camera 31R, a vehicle state sensor 33, a position detection sensor 35, an interior imaging camera 37, a biometric sensor 39, and a notification device 43.

[0059] The front imaging cameras 31LF, 31RF and the rear imaging camera 31R constitute ambient environment sensors for acquiring information about the ambient environment of the vehicle 1. The front imaging cameras 31LF, 31RF capture images of the area in front of the vehicle 1 and generate image data. The rear imaging camera 31R captures images of the area behind the vehicle 1 and generates image data. The front imaging cameras 31LF, 31RF and the rear imaging camera 31R are equipped with imaging elements such as a charge coupled device (CCD) or a complementary metal-oxide semiconductor (CMOS), and transmit the generated image data to the driving assistance device 50. In the vehicle 1 shown in FIG. 7 , the front imaging cameras 31LF, 31RF are configured as stereo cameras including a pair of left and right cameras, but the front imaging cameras may also be monocular cameras.

[0060] The surrounding environment sensor may include, in addition to the front imaging cameras 31LF, 31RF and the rear imaging camera 31R, a camera that is mounted on a side mirror and captures images of the left rear or right rear. In addition, the surrounding environment sensor may include one or more sensors selected from the group consisting of a radar sensor such as a light detection and ranging (LiDAR) or a millimeter wave radar, and an ultrasonic sensor.

[0061] The vehicle state sensor 33 is composed of at least one sensor that detects the operating state and behavior of the vehicle 1. The vehicle state sensor 33 includes, for example, at least one of a steering angle sensor, an accelerator position sensor, a brake stroke sensor, a brake pressure sensor, or an engine rotation speed sensor. The vehicle state sensor 33 also includes, for example, at least one of a vehicle speed sensor, an acceleration sensor, or an angular velocity sensor. The vehicle state sensor 33 further includes a switch that detects the on / off state of a turn signal. The vehicle state sensor 33 transmits a sensor signal indicating the detected information to the driving assistance device 50.

[0062] The position detection sensor 35 receives satellite signals from GNSS positioning satellites, such as GPS. The position detection sensor 35 transmits the position information of the vehicle 1 contained in the received satellite signals to the driving assistance device 50. Note that the position detection sensor 35 may be an antenna that receives satellite signals from other satellite systems that identify the position of the vehicle 1, in addition to a GPS sensor.

[0063] The interior camera 37 captures an image of the driver of the vehicle 1 and generates image data. The interior camera 37 includes an imaging element such as a CCD or a CMOS, and transmits the generated image data to the driving assistance device 50.

[0064] The biosensor 39 is composed of one or more sensors that detect the physical load of the driver. For example, the biosensor 39 is a sensor that detects myoelectric potential signals associated with the driver's driving behavior, and is provided on at least one of the steering wheel or the seat. The biosensor 39 provided on the steering wheel detects myoelectric potential signals of the arm muscles associated with the driver's steering operation. The biosensor 39 provided on the seat detects myoelectric potential signals of the lower leg muscles associated with the driver's accelerator or brake operation.

[0065] The notification device 43 is driven by the driving assistance device 50 and notifies the driver of the vehicle 1 of various information by means of image display, audio output, etc. The notification device 43 includes, for example, a display device provided in the instrument panel and a speaker provided in the vehicle 1. The display device may be a display device of a navigation system. The notification device 43 may also be a HUD (head-up display) that displays information on the windshield.

[0066] (1-3-2. Functional Configuration) Next, the functional configuration of the driving assistance device 50 will be described. The driving assistance device 50 functions as a device that assists in driving a vehicle by having one or more processors, such as CPUs, execute a computer program. The computer program is a computer program that causes the processor to execute the operations, described below, that should be executed by the driving assistance device 50. The computer program executed by the processor may be recorded on a recording medium that functions as a storage unit (memory) 55 provided in the driving assistance device 50, or may be recorded on a recording medium built into the driving assistance device 50 or any recording medium that can be externally attached to the driving assistance device 50.

[0067] The recording medium for recording a computer program may be a magnetic medium such as a hard disk, a floppy disk, or a magnetic tape; an optical recording medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD (Digital Versatile Disk), or a Blu-ray (registered trademark); a magneto-optical medium such as a floptical disk; a memory element such as a RAM or a ROM; a flash memory such as a USB (Universal Serial Bus) memory or an SSD; or any other medium capable of storing a program.

[0068] 8 is a block diagram showing the functional configuration of the driving assistance device 50. The driving assistance device 50 is connected to a surrounding environment sensor 31, a vehicle state sensor 33, a position detection sensor 35, an in-vehicle camera 37, and a biological sensor 39 via a dedicated line or communication means such as a controller area network (CAN) or local internet (LIN). The driving assistance device 50 is also connected to a vehicle control unit 41 and a notification device 43.

[0069] The driving assistance device 50 is not limited to an electronic control device mounted on the vehicle 1, and the driving assistance device 50 itself may be a terminal device such as a smartphone or a wearable device.

[0070] The driving assistance device 50 includes a communication unit 51, a processing unit 53, and a storage unit 55. The communication unit 51 is an interface for communicating with the management server 110 via the communication network 105. The processing unit 53 is configured with one or more processors such as CPUs. A part or all of the processing unit 53 may be configured with updatable firmware or the like, or may be a program module or the like that is executed in response to an instruction from the CPU or the like.

[0071] The storage unit 55 is composed of one or more memories such as RAM or ROM, and is communicably connected to the processing unit 53. However, the number and type of storage units 55 are not particularly limited. The storage unit 55 stores information such as computer programs executed by the processing unit 53, various parameters used in calculation processing, detection data, and calculation results. Map data is also stored in the storage unit 55. A part of the storage unit 55 is used as a work area for the processing unit 53.

[0072] The processing unit 53 includes an acquisition unit 61, a surrounding environment detection unit 63, a driver information calculation unit 65, a vehicle information detection unit 67, a driving scene determination unit 69, a communication control unit 71, and a notification processing unit 73. The functions of these units are realized by the execution of a computer program by a processor. Note that some of the acquisition unit 61, the surrounding environment detection unit 63, the driver information calculation unit 65, the vehicle information detection unit 67, the driving scene determination unit 69, the communication control unit 71, and the notification processing unit 73 may be configured using hardware such as an analog circuit.

[0073] The acquisition unit 61 acquires sensor signals or image data output from the surrounding environment sensor 31, the vehicle state sensor 33, the position detection sensor 35, the interior camera 37, and the biometric sensor 39 for each predetermined processing cycle.

[0074] The surrounding environment detection unit 63 detects the surrounding environment of the vehicle 1 based on the sensor signal or image data output from the surrounding environment sensor 31. For example, the surrounding environment detection unit 63 recognizes objects by extracting feature points from the image data and matching the pattern of the feature points with pre-prepared reference data. The surrounding environment detection unit 63 recognizes various objects, such as moving objects such as people, bicycles, motorcycles, and four-wheeled automobiles, as well as man-made or natural stationary objects and lines painted on roads such as white lines and crosswalks. The surrounding environment detection unit 63 also calculates the position and speed of the recognized objects, as well as the distance to the objects. The surrounding environment detection unit 63 may also detect information about the road on which the vehicle 1 is traveling based on map data and the position information of the vehicle 1.

[0075] The surrounding environment sensor 31 may perform processing to recognize these moving objects, stationary objects, etc. In this case, the driving assistance device 50 acquires measurement information including the recognition results from the surrounding environment sensor 31.

[0076] The driver information calculation unit 65 measures at least one of the driver's psychological state and physical load in a predetermined processing cycle. The driver information calculation unit 65 estimates the driver's psychological state from the driver's facial muscles acquired from image data from the in-vehicle camera 37. The driver's psychological state may be measured using a camera worn by the driver. The driver information calculation unit 65 also estimates the driver's physical load based on a myoelectric potential signal output from the biosensor 39. The driver's physical load may be measured using a biosensor worn by the driver and communicatively connected to the driving assistance device 50.

[0077] The vehicle information detection unit 67 detects various vehicle state information. Specifically, the vehicle information detection unit 67 calculates the direction of movement of the vehicle 1 based on the position information input from the position detection sensor 35. The vehicle information detection unit 67 also detects the running state of the vehicle 1 based on the sensor signal output from the vehicle state sensor 33. Specifically, the vehicle information detection unit 67 detects the speed, acceleration, angular velocity, steering angle, accelerator opening, and brake operation amount of the vehicle 1. The vehicle information detection unit 67 also detects the on / off status of the turn signal. Furthermore, the vehicle information detection unit 67 calculates energy consumption corresponding to the speed and acceleration when the speed of the vehicle 1 changes from one speed to another by accelerating or decelerating. As data on the energy consumption of the vehicle 1, design parameters of the vehicle 1 may be used instead of actual measurement data.

