Driving evaluation device, driving evaluation method, driving evaluation program, and recording medium

Abstract

To provide a driving evaluation device that can give evaluations for driving behavior with good manners, and that encourages drivers to yield and be considerate of others through the evaluations, thereby contributing to the realization of a better traffic society.SOLUTION: A driving evaluation device includes: an acquisition unit that acquires driving behavior information indicating driving behavior performed by a driver of a vehicle in a specific scene related to road traffic; a behavior determination unit that determines whether or not the driving behavior corresponds to a recommended driving behavior, which is a driving behavior that is not instructed by a road sign, a road marker, or a traffic signal and is a driving behavior recommended for the driver of the vehicle in the specific scene; and an evaluation information output unit that outputs evaluation information that contributes to the evaluation of the driver of the vehicle based on the determination by the behavior determination unit. The recommended driving behavior is associated with at least one of a plurality of items classifying the contribution of the recommended driving behavior in road traffic. The evaluation information output unit outputs the evaluation information for each of the items.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a driving evaluation device, a driving evaluation method, a driving evaluation program, and a recording medium. [Background technology]

[0002] Devices for evaluating the driving behavior of drivers are known. For example, Patent Document 1 discloses an on-board device that measures the distance between the vehicle and another vehicle ahead and records information including the distance when the vehicle is stopped. Patent Document 1 also discloses that the recorded information can be analyzed as needed after the vehicle has finished traveling, making it possible to grasp the driving behavior tendencies of each driver. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2020-46728 Summary of the Invention [Problem to be solved by the invention]

[0004] In road traffic, smoother traffic can be achieved by driving with good manners that show consideration for others, such as by yielding to others, while also ensuring safety by following road signs, etc. However, one of the challenges is that good driving behavior, despite its positive impact on traffic society, is difficult to objectively evaluate by drivers themselves or third parties.

[0005] The present invention has been made in consideration of the above points, and one of its objectives is to provide a driving evaluation device that can give evaluations to drivers for driving behavior that shows good manners, and that encourages drivers to be considerate of others and give in to traffic, thereby contributing to the realization of a better transportation society. [Means for solving the problem]

[0006] The invention described in claim 1 comprises a surrounding situation acquisition unit that acquires surrounding situation information that indicates the situation around the vehicle; a driving information acquisition unit that acquires driving information that indicates information regarding the driving of the vehicle; recommended behavior information that associates each of a plurality of scenes related to road traffic with recommended driving behaviors that are behaviors recommended to the driver of the vehicle for each of the scenes, and a behavior determination unit that determines whether the driving behavior performed by the driver in a scene that the vehicle actually encountered corresponds to the recommended driving behavior based on the surrounding situation information and the driving information; and an evaluation information output unit that outputs evaluation information that contributes to evaluating the driving of the driver of the vehicle based on the determination by the behavior determination unit, wherein the recommended driving behavior is driving behavior that is not indicated by road signs, road markings, or traffic lights.

[0007] The invention described in claim 9 is a driving evaluation method performed by a driving evaluation device, comprising: a surrounding situation acquisition step in which a surrounding situation acquisition unit acquires surrounding situation information indicating the situation around the vehicle; a driving information acquisition step in which a driving information acquisition unit acquires driving information related to the driving of the vehicle; a behavior determination step in which a behavior determination unit determines whether the driving behavior performed by the driver in a scene actually encountered by the vehicle corresponds to the recommended driving behavior, based on recommended behavior information in which the surrounding situation information, the driving information, and each of a plurality of scenes related to road traffic are associated with a recommended driving behavior that is an action recommended to the driver of the vehicle for each scene; and an evaluation information output step in which an evaluation information output unit outputs evaluation information that contributes to evaluating the driving of the driver of the vehicle, based on the determination by the behavior determination unit, wherein the recommended driving behavior is driving behavior that is not indicated by a road sign, road marking, or traffic light.