[0078] The driving scene determination unit 69 determines whether the vehicle 1 is passing through a predetermined specific driving scene based on information about the surrounding environment of the vehicle 1. Specifically, the driving scene determination unit 69 compares the road structure in the surrounding environment of the vehicle 1 detected by the surrounding environment detection unit 63 and the traffic conditions indicating the positional relationships of surrounding traffic participants around the vehicle 1 with conditions set as the specific driving scene, and determines that the vehicle 1 is passing through the specific driving scene if the road structure and traffic conditions correspond to the specific driving scene. The road structure is information about the road, such as the number of lanes (lanes), merging conditions, intersection conditions, radius of curvature, road width or lane width, road type (general road, intercity expressway, urban expressway, residential road or shopping street, etc.), and type of road or lane boundary line.

[0079] Furthermore, after determining that the vehicle 1 passes through the specific driving scene, the driving scene determination unit 69 determines whether the vehicle 1 has passed through the specific driving scene. Specifically, the driving scene determination unit 69 determines that the vehicle 1 has passed through the specific driving scene when the vehicle 1 leaves an area with a road structure or traffic conditions that correspond to the specific driving scene.

[0080] The communication control unit 71 transmits, at a predetermined timing, vehicle measurement data including driver state information and vehicle state information to the management server 110. Specifically, the communication control unit 71 transmits the vehicle measurement data to the management server 110 when the driving scene determination unit 69 determines that the vehicle 1 will pass through a specific driving scene, and when it determines that the vehicle 1 has passed through the specific driving scene.

[0081] The notification processing unit 73 receives notification information transmitted from the management server 110 and notifies the driver of the notification information via the notification device 43. In this embodiment, the notification processing unit 73 obtains notification information from the management server 110 before and after the vehicle 1 passes through a specific driving scene, and notifies the driver of the obtained notification information.

[0082] (1-3-3. Processing Operation) Next, the processing operation of the driving assistance device 50 will be specifically described.

[0083] 9 to 13 are flowcharts showing the processing operations performed by the driving support device 50. FIG. 9 is a flowchart showing a routine of the processing operations performed by the driving support device 50.

[0084] When the in-vehicle system including the driving assistance device 50 is started (step S21), the processing unit 53 starts a process of calculating and recording vehicle state information including information on energy consumption and driver state information including information on the driver's psychological state and physical load (step S23). Specifically, the driver information calculation unit 65 of the processing unit 53 acquires information identifying the driver and records the acquired driver identification information. For example, the driver information calculation unit 65 identifies the driver based on facial features of the driver acquired from image data from the in-vehicle camera 37 and records identification information such as an identification number assigned to each driver. The driver information calculation unit 65 may also identify the driver based on information input by the driver.

[0085] The driver information calculation unit 65 also estimates the driver's psychological state from the facial muscles of the driver acquired from image data captured by the in-vehicle camera 37. The driver's psychological state is preferably displayed using the same standard as the psychological state of passersby H, for example, but may be displayed using a different standard as long as it can be converted to the same standard as the psychological state of passersby H. The driver information calculation unit 65 also estimates the driver's physical load based on the myoelectric potential signal output from the biosensor 39. The driver's physical load is displayed as, for example, the amount of calories burned per unit time.

[0086] Furthermore, the vehicle information detection unit 67 of the processing unit 53 calculates the direction of movement of the vehicle 1 based on the position information input from the position detection sensor 35. For example, the vehicle information detection unit 67 can calculate the direction of movement of the vehicle 1 based on changes over time in the position information input at each predetermined processing cycle. Furthermore, the vehicle information detection unit 67 detects the running state of the vehicle 1 based on the sensor signal output from the vehicle state sensor 33. Specifically, the vehicle information detection unit 67 detects the speed, acceleration, angular velocity, steering angle, accelerator opening, and brake operation amount of the vehicle 1. Furthermore, the vehicle information detection unit 67 detects whether the direction indicators are on or off.

[0087] Furthermore, the vehicle information detection unit 67 calculates the energy consumption corresponding to the speed and acceleration when the speed of the vehicle 1 changes from one speed to another by accelerating or decelerating. For example, if the driving force source 9 is an internal combustion engine, the vehicle information detection unit 67 determines the energy consumption as the integrated value of the fuel injection amount while the speed of the vehicle 1 changes from one speed to another by accelerating or decelerating. Also, if the driving force source 9 is a drive motor, the vehicle information detection unit 67 determines the energy consumption as the integrated value of the power consumption while the speed of the vehicle 1 changes from one speed to another by accelerating or decelerating. The data on the energy consumption of the vehicle 1 may use design parameters of the vehicle 1 instead of actual measurement data.

[0088] The process of calculating and recording the vehicle condition information and the driver condition information, which is started in step S23, is thereafter repeatedly executed in a predetermined processing cycle.

[0089] Next, the processing unit 53 executes an assistance process to assist the driver in driving the vehicle 1 (step S25). In the present embodiment, the processing unit 53 executes, as the assistance process, a notification process to notify the driver of notification information for assisting the driver in driving.

[0090] FIG. 10 shows a flowchart of the assistance processing. First, the driving scene determination unit 69 of the processing unit 53 determines whether the vehicle 1 is passing through a specific driving scene (step S31). Specifically, the driving scene determination unit 69 compares the road structure in the surrounding environment of the vehicle 1 detected by the surrounding environment detection unit 63 and the traffic conditions indicating the positional relationships of surrounding traffic participants around the vehicle 1 with conditions set as the specific driving scene, and determines that the vehicle 1 is passing through the specific driving scene if the road structure and traffic conditions correspond to the specific driving scene. For example, the driving scene determination unit 69 may determine that the vehicle 1 is passing through the specific driving scene when it detects road structure and traffic conditions that correspond to the specific driving scene, or may determine that the vehicle 1 is passing through the specific driving scene when the vehicle 1 approaches the corresponding road structure and traffic conditions within a certain distance. The certain distance may be a fixed value set to, for example, 30 to 50 meters, or may be a value that changes depending on the speed of the vehicle 1.

[0091] If the driving scene determination unit 69 does not determine that the vehicle 1 will pass through the specific driving scene (S31 / No), the determination of step S31 is repeated. On the other hand, if the driving scene determination unit 69 determines that the vehicle 1 will pass through the specific driving scene (S31 / Yes), the processing unit 53 executes pre-passage processing (step S33). The pre-passage processing is support processing that is performed before the vehicle 1 passes through the specific driving scene.

[0092] 11 shows a flowchart of the pre-passage processing. In the pre-passage processing, the communication control unit 71 of the processing unit 53 transmits information indicating that the vehicle 1 is passing through a specific driving scene and vehicle measurement data, along with the driver's identification information, to the management server 110 (step S41). The vehicle measurement data includes position information of the vehicle 1, information about the surrounding environment detected immediately before, vehicle state information, and driver state information. In other words, the driving assistance device 50 transmits to the management server 110 information indicating the location of the vehicle 1 in the specific driving scene, the driving condition of the vehicle 1, the psychological state and physical load of the driver, and the conditions of surrounding traffic participants.

[0093] Next, the notification processing unit 73 of the processing unit 53 receives the notification information transmitted from the management server 110 (step S43). As will be described later, the notification information transmitted by the management server 110 is information that is set based on the difference that appears in the overall optimization of traffic participants, including surrounding traffic participants, when the driver of the vehicle 1 changes or does not change his or her driving behavior when passing through a specific driving scene. The notification information transmitted by the management server 110 in the pre-passage processing includes support information for recommended driving behavior that can improve the overall optimization when the vehicle 1 passes through a specific driving scene.

[0094] Next, the notification processing unit 73 notifies the driver of the received notification information (step S45). Specifically, the notification processing unit 73 controls the driving of the notification device 43 and notifies the driver of the support information for the recommended driving behavior received from the management server 110. In this way, the notification processing unit 73 can encourage the driver to take driving behavior that can improve overall optimization in a specific driving situation.

[0095] 10 , after the pre-passage process is executed, the driving scene determination unit 69 determines whether the vehicle 1 has passed through the specific driving scene (step S35). For example, the driving scene determination unit 69 determines that the vehicle 1 has passed through the specific driving scene when the vehicle 1 leaves an area with a road structure or traffic conditions that correspond to the specific driving scene determined in step S31.

[0096] If the driving scene determination unit 69 does not determine that the vehicle 1 has passed through the specific driving scene (S35 / No), the determination of step S35 is repeated. On the other hand, if the driving scene determination unit 69 determines that the vehicle 1 has passed through the specific driving scene (S35 / Yes), the processing unit 53 executes post-passage processing (step S37). The post-passage processing is support processing that is performed after the vehicle 1 has passed through the specific driving scene.

[0097] 12 shows a flowchart of the post-passage processing. In the post-passage processing, the communication control unit 71 determines whether the driver has changed their driving behavior while the vehicle 1 is passing through the specific driving scene (step S51). For example, the communication control unit 71 determines whether the vehicle 1 has slowed down or stopped before a pedestrian crossing or given way to another vehicle, based on the vehicle measurement data collected and recorded while the vehicle 1 is passing through the specific driving scene. The content of the determination is preset according to the specific driving scene.

[0098] If the communication control unit 71 determines that the driver changed his driving behavior while the vehicle 1 was passing through the specific driving scene (S51 / Yes), it records the vehicle measurement data collected while the vehicle 1 was passing through the specific driving scene as vehicle measurement data when the driver changed his driving behavior (step S53), and proceeds to step S59.

[0099] On the other hand, if the communication control unit 71 does not determine that the driver changed his / her driving behavior while the vehicle 1 passed through the specific driving scene (S51 / No), the communication control unit 71 determines whether the vehicle 1 was affected by a change in the driving behavior of another vehicle while the vehicle 1 passed through the specific driving scene (step S55). For example, the communication control unit 71 determines whether the vehicle 1 suddenly decelerated as another vehicle slowed down or stopped in front of a pedestrian crossing, or whether the vehicle 1 was given the space in front of the other vehicle, based on the vehicle measurement data collected and recorded while the vehicle 1 passed through the specific driving scene. The content of the determination is set in advance depending on the specific driving scene.

[0100] If the communication control unit 71 determines that the vehicle 1 has been affected by a change in the driving behavior of another vehicle while passing through a specific driving scene (S55 / Yes), it records the vehicle measurement data collected while the vehicle 1 has passed through the specific driving scene as vehicle measurement data when it has been affected by a change in the driving behavior of another vehicle (step S57), and proceeds to step S59.

[0101] On the other hand, if the communication control unit 71 does not determine that the vehicle 1 was affected by a change in the driving behavior of another vehicle while passing through the specific driving scene (S55 / No), the process proceeds to step S59. In step S59, the communication control unit 71 transmits to the management server 110 information indicating that the vehicle 1 has completed passing through the specific driving scene and the vehicle measurement data collected and recorded while the vehicle 1 passed through the specific driving scene (step S59). Here, the vehicle measurement data transmitted to the management server 110 is one of the following: vehicle measurement data when the driver changed his driving behavior, vehicle measurement data when the vehicle 1 was affected by a change in the driving behavior of another vehicle, or vehicle measurement data when the driver did not change his driving behavior and was not affected by a change in the driving behavior of another vehicle.

[0102] The vehicle measurement data includes time-series data of the position information of the vehicle 1, information on the surrounding environment detected immediately before, vehicle state information, and driver state information. In other words, while the vehicle 1 passes through a specific driving scene, the driving assistance device 50 transmits to the management server 110 information indicating what driving behavior the driver selected, the driving condition of the vehicle 1, the psychological state and physical load of the driver, and the conditions of surrounding traffic participants.

[0103] Next, the notification processing unit 73 of the processing unit 53 receives the advice information transmitted from the management server 110 (step S61). As will be described later, the notification information transmitted by the management server 110 is advice information that is set based on the overall optimization of traffic participants, including surrounding traffic participants, while the vehicle 1 passes through the specific driving scene. The advice information transmitted by the management server 110 in the post-passage processing includes information indicating how the vehicle 1 affected the overall optimization while passing through the specific driving scene, or what driving behavior should have been taken.

[0104] Next, the notification processing unit 73 notifies the driver of the received advice information (step S63). Specifically, the notification processing unit 73 controls the driving of the notification device 43 and notifies the driver of the advice information received from the management server 110. This allows the driver to know how his or her driving behavior while passing through the specific driving scene contributed to overall optimization, or what driving behavior to adopt the next time the driver passes through the same specific driving scene.

[0105] 9 , after the assistance process is executed, the processing unit 53 determines whether the in-vehicle system has stopped (step S27), and if it is determined that the in-vehicle system has not stopped (S27 / No), the processing unit 53 repeats the assistance process of step S25. On the other hand, if it is determined that the in-vehicle system has stopped (S27 / Yes), the processing unit 53 stops the process.

[0106] As described above, when the vehicle 1 encounters a specific driving scene, the driving assistance device 50 acquires assistance information from the management server 110 before passing through the specific driving scene and notifies the driver of information on recommended driving behavior. After the vehicle 1 passes through the specific driving scene, the driving assistance device 50 acquires advice information based on the driver's driving behavior while passing through the specific driving scene from the management server 110 and notifies the driver of the advice information. Furthermore, each time the driving assistance device 50 passes through a specific driving scene, it transmits vehicle measurement data collected while passing through the specific driving scene to the management server 110.

[0107] <1-4. Management Server> Next, the management server 110 will be described in detail.

[0108] The management server 110 functions as a device that sets information for assisting vehicle driving by having one or more processors, such as CPUs, execute a computer program. The computer program is a computer program that causes the processor to execute the operations, described below, that should be performed by the management server 110. The computer program executed by the processor may be recorded on a recording medium that functions as a storage unit (memory) 115 provided in the management server 110, or may be recorded on a recording medium built into the management server 110 or any recording medium that can be externally attached to the management server 110.

[0109] The recording medium for recording a computer program may be a magnetic medium such as a hard disk, a floppy disk, or a magnetic tape; an optical recording medium such as a CD-ROM, a DVD, or a Blu-ray (registered trademark); a magneto-optical medium such as a floptical disk; a memory element such as a RAM or a ROM; a flash memory such as a USB memory or an SSD; or any other medium capable of storing a program.

[0110] (1-4-1. Functional Configuration) Fig. 13 is a block diagram showing the functional configuration of the management server 110. The management server 110 includes a communication unit 111, a processing unit 113, a storage unit 115, and a collected data storage unit 117. The communication unit 111 is an interface for communicating with the mobile terminal 130 and the driving assistance device 50 via the communication network 105. The processing unit 113 includes one or more CPUs, and executes overall optimization calculation processing and driving assistance processing.

[0111] The storage unit 115 includes one or more memories, and stores various parameters used in the calculation processes and information on the results of calculations, as well as computer programs executed by the processing unit 113. The storage unit 115 may be a magnetic medium such as a hard disk, a floppy disk, or a magnetic tape, an optical recording medium such as a CD-ROM, a DVD, or a Blu-ray (registered trademark), a magneto-optical medium such as a floptical disk, a storage element such as a RAM or a ROM, a flash memory such as a USB memory or an SSD, or other recording medium.

[0112] The collected data storage unit 117 stores vehicle measurement data measured in a predetermined specific driving scene, which is transmitted from first terminals (driving assistance devices) mounted on each of a plurality of vehicles, and passerby measurement data transmitted from second terminals (mobile terminals) carried by each passerby. The collected data storage unit 117 may be a magnetic medium such as a hard disk, floppy disk, or magnetic tape, an optical recording medium such as a CD-ROM, DVD, or Blu-ray (registered trademark), a magneto-optical medium such as a floptical disk, a flash memory such as a USB memory or SSD, or another recording medium.

[0113] The collected data storage unit 117 stores the vehicle measurement data of the vehicle 1 collected while the vehicle 1 passes through a predetermined specific driving scene, the vehicle measurement data of other vehicles that were present in the specific driving scene, and the pedestrian measurement data of the pedestrian H, in association with each other. The data stored in the collected data storage unit 117 will be described in detail later.

[0114] The processing unit 113 includes a communication control unit 121, an overall optimization calculation unit 123, and a driving support processing unit 125. The functions of these units are realized by the execution of a computer program by a processor.

[0115] The communication control unit 121 communicates with the driving assistance device (first terminal) 50 mounted on the vehicle 1 and the mobile terminal (second terminal) 130 carried by the passerby H, and controls the transmission and reception of various data or information. Specifically, the communication control unit 121 communicates with the driving assistance device 50, receives information indicating that the vehicle 1 is passing through a predetermined specific driving scene or vehicle measurement data, and transmits notification information. The communication control unit 121 also communicates with the mobile terminal 130, receives location information, transmits a data transmission request to the mobile terminal 130 of the passerby H present in the specific driving scene, and receives passerby measurement data transmitted from the mobile terminal 130.