[0008] The invention described in claim 10 is a driving evaluation program executed by a driving evaluation device having a computer, which causes the computer to execute the following steps: a surrounding situation acquisition step of acquiring surrounding situation information indicating the situation around the vehicle; a driving information acquisition step of acquiring driving information related to the driving of the vehicle by a driving information acquisition unit; a behavior determination step of determining whether the driving behavior performed by the driver in a scene actually encountered by the vehicle corresponds to the recommended driving behavior, based on recommended behavior information in which the surrounding situation information, the driving information, and each of a plurality of scenes related to road traffic are associated with a recommended driving behavior that is an action recommended to the driver of the vehicle for each scene; and an evaluation information output step of outputting evaluation information that contributes to evaluating the driving of the driver of the vehicle, based on the determination by the behavior determination unit, wherein the recommended driving behavior is driving behavior that is not indicated by a road sign, road marking, or traffic light. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a diagram showing a vehicle equipped with a driving evaluation device according to an embodiment and its surrounding environment; [Figure 2] 1 is a diagram showing a front seat portion of a vehicle in which a driving evaluation device according to an embodiment is installed. [Figure 3] 1 is a block diagram showing a configuration of a driving evaluation device according to an embodiment; [Figure 4] FIG. 2 is a diagram illustrating an example of a recommended driving behavior according to an embodiment. [Figure 5] 4 is a flowchart illustrating an example of a driving evaluation performed by the driving evaluation device according to the embodiment. [Figure 6] FIG. 2 is a diagram showing an example of criteria for driving evaluation executed by the driving evaluation device according to the embodiment. [Figure 7] FIG. 10 is a diagram showing an example of a learning model used for driving evaluation according to a modified example of the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In the following description and accompanying drawings, substantially the same or equivalent parts are designated by the same reference numerals. [Example]

[0011] Fig. 1 is a diagram showing a vehicle equipped with a driving evaluation device 10 according to an embodiment and its surrounding environment. The driving evaluation device 10 is mounted on a host vehicle M1. Fig. 1 also shows the host vehicle M1 equipped with the driving evaluation device 10, as well as a driver DR of the host vehicle M1, a pedestrian P1 present around the host vehicle M1, another vehicle M2 that is another vehicle as seen from the host vehicle M1, and the driver P2 of the other vehicle M2.

[0012] The driving evaluation device 10 is a device that evaluates the driving behavior of the driver DR of the vehicle M1 based on whether or not the driver DR has performed well-mannered driving behavior appropriate for the road traffic situation encountered.

[0013] For example, in FIG. 1, a host vehicle M1 and another vehicle M2 are traveling on a road R, and a puddle W exists in the direction of travel of the host vehicle M1. A pedestrian P1 is walking on the sidewalk near the puddle W. The host vehicle M1 encounters a situation in which "there is a pedestrian near the puddle ahead."

[0014] One of the driving actions appropriate for this situation would be for the host vehicle M1 to slow down (drive slowly) as it passes near the pedestrian P1 or to avoid the puddle, which would prevent the host vehicle M1 from splashing up water from the puddle and prevent the clothes of the pedestrian P1 from getting soiled by the splashed water from the puddle.

[0015] Also, in the situation shown in Figure 1, when pedestrian P1 is heading towards road R, he or she encounters a situation in which there is a pedestrian trying to cross the road ahead at the edge of the road. One of the appropriate driving actions in this situation would be to slow down or stop. By doing so, it is possible to confirm the pedestrian's intention to cross and allow the pedestrian to cross safely.

[0016] It is also appropriate to flash your headlights several times to signal to the pedestrian P1 and other vehicles M2 when slowing down or stopping. By signaling to the pedestrian P1 by flashing your headlights, for example, you can let the pedestrian P1 know that your vehicle M1 is slowing down or stopping, allowing the pedestrian P1 to quickly cross the road, minimizing the disruption to the flow of vehicles caused by the crossing.

[0017] In addition, by passing the lights, a signal can be sent to the driver P2 of the other vehicle M2, making the driver P2 aware of the presence of the pedestrian P1 more reliably and earlier, and encouraging the driver P2 to take driving actions that will allow the pedestrian P1 to cross safely.