[0116] The overall optimization calculation unit 123 calculates load state values ​​indicating changes in the load state of each of the drivers of other vehicles and pedestrians H present in a specific driving scene, including a first load state value when the driver of the assisted vehicle 1 changes his / her driving behavior in a predetermined specific driving scene, and a second load state value when the driver of the assisted vehicle 1 does not change his / her driving behavior in a predetermined specific driving scene. In this embodiment, the overall optimization calculation unit 123 calculates a first psychological state value and a first physical load state value when the driver of the assisted vehicle 1 changes his / her driving behavior in a predetermined specific driving scene, and a second psychological state value and a second physical load state value when the driver of the assisted vehicle 1 does not change his / her driving behavior in a predetermined specific driving scene.

[0117] Furthermore, the overall optimization calculation unit 123 calculates an overall optimization evaluation value that indicates the influence of the driving behavior of the assistance target vehicle on the overall optimization based on the difference between the first load state value and the second load state value. In this embodiment, the overall optimization calculation unit 123 calculates an overall optimization evaluation value based on the difference between the first psychological state value and the second psychological state value, and an overall optimization evaluation value based on the difference between the first physical load state value and the second physical load state value.

[0118] Furthermore, in this embodiment, the overall optimization calculation unit 123 further calculates an overall optimization evaluation value based on the difference between the first energy state value and the second energy state value, which are energy state values ​​indicating changes in the energy consumption of other vehicles present in a specific driving scene, and which are a first energy state value when the driver of the assisted vehicle 1 changes his / her driving behavior in a predetermined specific driving scene, and a second energy state value when the driver of the assisted vehicle 1 does not change his / her driving behavior in a predetermined specific driving scene.

[0119] The driving assistance processing unit 125 executes processing to assist the driving of the assistance target vehicle 1 based on the overall optimization evaluation value calculated by the overall optimization calculation unit 123. In this embodiment, the driving assistance processing unit 125 sets notification information to assist the driving of the assistance target vehicle 1. The notification information consists of assistance information that is notified before the assistance target vehicle 1 passes through a predetermined specific driving scene, and advice information that is notified after the assistance target vehicle 1 has passed through the predetermined specific driving scene. The set notification information is transmitted to the driving assistance device 50 by the communication control unit 121.

[0120] (1-4-2. Processing Operation) Fig. 14 shows a flowchart of the processing operation by the management server 110. The flowchart shown in Fig. 14 is repeatedly executed for each predetermined processing cycle.

[0121] First, the communication control unit 121 receives data transmitted from the driving assistance devices (first terminals) 50 mounted on the multiple vehicles 1 and the mobile terminals (second terminals) 130 carried by the passersby H (step S71). When any of the driving assistance devices (first terminals) 50 executes the process of transmitting information indicating that the vehicle 1 is passing through a predetermined specific driving scene and vehicle measurement data in the above-mentioned step S41, the communication control unit 121 receives this information and data. The communication control unit 121 also receives location information transmitted from the mobile terminals (second terminals) 130.

[0122] Next, the overall optimization calculation unit 123 determines whether or not information indicating that a predetermined specific driving scene will be passed is acquired from the driving assistance device (first terminal) 50 of any vehicle (assisted vehicle) 1 among the vehicles 1 equipped with the driving assistance device 50 (step S73). If the overall optimization calculation unit 123 determines that information indicating that a predetermined specific driving scene will be passed is not acquired from the driving assistance device 50 of any vehicle (assisted vehicle) 1 (S73 / No), the overall optimization calculation unit 123 returns to step S71. On the other hand, if the overall optimization calculation unit 123 determines that information indicating that a predetermined specific driving scene will be passed is acquired from the driving assistance device 50 of any vehicle (assisted vehicle) 1 (S73 / Yes), the overall optimization calculation unit 123 executes a pre-passage assistance information setting process (step S75). The pre-passage assistance information setting process is a process of setting assistance information to be notified to the driver of the assisted vehicle 1 before the assisted vehicle 1 passes through the predetermined specific driving scene.

[0123] FIG. 15 shows a flowchart of the pre-passage support information setting process.

[0124] The overall optimization calculation unit 123 identifies surrounding traffic participants present in a specific driving scene that the assisted vehicle 1 is about to pass through based on the location information transmitted from the driving assistance device 50 of each vehicle 1 and the mobile terminal 130 of the passerby H, and acquires vehicle measurement data and passerby measurement data from the first terminal and second terminal of the surrounding traffic participants, respectively (step S91).

[0125] Specifically, the surrounding traffic participants to be targeted for overall optimization are set according to a specific driving scene. For example, the target surrounding traffic participants are identified as other vehicles and passersby H present within a predetermined area set according to the specific driving scene, with the position of the supported vehicle 1 as a reference. For example, the predetermined area may be an area within a certain distance from the supported vehicle 1, or an area within a distance that the supported vehicle 1 can reach in a predetermined time, determined according to the travel speed of the supported vehicle 1. Furthermore, the target surrounding traffic participants may be identified as a predetermined number of other vehicles and passersby H present within the predetermined area, in descending order of proximity to the supported vehicle 1. As a result, other vehicles or passersby H with a low impact on the overall optimization are not included in the calculation of the overall optimization, allowing appropriate support for the supported vehicle 1.

[0126] In addition, the overall optimization calculation unit 123 sends a message to the driving assistance device 50 and mobile terminal 130 of the identified surrounding traffic participants requesting the transmission of vehicle measurement data and passerby measurement data, and acquires the vehicle measurement data and passerby measurement data that are returned.

[0127] Next, the global optimization calculation unit 123 extracts, from the vehicle measurement data and passerby measurement data stored in the collected data storage unit 117, vehicle measurement data and passerby measurement data previously collected in the same specific driving scene as the specific driving scene through which the assistance target vehicle 1 is about to pass (step S93). The extracted vehicle measurement data and passerby measurement data are measurement data that were transmitted to the management server 110 from the driving assistance device 50 of a vehicle that previously existed in the specific driving scene and the mobile terminal 130 of the passerby H, and that were stored in association with each other. The same specific driving scene is not limited to specific driving scenes at the same position on the map, but refers to a specific scene in which at least the road structure and the traffic environment, such as the locations and moving speeds of surrounding traffic participants, are judged to be within a predetermined error range.

[0128] Next, based on the extracted vehicle measurement data and passerby measurement data, the overall optimization calculation unit 123 calculates a first psychological state value and a first physical load state value that indicate changes in the load state of surrounding traffic participants when the driver of the supported vehicle 1 changes his or her driving behavior while passing through a specific driving scene, and a first energy state value that indicates changes in the energy consumption (consumption rate) of other vehicles (step S95).

[0129] Specifically, the overall optimization calculation unit 123 extracts vehicle measurement data and passerby measurement data of surrounding traffic participants when a driver of a vehicle changes his or her driving behavior while passing through a specific driving scene from the extracted measurement data. Furthermore, the overall optimization calculation unit 123 calculates a first psychological state value Cx1_i relating to a change in the psychological state of each surrounding traffic participant and a first physical load state value Cy1_i relating to a change in the physical load of each surrounding traffic participant based on the extracted vehicle measurement data and passerby measurement data. Furthermore, in this embodiment, the overall optimization calculation unit 123 further calculates a first energy state value Cz1_i relating to a change in the energy consumption of another vehicle based on the extracted vehicle measurement data.

[0130] For example, if there are five other vehicles and two passersby H as surrounding traffic participants in addition to the support target vehicle 1, the overall optimization calculation unit 123 calculates a first psychological state value Cx1_i (i = 1, 2 ... 7) indicating a change in the psychological state of each of the surrounding traffic participants and a first physical load state value Cy1_i (i = 1, 2 ... 7) indicating a change in the physical load of each of the surrounding traffic participants. In addition, the overall optimization calculation unit 123 calculates a first energy state value Cz1_i (i = 1, 2 ... 5) indicating a change in the energy consumption of each of the other vehicles.

[0131] The first psychological state value Cx1_i represents a change (difference) in the psychological state of each surrounding traffic participant. In this embodiment, the psychological state is calculated on 11 levels ranging from -5 to 5, with a larger positive absolute value indicating a more positive psychological state. Therefore, the larger the positive absolute value of the psychological state value Cx, the more positive the change in the psychological state. In other words, the first psychological state value Cx1_i does not provide an overall evaluation of the psychological state of each surrounding traffic participant while the assisted vehicle 1 passes through a specific driving scene, but rather indicates how much the psychological state of each surrounding traffic participant changes due to a change in the driving behavior of the assisted vehicle 1.