[0018] For example, as described above, the driving evaluation device 10 gives a good evaluation to the driver DR when the driver DR drives appropriately in a particular situation, or when the driver DR's driving causes the vehicle M1 to be in an appropriate driving state in a particular situation.

[0019] Fig. 2 is a diagram showing the front seat area of ​​the host vehicle M1. Fig. 2 shows, as an example of installation, a case in which the driving evaluation device 10 is installed near the center console of the dashboard DB of the front seat of the host vehicle M1. The host vehicle M1 is equipped with equipment for acquiring information necessary or usable for the driving evaluation device 10 to perform the driving evaluation described above.

[0020] The camera 11 is a camera capable of capturing images of the surroundings of the vehicle M1. The camera 11 is provided, for example, on a dashboard DB and oriented so as to be able to capture an image in front of the vehicle M1. In addition to the camera 11 capable of capturing an image in front of the vehicle M1, the vehicle M1 may be equipped with a plurality of cameras 11 arranged so as to be able to capture images to the sides or rear of the vehicle M1. The camera 11 is connected to the driving evaluation device 10 so as to be able to communicate with the driving evaluation device 10, and is capable of transmitting a signal of the captured image to the driving evaluation device 10.

[0021] The steering wheel 13 is a member that receives a steering operation for steering the host vehicle M1. The steering wheel 13 is provided rotatably with respect to the dashboard DB. When the steering wheel 13 is turned, the wheels that serve as steered wheels of the host vehicle M1 turn accordingly.

[0022] The accelerator pedal 15 is provided under the driver's feet and is a member that receives an operation related to control of a driving motor such as an engine or a motor of the host vehicle M1 by depressing the accelerator pedal 15. In other words, the accelerator pedal 15 is a member that receives a steering operation related to acceleration and deceleration of the host vehicle M1.

[0023] The brake pedal 17 is provided under the driver's seat and is a member that receives an operation related to brake control of the host vehicle M1 by the driver's depression action. That is, the brake pedal 17 is a member that receives a steering operation related to deceleration of the host vehicle M1.

[0024] The GPS receiver 19 is a device that receives signals (GPS signals) from GPS (Global Positioning System) satellites. The GPS receiver 19 is disposed, for example, on a dashboard DB. The GPS receiver 19 may be disposed anywhere as long as it can receive GPS signals. The GPS receiver 19 is communicably connected to the driving evaluation device 10 and can transmit the received GPS signals to the driving evaluation device 10.

[0025] The touch panel display 21 is a touch panel monitor that combines a display device, such as a liquid crystal display, capable of displaying images with a touch panel. The touch panel display 21 is disposed, for example, in the center console of the dashboard DB. For example, the touch panel display 21 may be attached to the dashboard DB.

[0026] The touch panel display 21 is communicably connected to the driving evaluation device 10 and is capable of displaying a screen based on the control of the driving evaluation device 10. The touch panel display 21 is also capable of transmitting to the driving evaluation device 10 a signal representing an input operation to the touch panel received from the user.

[0027] The speaker 23 is provided, for example, on the interior side of the A-pillar AP. The speaker 23 is communicably connected to the driving evaluation device 10 and is capable of emitting sounds such as voices based on the control of the driving evaluation device 10.

[0028] 3 is a block diagram showing the configuration of the driving evaluation device 10. As shown in FIG. 3, the driving evaluation device 10 is configured by connecting each unit via a system bus 25.

[0029] The input unit 27 is an interface that communicably connects the driving evaluation device 10 with devices provided in the host vehicle M1.

[0030] The input unit 27 is an interface that connects the driving evaluation device 10 and the camera 11 so that they can communicate with each other.

[0031] The input unit 27 is an interface that communicatively connects the driving evaluation device 10 with a steering sensor 13S that is a sensor that detects physical quantities related to the operation of the steering wheel 13, such as the amount of rotation and rotational force.