[0132] The first physical load state value Cy1_i represents a change (difference) in the physical load of each surrounding traffic participant. In this embodiment, the physical load is calculated as the amount of calories burned per unit time, and a positive value with a larger absolute value indicates a higher physical load. Therefore, a negative value of the physical load state value Cy with a larger absolute value indicates a decrease in the physical load. In other words, the first physical load state value Cy1_i does not provide an overall evaluation of the physical load of each surrounding traffic participant while the assisted vehicle 1 passes through a specific driving scene, but rather indicates how the physical load of each surrounding traffic participant changes due to changes in the driving behavior of the assisted vehicle 1.

[0133] The first energy state value Cz1_i represents a change (difference) in the energy consumption of each other vehicle. Energy consumption is the amount of fuel or electricity consumed to drive the vehicle's driving power source, and the larger the absolute value of the energy state value Cz is, the more fuel-efficient the driving behavior of each vehicle is. In other words, the first energy state value Cz1_i does not provide an overall evaluation of the energy consumption of each other vehicle while the assisted vehicle 1 passes through a specific driving scene, but rather indicates how much the energy consumption of each surrounding traffic participant changes due to a change in the driving behavior of the assisted vehicle 1.

[0134] Next, based on the extracted vehicle measurement data and passerby measurement data, the overall optimization calculation unit 123 calculates a second psychological state value and a second physical load state value that indicate the change in the load state of surrounding traffic participants when the driver of the support target vehicle 1 does not change his / her driving behavior while passing through the specific driving scene, and a second energy state value that indicates the change in energy consumption (consumption rate) of other vehicles (step S97).

[0135] Specifically, the overall optimization calculation unit 123 extracts, from the extracted measurement data, vehicle measurement data and passerby measurement data of surrounding traffic participants when the driver of a given vehicle did not change his or her driving behavior while passing through a specific driving scene. Furthermore, the overall optimization calculation unit 123 calculates a second psychological state value Cx2_i relating to a change in the psychological state of each surrounding traffic participant and a second physical load state value Cy2_i relating to a change in the physical load of each surrounding traffic participant based on the extracted vehicle measurement data and passerby measurement data. In this embodiment, the overall optimization calculation unit 123 further calculates a second energy state value Cz2_i relating to a change in the energy consumption of another vehicle based on the extracted vehicle measurement data.

[0136] The second psychological state value Cx2_i indicates how much the psychological state of each surrounding traffic participant will change if the driving behavior of the assisted vehicle 1 continues. The second physical load state value Cy2_i indicates how much the physical load of each surrounding traffic participant will change if the driving behavior of the assisted vehicle 1 continues. The second energy state value Cz2_i indicates how much the energy consumption of each surrounding traffic participant will change if the driving behavior of the assisted vehicle 1 continues.

[0137] In the above-mentioned example of a scene where lanes merge, a case where a vehicle's driving behavior continues corresponds to a situation where a vehicle traveling in the lane where the vehicle is being merged continues traveling without yielding the space in front of its own vehicle to another vehicle traveling in the lane where the vehicle is being merged. Also, a case where a vehicle's driving behavior changes corresponds to a situation where a vehicle traveling in the lane where the vehicle is being merged slows down or stops to yield the space in front of its own vehicle to another vehicle traveling in the lane where the vehicle is being merged.

[0138] In the example of the scene of crossing a pedestrian crossing described above, the case where the vehicle's driving behavior continues corresponds to a situation where the vehicle continues to drive without stopping in front of the pedestrian crossing despite the presence of a pedestrian approaching the pedestrian crossing, and the case where the vehicle's driving behavior changes corresponds to a situation where the vehicle slows down or stops in front of the pedestrian crossing to give priority to the pedestrian crossing.

[0139] Next, the overall optimization calculation unit 123 calculates an overall optimal evaluation value based on the calculated first psychological state value Cx1_i, first physical load state value Cy1_i, and first energy state value Cz1_i, and the calculated second psychological state value Cx2_i, second physical load state value Cy2_i, and second energy state value Cz2_i (step S99). The overall optimal evaluation value includes either or both of an overall optimal evaluation value CX based on changes in the psychological states of the surrounding traffic participants and an overall optimal evaluation value CY based on changes in the physical load states of the surrounding traffic participants. In this embodiment, the overall optimization calculation unit 123 calculates the overall optimal evaluation value CX based on changes in the psychological states of the surrounding traffic participants, the overall optimal evaluation value CY based on changes in the physical load states of the surrounding traffic participants, and the overall optimal evaluation value CZ based on changes in the energy consumption of other surrounding vehicles.

[0140] In this embodiment, the overall optimum evaluation values ​​CX, CY, and CZ are expressed by the following equation (1).

[0141]

[0142] The overall optimal evaluation value CX indicates the sum of changes in the psychological states of the surrounding traffic participants, and indicates how and to what extent the psychological states of the surrounding traffic participants change as a whole due to a change in the driving behavior of the supported vehicle 1. The greater the absolute value of the overall optimal evaluation value CX, which is a positive value, the more positively the psychological states of the surrounding traffic participants change overall.

[0143] The overall optimal evaluation value CY indicates the sum of changes in the physical load states of the surrounding traffic participants, and indicates how and to what extent the physical load states of the surrounding traffic participants change overall due to changes in the driving behavior of the supported vehicle 1. The greater the absolute value of the overall optimal evaluation value CY, which is a positive value, the greater the overall reduction in the physical load of the surrounding traffic participants.

[0144] The overall optimal evaluation value CZ indicates the sum of changes in the energy consumption of other surrounding vehicles, and indicates how and to what extent the energy consumption of other surrounding vehicles changes overall due to changes in the driving behavior of the supported vehicle 1. The overall optimal evaluation value CZ is a positive value, and the larger the absolute value, the more fuel-efficient the driving behavior of other surrounding vehicles becomes overall.

[0145] These overall optimization evaluation values ​​CX, CY, and CZ are all positive values, and the larger the absolute value, the greater the effect of improving overall optimization.

[0146] Next, the driving assistance processing unit 125 sets a recommended driving behavior to be notified to the driver of the assistance target vehicle 1 based on the calculated overall optimal evaluation values ​​CX, CY, and CZ (step S101). For example, when one or both of the overall optimal evaluation values ​​CX and CY are equal to or greater than a predetermined reference value, the driving assistance processing unit 125 sets a driving behavior that is assumed to change the driving behavior as the recommended driving behavior.

[0147] Alternatively, the driving assistance processing unit 125 may convert the overall optimal evaluation values ​​CX, CY related to the psychological state and physical load, or all the overall optimal evaluation values ​​CX, CY, CZ, into the same index value, calculate the sum thereof, and if the value of the sum is equal to or greater than a predetermined reference value set in advance, set the driving behavior that is assumed to change the driving behavior as the recommended driving behavior.

[0148] When a plurality of changes in driving behaviors are expected in a specific driving scene, the overall optimization calculation unit 123 calculates the first psychological state value Cx1_i, the first physical load state value Cy1_i, and the first energy state value Cz1_i for each driving behavior in step S95 described above, and calculates the overall optimal evaluation values ​​CX, CY, and CZ for each driving behavior in step S99. In addition, in step S101, the driving assistance processing unit 125 may set, as the recommended driving behavior, the driving behavior for which either one or both of the overall optimal evaluation values ​​CX and CY are maximum.

[0149] Alternatively, the driving assistance processing unit 125 may convert the overall optimal evaluation values ​​CX, CY related to the psychological state and physical load, or all the overall optimal evaluation values ​​CX, CY, CZ, into the same index value, calculate their sum, and set the driving behavior that produces the maximum sum as the recommended driving behavior.

[0150] In addition, the driving assistance processing unit 125 may set the recommended driving behavior by weighting the psychological state or physical load so that the priority item designated by the driver of the assistance target vehicle 1 is reflected.

[0151] 14 , the driving assistance processing unit 125 transmits assistance information to the driving assistance device 50 of the assistance target vehicle 1 that is about to pass through the specific driving scene in accordance with the set recommended driving behavior (step S77). The assistance information includes at least information on the recommended driving behavior, but may also include information on the overall optimal evaluation values ​​CX, CY, CZ and / or information indicating how the recommended driving behavior will affect the load states of surrounding traffic participants.

[0152] The notification processing unit 73 of the driving support device 50 that has received the support information notifies the driver of the received support information, thereby enabling the driver to take driving actions that can improve overall optimization in a specific driving situation.

[0153] Next, the overall optimization calculation unit 123 executes a post-passage advice information setting process (step S79). The post-passage advice information setting process is a process for setting advice information to be notified to the driver of the supported vehicle 1 after the supported vehicle 1 has passed through a predetermined specific driving scene.

[0154] 16 shows a flowchart of the post-passage advice information setting process. The global optimization calculation unit 123 acquires information indicating completion of passing through a specific driving scene from the driving assistance device 50 of the assistance target vehicle (step S111).

[0155] Next, the global optimization calculation unit 123 acquires vehicle measurement data and passerby measurement data recorded while the assistance target vehicle 1 was passing through the specific driving scene from the driving assistance devices 50 and mobile terminals 130 of the traffic participants present in the specific driving scene (step S113). The target traffic participants are the assistance target vehicle 1 and the surrounding traffic participants identified in step S91.

[0156] The overall optimization calculation unit 123 transmits a message to the driving assistance devices 50 and mobile devices 130 of the surrounding traffic participants, requesting the transmission of vehicle measurement data and passerby measurement data, and receives the returned vehicle measurement data and passerby measurement data. At that time, the overall optimization calculation unit 123 transmits a message requesting the transmission of measurement data, specifying the measurement time (start time to end time). The vehicle measurement data of the assistance target vehicle 1 is acquired together with information indicating the completion of passing through the specific driving scene. The vehicle measurement data of the assistance target vehicle 1 is acquired together with information indicating whether the vehicle measurement data is the vehicle measurement data when the driver changed his / her driving behavior while passing through the specific driving scene, or the vehicle measurement data when he / she did not change his / her driving behavior.

[0157] Next, the overall optimization calculation unit 123 calculates the overall optimal evaluation values ​​CX, CY, and CZ based on the acquired vehicle measurement data and pedestrian measurement data of traffic participants and the past measurement data stored in the collected data storage unit 117 (step S115).

[0158] 17 is a flowchart showing the overall optimization evaluation value calculation process in step S115. First, the overall optimization calculation unit 123 determines whether the vehicle measurement data acquired from the driving assistance device 50 of the assistance target vehicle 1 is vehicle measurement data when the driver has changed his / her driving behavior or vehicle measurement data when the driver has not changed his / her driving behavior (step S121).

[0159] When the overall optimization calculation unit 123 determines that the vehicle measurement data is vehicle measurement data obtained when the driver changed his / her driving behavior (S121 / Yes), the overall optimization calculation unit 123 calculates the first psychological state value Cx1_i, the first physical load state value Cy1_i, and the first energy state value Cz1_i using the acquired measurement data in accordance with the processing of step S95 described above (step S123). In addition, the overall optimization calculation unit 123 reads out the calculation results of the second psychological state value Cx2_i, the second physical load state value Cy2_i, and the second energy state value Cz2_i calculated in step S97 of the pre-passage support information setting processing (step S125). Then, the overall optimization calculation unit 123 calculates the overall optimal evaluation values ​​CX, CY, CZ based on the calculated first psychological state value Cx1_i, first physical load state value Cy1_i, and first energy state value Cz1_i, and the read-out second psychological state value Cx2_i, second physical load state value Cy2_i, and second energy state value Cz2_i, in accordance with the processing of step S99 described above (step S131).

[0160] In this case, if the surrounding traffic participants include a traffic participant whose psychological state has significantly changed to a negative state, the global optimization calculation unit 123 may calculate the global optimal evaluation value excluding the traffic participant. This makes it possible to prevent feedback that suppresses the overall optimal driving behavior due to the influence of some traffic participants, even though it changes the psychological state of the other surrounding traffic participants to a positive state and has a positive effect on the overall optimization in terms of energy consumption and physical load.

[0161] For example, the global optimization calculation unit 123 may determine traffic participants to be excluded based on whether the driver satisfies conditions such as an unsmooth driving behavior of the vehicle, a violation of manners, etc. Specifically, in the situation where multiple lanes merge as described above, when the lane on the merging side is moving at high speed, if the driver suddenly brakes to make space ahead and give space to other vehicles traveling in the lane on the merging side, the driver who suddenly brakes may be excluded from the surrounding traffic participants.

[0162] On the other hand, if the overall optimization calculation unit 123 does not determine that the vehicle measurement data is vehicle measurement data when the driver changed his / her driving behavior (S121 / No), the overall optimization calculation unit 123 uses the acquired measurement data to calculate the second psychological state value Cx2_i, the second physical load state value Cy2_i, and the second energy state value Cz2_i in accordance with the processing of step S97 of the pre-passage support information setting processing (step S127). In addition, the overall optimization calculation unit 123 reads out the calculation results of the first psychological state value Cx1_i, the first physical load state value Cy1_i, and the first energy state value Cz1_i calculated in the above-mentioned step S95 (step S129). Then, the overall optimization calculation unit 123 calculates the overall optimal evaluation values ​​CX, CY, CZ based on the read-out first psychological state value Cx1_i, first physical load state value Cy1_i, and first energy state value Cz1_i, and the calculated second psychological state value Cx2_i, second physical load state value Cy2_i, and second energy state value Cz2_i, in accordance with the processing of step S99 described above (step S131).

[0163] 16 , the driving assistance processing unit 125 sets advice information to be notified to the driver of the assistance target vehicle 1 based on the calculated overall optimization evaluation values ​​CX, CY, and CZ (step S117). The advice information is information about the impact of the driving behavior of the driver of the assistance target vehicle 1 on the overall optimization, and includes information about the impact on at least the psychological state or physical stress of surrounding traffic participants due to the driver of the assistance target vehicle 1 changing or not changing his / her driving behavior. For example, the driving assistance processing unit 125 may set the overall optimization evaluation values ​​CX, CY, and CZ as the advice information to quantitatively indicate the impact on the overall optimization. Alternatively, the overall optimization calculation unit 123 may convert the overall optimization evaluation values ​​CX, CY, and CZ related to the psychological state and physical stress, or all of the overall optimization evaluation values ​​CX, CY, and CZ, into the same index value, calculate the sum of the index values, and set the sum as the advice information.

[0164] At this time, if the overall optimal evaluation values ​​CX, CY, and CZ are equal to or smaller than predetermined thresholds, the driving assistance processing unit 125 may exclude them from the advice information. This makes it possible to avoid providing unnecessary advice based on slight changes in the load state when the assistance target vehicle 1 has barely changed its driving behavior while passing through a specific driving scene.

[0165] Furthermore, the driving assistance processing unit 125 may identify past driving actions in which the overall optimal evaluation value increased by a predetermined reference value or more in a specific driving scene that the assistance target vehicle 1 passed through, based on the data stored in the collected data storage unit 117, and set advice information to be notified to the driver of the assistance target vehicle 1 based on the past driving actions. For example, in a case where the overall optimal evaluation values ​​are calculated for a plurality of driving actions in the pre-passage assistance information setting process, one or more of the driving actions in which the overall optimal evaluation value increased by a predetermined reference value or more may be set as advice information to be notified to the driver after the specific driving scene has passed. Note that whether or not the advice information for the driving actions can be set may be determined in response to a request from the driver.

[0166] Next, the driving assistance processing unit 125 associates the vehicle measurement data of the assistance target vehicle 1 and the surrounding traffic participants acquired in step S113 with each other and stores the data in the collected data storage unit 117 (step S119).

[0167] 14 , the driving assistance processing unit 125 transmits the set advice information to the driving assistance device 50 of the assisted vehicle 1 (step S81). The notification processing unit 73 of the driving assistance device 50 that has received the advice information notifies the driver of the received advice information. This allows the driver to know how his or her driving behavior while passing through the specific driving scene contributed to overall optimization, or what driving behavior to adopt the next time the driver passes through the same specific driving scene.

[0168] 1-5. Effects As described above, the driving assistance system 100 according to the first embodiment of the present disclosure calculates an overall optimization evaluation value that indicates the impact on overall optimization of changes in the driver's driving behavior when the assisted vehicle 1 passes through a specific driving scene based on measurement data collected from vehicle measurement data and passerby measurement data, and assists the driving of the assisted vehicle based on the overall optimization evaluation value. The calculated overall optimization evaluation value indicates changes in the psychological state and physical stress of surrounding traffic participants present in the specific driving scene due to the driving behavior of the driver of the assisted vehicle 1. According to this embodiment, it is possible to assist the driver of the assisted vehicle 1 in driving so as to adopt altruistic driving behavior that does not impose stress on other traffic participants. Furthermore, the driving assistance system 100 according to the first embodiment of the present disclosure can also suppress illegal driving behavior by assisting the driver to adopt overall optimal driving behavior.

[0169] Furthermore, the driving assistance system 100 according to this embodiment notifies the driver of a recommended driving behavior for passing through a specific driving scene based on past measurement data before the assisted vehicle 1 passes through the specific driving scene. Therefore, the driver can take an altruistic driving behavior that does not burden other traffic participants when passing through the specific driving scene. Furthermore, the driving assistance system 100 according to this embodiment can also notify the driver of the driving behavior with the highest overall optimization evaluation value as a recommended driving behavior before the assisted vehicle 1 passes through the specific driving scene. This allows the driver to take a driving behavior that can most improve overall optimization when passing through the specific driving scene.