[0032] The input unit 27 is an interface that communicatively connects the driving evaluation device 10 with an accelerator sensor 15S, which is a sensor that detects physical quantities related to operation such as the amount of movement and travel speed of the accelerator pedal 15. The input unit 27 is also an interface that communicatively connects the driving evaluation device 10 with a brake sensor 17S, which is a sensor that detects physical quantities related to operation such as the amount of movement and travel speed of the brake pedal 17.

[0033] The input unit 27 is an interface that communicatively connects the driving evaluation device 10 with the GPS receiver 19, the gyro sensor GY, and the acceleration sensor AC. The gyro sensor GY is a sensor that can detect, for example, the lateral angle (attitude), angular velocity, or angular acceleration of the host vehicle M1. The acceleration sensor AC is a sensor that can detect the acceleration in the traveling direction of the host vehicle M1 as viewed from above the host vehicle M1, that is, in a direction intersecting the front-to-rear direction. The acceleration sensor AC can also detect, for example, the acceleration in the lateral direction (width direction) perpendicular to the traveling direction of the host vehicle M1.

[0034] The driving evaluation device 10 acquires driving state information indicating the driving state of the host vehicle M1 from sensor signals of the steering sensor 13S, accelerator sensor 15S, brake sensor 17S, GPS receiver 19, gyro sensor GY, and acceleration sensor AC.

[0035] The input unit 27 is an interface that connects the driving evaluation device 10 and the touch panel of the touch panel display 21 so that they can communicate with each other.

[0036] The storage unit 29 is configured with, for example, a hard disk drive, a solid state drive (SSD), a flash memory, etc., and stores various programs executed by the driving evaluation device 10. Note that the various programs may be acquired, for example, from another server device or the like via a network, or may be recorded on a recording medium and read via various drive devices. In other words, the various programs stored in the storage unit 29 can be transmitted via a network, or can be recorded on a computer-readable recording medium and transferred.

[0037] A recommended action database (hereinafter referred to as recommended action DB) 29A is constructed in the storage unit 29. The recommended action database 29A stores data necessary for information processing related to the evaluation of the driving of the driver DR of the vehicle M1 by the driving evaluation device 10. The data necessary for this information processing is, for example, data recording examples of specific situations in which good driving manners are expected, recommended action information recording details of recommended driving actions recommended in each of the specific situations, and the like.

[0038] An example of the contents of the recommended action DB is shown in Figure 4. The recommended action DB stores information indicating a number of specific situations in which good driving behavior is expected, among the situations that a vehicle may encounter in road traffic. For example, as shown in Figure 4, each specific situation is stored with an identifier (ID) assigned to it.

[0039] As shown in Figure 4, each of a number of specific situations is associated with a recommended driving behavior, which is a driving behavior recommended for that situation. The recommended driving behavior is a driving behavior that, when performed in the corresponding situation, will result in good driving manners.

[0040] Specifically, the recommended driving behavior in the scene where "a pedestrian is about to cross the road in a section where there is no crosswalk" (scene ID: ST1) is "stop and wait until the pedestrian has finished crossing." This driving behavior allows pedestrians to cross the road safely, even on roads without crosswalks.

[0041] Furthermore, in addition to the driving behavior of "stopping and waiting until the pedestrian has finished crossing," the scene ST1 may be further associated with other driving behaviors, such as "flashing the lights to warn oncoming vehicles when stopping" or "turning on hazard lights to warn following vehicles when stopping." These actions accompanying a stop can alert surrounding vehicles and ensure the safety of pedestrians.

[0042] In the example shown in Fig. 4, a scene in which "there is a pedestrian near a puddle ahead" (scene ID: ST2) is associated with a recommended driving behavior of "driving slowly until you have passed the pedestrian." For example, if the driver DR of the vehicle M1 takes such a behavior, splashing of water can be suppressed when the vehicle M1 passes through a puddle on the road, and water can be prevented from splashing on pedestrians. Therefore, it is possible to prevent pedestrians from feeling uncomfortable.