[0170] Furthermore, the driving assistance system 100 according to this embodiment notifies the driver of advice information regarding the impact of driving actions performed by the driver of the assisted vehicle 1 on overall optimization after the assisted vehicle 1 passes through a specific driving scene. Therefore, the driver can know how his / her driving actions have affected the load conditions of surrounding traffic participants, and can know the driving actions he / she should take from next time onwards. Furthermore, the driving assistance system 100 according to this embodiment can also identify driving actions that have increased the overall optimization evaluation value by a predetermined reference value or more, based on past measurement data, after the assisted vehicle 1 passes through a specific driving scene, and notify the driver of the assisted vehicle 1 of the advice information. This allows the driver to know what driving actions he / she should have taken when passing through a specific driving scene, and can know the driving actions he / she should take from next time onwards.

[0171] <<2. Second Embodiment>> Next, a driving assistance system according to a second embodiment will be described.

[0172] While the driving assistance system according to the first embodiment described above is a system that assists the driver in manual driving of the assisted vehicle, the driving assistance system of the present disclosure can also be applied as a system that assists the assisted vehicle in automatic driving. Hereinafter, the driving assistance system according to the second embodiment will be described, focusing mainly on the differences from the driving assistance system according to the first embodiment.

[0173] <2-1. Basic Configuration of Driving Assistance System> The basic configuration of the driving assistance system according to this embodiment may be configured similarly to the basic configuration of the driving assistance system according to the first embodiment shown in FIG.

[0174] In the driving assistance system according to this embodiment, the assisted vehicle 1 is configured to be able to execute autonomous driving control. When the assisted vehicle 1 encounters a specific driving scene, the management server 110 sets recommended driving behaviors based on past measurement data before passing through the specific driving scene, and transmits assistance information to the driving assistance device 50 of the assisted vehicle 1. Upon receiving the assistance information, the driving assistance device 50 sets driving conditions for autonomous driving of the assisted vehicle 1 based on the information on the recommended driving behavior, and outputs the information on the driving conditions to the vehicle control unit 41.

[0175] 18 is a block diagram showing the functional configuration of a driving assistance device (first terminal) 50 of an assisted vehicle 1 to which the driving assistance system according to this embodiment can be applied. In this embodiment, the driving assistance device 50 includes a driving condition setting unit 75 instead of the notification processing unit 73. The driving condition setting unit 75 sets driving conditions for causing the assisted vehicle 1 to travel in autonomous driving. Specifically, the driving condition setting unit 75 sets a target vehicle speed or target acceleration / deceleration, and a target steering angle or target steering angular velocity for the assisted vehicle 1 in accordance with the recommended driving behavior set by the management server 110, and outputs information on the set driving conditions to the vehicle control unit 41.

[0176] The functional configuration of the mobile terminal 130 held by the passerby H and the functional configuration of the management server 110 may be the same as the functional configuration of the driving assistance system 100 according to the first embodiment, and therefore detailed explanations will be omitted.

[0177] <2-2. Processing Operation of Driving Assistance Device> Next, processing operation of the driving assistance device in the driving assistance system according to this embodiment will be described.

[0178] The main routine of the processing operation by the driving assistance device 50 may be the same as the processing operation by the driving assistance device of the driving assistance system according to the first embodiment shown in Fig. 9. Among these, in the assistance processing in step S25, the pre-passage processing in step S33 of the flowchart shown in Fig. 10 is different from that in the first embodiment. Hereinafter, the pre-passage processing by the driving assistance device 50 of the driving assistance system according to this embodiment will be described with reference to Fig. 19.

[0179] First, the communication control unit 71 of the processing unit 53 transmits information indicating that the vehicle 1 is passing through a specific driving scene, vehicle measurement data, and the driver's identification information to the management server 110 in a procedure similar to step S41 of the flowchart shown in Figure 11 (step S41).

[0180] Next, the driving condition setting unit 75 of the processing unit 53 receives the support information transmitted from the management server 110 (step S43). The support information transmitted by the management server 110 includes information on recommended driving behaviors that can improve overall optimization when the vehicle 1 passes through a specific driving scene.

[0181] Next, the driving condition setting unit 75 detects the surrounding environment of the vehicle 1 based on the sensor signal or image data output from the surrounding environment sensor 31 (step S46). As a result, the driving condition setting unit 75 recognizes changes in the road structure in the direction of travel of the support target vehicle 1 and changes in the positions, movement direction, and movement speed of surrounding traffic participants.

[0182] Next, the driving condition setting unit 75 sets driving conditions according to changes in the surrounding environment based on the information on the recommended driving behavior acquired from the management server 110 (step S47). Specifically, the driving condition setting unit 75 sets a target acceleration / deceleration speed and a target steering angular velocity to realize a driving behavior in accordance with the recommended driving behavior according to changes in the surrounding environment.

[0183] Next, the driving condition setting unit 75 outputs information about the set driving conditions to the vehicle control unit 41 (step S48). The vehicle control unit 41, which has received the information about the driving conditions, sets operation command values ​​for the driving force source 9, the electric steering device 15, and the hydraulic unit 16 based on the information about the driving conditions, and controls the driving of the driving force source 9, the electric steering device 15, and the hydraulic unit 16.

[0184] Next, the driving condition setting unit 75 determines whether the assisted vehicle 1 has passed through the specific driving scene (step S49). If the driving condition setting unit 75 does not determine that the assisted vehicle 1 has passed through the specific driving scene (S49 / No), the process returns to step S46 and the setting and output of the driving conditions are repeated. On the other hand, if the driving condition setting unit 75 determines that the assisted vehicle 1 has passed through the specific driving scene (S49 / Yes), the pre-passage processing is terminated.

[0185] The assistance target vehicle 1 repeatedly detects the surrounding environment, sets driving conditions, and outputs driving conditions from the time it encounters a driving scene until it completes passing through. Specifically, in the example of the driving scene where lanes merge as described above, it is assumed that the recommended driving behavior is set to leave space ahead of the vehicle at the merging point of the lane where the vehicle is traveling by automated driving in the lane where the vehicle is to be merged, and to yield space to another vehicle traveling in the lane where the vehicle is to be merged.

[0186] In this case, the driving condition setting unit 75 sets driving conditions that allow the assisted vehicle 1 to travel while maintaining a predetermined distance between the assisted vehicle 1 and the preceding vehicle until the assisted vehicle 1 approaches a point within a predetermined distance from the merging point. Furthermore, when the assisted vehicle 1 approaches a point within a predetermined distance from the merging point, the driving condition setting unit 75 starts decelerating the assisted vehicle 1 to create a space between the assisted vehicle 1 and the preceding vehicle that allows another vehicle traveling in the merging lane to enter. This behavior corresponds to changing driving behavior. At this time, the driving condition setting unit 75 sets a target deceleration within a range equal to or less than the maximum deceleration to avoid a sudden deceleration. Furthermore, when the other vehicle enters the space ahead of the host vehicle and the merging is completed, the driving condition setting unit 75 sets driving conditions that allow the assisted vehicle 1 to travel while maintaining a predetermined distance between the assisted vehicle 1 and the merging vehicle.

[0187] <2-3. Effects> As described above, the driving assistance system 100 according to the second embodiment of the present disclosure calculates an overall optimization evaluation value that indicates the impact on overall optimization of changes in the driver's driving behavior when the assisted vehicle 1 passes through a specific driving scene, based on measurement data obtained by collecting vehicle measurement data and passerby measurement data, and assists the driving of the assisted vehicle based on the overall optimization evaluation value. The calculated overall optimization evaluation value indicates changes in the psychological state and physical stress of surrounding traffic participants present in the specific driving scene due to the driving behavior of the automated driving of the assisted vehicle 1, and according to this embodiment, it is possible to assist the automated driving of the assisted vehicle 1 so that it adopts altruistic driving behavior that does not impose stress on other traffic participants.

[0188] In particular, the driving assistance system 100 according to this embodiment sets recommended driving behaviors for passing through a specific driving scene based on past measurement data and sets driving conditions for autonomous driving before the assisted vehicle 1 passes through the specific driving scene. Therefore, when passing through the specific driving scene by autonomous driving, the assisted vehicle 1 can take altruistic driving behaviors that do not burden other traffic participants.

[0189] Although the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the technology of the present disclosure is not limited to such examples. It is clear that a person skilled in the art of the technology to which the present disclosure pertains can conceive of various modified or altered examples within the scope of the technical ideas described in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure.