[0043] Additionally, the ST2 scenario is associated with the recommended driving behavior of "turning on hazard lights to warn following vehicles when slowing down." This behavior associated with slowing down can prevent following vehicles from splashing water, ensuring a more comfortable passage for pedestrians.

[0044] In the example shown in Figure 4, the scene where "there is an oncoming vehicle on a narrow road where passing is difficult" (scene ID: ST3) is associated with the recommended driving actions of "stop and wait until the oncoming vehicle passes" and "back up to a wide area and wait until the oncoming vehicle passes." Such driving actions can ensure the safety of the vehicle and oncoming vehicles. Furthermore, the recommended driving action associated with scene ST3 can be said to be a well-behaved driving action that is considerate of the driver of the oncoming vehicle in that it allows the oncoming vehicle to pass first.

[0045] The recommended driving behaviors illustrated in Fig. 4 are behaviors that cannot be performed simply by following the instructions of road signs, road markings, and traffic lights. In other words, they are driving behaviors that are not instructed by road signs, road markings, and traffic lights. The recommended driving behaviors in this embodiment are driving behaviors that take into consideration other drivers, surrounding pedestrians, and other drivers, on the premise that the instructions of road signs, road markings, and traffic lights are followed. For example, they can be said to be well-mannered driving behaviors in that they further ensure the safety of surrounding people and give priority to the passage of surrounding people over the passage of the vehicle itself.

[0046] The control unit 31 is configured with a CPU (Central Processing Unit) 31A, a ROM (Read Only Memory) 31B, a RAM (Random Access Memory) 31C, etc., and functions as a computer. The CPU 31A reads and executes various programs stored in the ROM 31B and the storage unit 29, thereby realizing various functions.

[0047] The control unit 31 acquires video of the surroundings of the host vehicle M1 from the camera 11 via the input unit 27. The video acquired from the camera 11 is information indicating the surrounding conditions of the host vehicle M1, such as the shape of the road around the host vehicle M1, the presence or absence of road signs, the presence of surrounding vehicles and pedestrians, etc. The control unit 31 functions as a surrounding condition acquisition unit that acquires surrounding condition information indicating the surrounding conditions of the host vehicle M1.

[0048] The control unit 31 recognizes the scene that the host vehicle M1 actually encounters, for example, based on the acquired surrounding situation information.

[0049] The control unit 31 acquires travel information related to the travel of the host vehicle M1 from various sensors provided in the host vehicle M1 via the input unit 27. The travel information is, for example, information indicating the travel state or operation state of the host vehicle M1.

[0050] For example, the control unit 31 receives signals from the gyro sensor GY and the acceleration sensor AC to acquire information indicating the driving state of the vehicle M1, such as the acceleration and traveling direction, as driving information. Note that the control unit 31 may also acquire information indicating the driving state by receiving signals indicating the lighting state of the headlights and turn signals from sensors (not shown) that detect the lighting state of the headlights and turn signals.

[0051] The control unit 31 also receives signals indicating physical quantities related to operation, such as the amount of rotation and rotational force of the steering wheel 13. The control unit 31 also receives signals indicating physical quantities related to operation, such as the amount of movement and speed of the accelerator pedal 15, and signals indicating physical quantities related to operation, such as the amount of movement and speed of the brake pedal 17. Based on these signals, the control unit 31 obtains operation information indicating the state of operation with respect to steering or acceleration / deceleration of the host vehicle M1. Note that the control unit 31 may obtain driving state information by calculating the driving state of the host vehicle M1 based on this operation information. The control unit 31 may also be able to obtain information indicating the position of the shift lever as steering information.

[0052] The control unit 31 functions as a driving information acquisition unit that acquires driving information, which is information indicating the driving state of the vehicle M1, such as its speed, direction of travel, acceleration / deceleration, etc., or the operating state, including the steering angle of the steering wheels, based on signals from the above-mentioned sensors.