[0190] For example, the information used to calculate the overall optimal evaluation value is not limited to the examples described in the above embodiments. For example, when calculating the overall optimal evaluation value for the psychological states of the surrounding traffic participants, information on the activity schedule of each surrounding traffic participant may be used. For example, the overall optimal evaluation value may be calculated using activity schedule information stored in the mobile terminal 130 held by the passerby H or in the mobile terminal of the driver connected to the driving assistance device in a communicable manner, and information on the destination and target arrival time set in the vehicle's navigation system. By incorporating information on whether the surrounding traffic participants are in a hurry, determined from the activity schedule of the surrounding traffic participants, into the psychological states, the accuracy of estimating the psychological states of each surrounding traffic participant can be improved. Therefore, the overall optimization can be improved in line with reality.

[0191] In the above embodiment, the management server executes the process of setting information for assisting the driving of the vehicle based on various information, but the driving assistance device of the assisted vehicle may have this function. In addition, some of the functions of the mobile terminal, the management server, and the driving assistance device described in the above embodiment may be provided in other components.

[0192] In addition, the technology of the present disclosure can also be realized as a vehicle equipped with the driving assistance system described in the above embodiment, a driving assistance processing method using the driving assistance system, a computer program that causes a computer to function as the above driving assistance system, and a non-transitory tangible recording medium on which the computer program is recorded.

[0193] 1: Vehicle 50: Driving assistance device 100: Driving assistance system 110: Management server 130: Mobile terminal CX: Overall optimum evaluation value CY: Overall optimum evaluation value CZ: Overall optimum evaluation value Cx: Mental state value Cx1_i: First mental state value Cx2_i: Second mental state value Cy: Physical load state value Cy1_i: First physical load state value Cy2_i: Second physical load state value Cz: Energy state value Cz1_i: First energy state value Cz2_i: Second energy state value

Claims

1. A driving assistance system that assists driving of a vehicle, - Vehicle measurement data including driver state information relating to the load state of the driver of the vehicle, measured in a predetermined specific driving scene set in advance, transmitted from a first terminal mounted on each of the vehicles; Passerby measurement data including passerby state information related to the load state of the passerby measured in the predetermined specific driving scene, which is transmitted from a second terminal carried by each passerby; a collected data storage unit that stores the a processing unit that executes a process of assisting the driving of the assistance target vehicle based on the collected vehicle measurement data and the collected pedestrian measurement data, The processing unit an overall optimization calculation process that calculates, based on the vehicle measurement data and the passerby measurement data, load state values ​​that indicate changes in the load state of each of the drivers of other vehicles and passersby present in the predetermined specific driving scene while the assistance target vehicle is traveling in the predetermined specific driving scene, the first load state value when the driver of the assistance target vehicle changes his / her driving behavior in the predetermined specific driving scene, and the second load state value when the driver of the assistance target vehicle does not change his / her driving behavior in the predetermined specific driving scene, and calculates an overall optimization evaluation value that indicates the influence of the driving behavior of the assistance target vehicle on overall optimization based on the difference between the first load state value and the second load state value; a driving assistance process for assisting driving of the assistance target vehicle based on the overall optimal evaluation value; A driving assistance system that performs the following:

2. The load state of the driver and the passerby is either one or both of a psychological load and a physical load. The driving assistance system according to claim 1 .

3. The processing unit In the overall optimization calculation process, After the assistance target vehicle has passed through the predetermined specific driving scene, the vehicle measurement data of the assistance target vehicle and the other vehicle passing through the predetermined specific driving scene, and the passerby measurement data of passersby who were present in the predetermined specific driving scene are acquired; calculating the first load state value and the second load state value and the overall optimum evaluation value based on the acquired vehicle measurement data and the pedestrian measurement data and the vehicle measurement data and the pedestrian measurement data stored in the collected data storage unit; In the driving assistance process, notifying the driver of the assistance target vehicle of information on the influence of the driving behavior of the driver of the assistance target vehicle on the overall optimization based on the overall optimization evaluation value; The driving assistance system according to claim 1 .

4. The processing unit In the driving assistance process, identifying past driving behaviors in which the driving behavior was changed and the overall optimal evaluation value was equal to or greater than a predetermined reference value in the predetermined specific driving scene that the assisted vehicle has passed through, and notifying the driver of the assisted vehicle of advice information based on the past driving behaviors; The driving assistance system according to claim 3 .

5. The processing unit In the overall optimization calculation process, before the assistance target vehicle passes through the predetermined specific driving scene, calculate the first load state value and the second load state value when the assistance target vehicle passes through the predetermined specific driving scene based on the vehicle measurement data and the pedestrian measurement data stored in the collected data storage unit, and calculate the overall optimum evaluation value; In the driving assistance process, determining a recommended driving behavior based on the overall optimal evaluation value, and notifying the driver of the assistance target vehicle of information about the recommended driving behavior; The driving assistance system according to claim 1 .

6. The processing unit In the overall optimization calculation process, calculating the first load state value and the second load state value and the overall optimum evaluation value for a plurality of driving actions when passing through the predetermined specific driving scene; In the driving assistance process, the driving action with the largest overall optimal evaluation value is designated as the recommended driving action, and information about the recommended driving action is notified to the driver of the assistance target vehicle. The driving assistance system according to claim 5 .

7. The processing unit In the overall optimization calculation process, before the assistance target vehicle passes through the predetermined specific driving scene, calculate the first load state value and the second load state value when the assistance target vehicle passes through the predetermined specific driving scene based on the vehicle measurement data and the pedestrian measurement data stored in the collected data storage unit, and calculate the overall optimum evaluation value; In the driving assistance process, determining a driving behavior that will result in the overall optimal evaluation value being equal to or greater than a predetermined reference value, and setting driving conditions for the autonomous driving of the assistance target vehicle; The driving assistance system according to claim 1 .

8. the vehicle measurement data includes vehicle status information relating to energy consumption of the vehicle; The processing unit In the overall optimization calculation process, further calculating a first energy state value indicating a change in the energy consumption of each of the other vehicles when the driver of the assisted vehicle changes his / her driving behavior while the assisted vehicle is traveling in the predetermined specific driving scene, and a second energy state value indicating a change in the energy consumption of each of the other vehicles when the driver of the assisted vehicle does not change his / her driving behavior while the assisted vehicle is traveling in the predetermined specific driving scene, and calculating an overall optimization evaluation value indicating an influence on the overall optimization by the driving behavior of the assisted vehicle based on the difference between the first energy state value and the second energy state value; The driving assistance system according to claim 1 .

9. A driving assistance processing method for assisting driving of a vehicle, comprising: The computer Vehicle measurement data including driver state information relating to the load state of the driver of the vehicle, measured in a predetermined specific driving scene set in advance, transmitted from a first terminal mounted in each vehicle; Passerby measurement data including passerby state information related to the load state of the passerby measured in the predetermined specific driving scene, which is transmitted from a second terminal carried by each passerby; calculates load state values ​​indicating changes in the load state of each of the drivers of other vehicles and pedestrians present in the predetermined specific driving scene while the assisted vehicle is traveling in the predetermined specific driving scene, the load state values ​​being a first load state value when the driver of the assisted vehicle changes his / her driving behavior in the predetermined specific driving scene, and a second load state value when the driver of the assisted vehicle does not change his / her driving behavior in the predetermined specific driving scene, based on the above, and calculates an overall optimization evaluation value indicating the influence of the driving behavior of the assisted vehicle on overall optimization based on the difference between the first load state value and the second load state value; Assisting the driving of the assistance target vehicle based on the overall optimal evaluation value; A driving assistance processing method for performing the above.

10. On the computer, Vehicle measurement data including driver state information relating to the load state of the driver of the vehicle, measured in a predetermined specific driving scene set in advance, transmitted from a first terminal mounted in each vehicle; Passerby measurement data including passerby state information related to the load state of the passerby measured in the predetermined specific driving scene, which is transmitted from a second terminal carried by each passerby; calculates load state values ​​indicating changes in the load state of each of the drivers of other vehicles and pedestrians present in the predetermined specific driving scene while the assisted vehicle is traveling in the predetermined specific driving scene, the load state values ​​being a first load state value when the driver of the assisted vehicle changes his / her driving behavior in the predetermined specific driving scene, and a second load state value when the driver of the assisted vehicle does not change his / her driving behavior in the predetermined specific driving scene, based on the above, and calculates an overall optimization evaluation value indicating the influence of the driving behavior of the assisted vehicle on overall optimization based on the difference between the first load state value and the second load state value; Assisting the driving of the assistance target vehicle based on the overall optimal evaluation value; A non-transitory tangible recording medium on which a computer program that executes the above is recorded.

Images