[0053] The control unit 31 recognizes the driving behavior of the driver DR of the vehicle M1 based on, for example, the acquired driving state information or operation information. Furthermore, for example, the control unit 31 may recognize the driving behavior of the driver DR of the vehicle M1 by combining the driving state information with the above-mentioned surrounding situation information.

[0054] The control unit 31 reads out and executes the driving evaluation program stored in the storage unit 29, thereby outputting information that contributes to the evaluation of the driving of the driver DR of the host vehicle M1.

[0055] For example, when executing the driving evaluation program, the control unit 31 makes a judgment regarding the driving evaluation of the driver DR of the vehicle M1 based on the above-mentioned surrounding situation information, driving information, and recommended action information stored in the recommended action database 29A.

[0056] For example, in executing the driving evaluation program, the control unit 31 determines whether a scene that the host vehicle M1 has actually encountered corresponds to a specific scene. For example, the specific scene is a scene in which good driving manners are expected. The specific scene is stored, for example, in the recommended driving DB of the memory unit 29. The control unit 31 determines whether the host vehicle M1 has encountered the specific scene based on the recommended behavior DB and the above-mentioned surrounding situation information. Note that this determination may be made based on the above-mentioned driving state and operation information, or may be made by taking these into account in addition to the surrounding situation information.

[0057] Furthermore, when the host vehicle M1 encounters a specific scene during execution of the driving evaluation program, the control unit 31 determines whether the driving behavior performed by the driver DR in that scene corresponds to the behavior recommended for that specific scene. The control unit 31 makes this determination based on the recommended behavior DB and the above-mentioned driving information or operation information. That is, the control unit 31 functions as a behavior determination unit that determines whether the driving behavior performed by the driver DR corresponds to the recommended driving behavior.

[0058] Based on a determination of whether the driving behavior performed by the driver DR corresponds to the recommended driving behavior, the control unit 31 outputs evaluation information indicating an evaluation of the driving of the driver DR of the vehicle M1 or information contributing to the evaluation (hereinafter, the evaluation information and information contributing to the evaluation will be referred to simply as evaluation information).

[0059] As the evaluation information, for example, a score for the good driving behavior of the driver DR is output. Alternatively, information indicating the number of times the good driving behavior of the driver DR is detected may be output. The control unit 31 functions as an evaluation information output unit that outputs information that contributes to such driving evaluation.

[0060] The output unit 33 is connected to the display and speaker 23 of the touch panel display 21 provided in the host vehicle M1. The output unit 33 is an interface for supplying various information to the display and speaker 23 in accordance with commands from the control unit 31.

[0061] For example, the output unit 33 supplies an image to a display for presenting evaluation information of the driver DR's driving to the driver DR. For example, the output unit 33 outputs the evaluation information as an evaluation result that can be presented to the driver DR of the host vehicle M1. For example, a score is displayed on the display as the evaluation result for the driving behavior of the driver DR.

[0062] For example, the output unit 33 supplies a voice to the speaker 23 to inform the driver DR of the evaluation information of the driver DR's driving. For example, a voice in which a score is read out as the evaluation result of the driver DR's driving behavior is output from the speaker 23.

[0063] The evaluation of the driving of the driver DR of the vehicle M1 will be specifically described with reference to Figures 4 and 5. Figure 4 is a diagram showing, in the form of a table, an example of recommended action information stored in the recommended action DB as described above.

[0064] FIG. 5 is a flowchart showing a driving evaluation routine RT1, which is an example of driving evaluation executed by the control unit 31 of the driving evaluation device 10.

[0065] For example, when the host vehicle M1 starts traveling, the control unit 31 starts the driving evaluation routine RT1. When the control unit 31 starts the driving evaluation routine RT1, it first starts acquiring surrounding situation information and traveling information. The control unit 31 functions as a surrounding situation acquisition unit that executes a surrounding situation acquisition step. The control unit 31 also functions as a traveling state acquisition unit that executes a traveling state acquisition step. Thereafter, the control unit 31 determines whether the host vehicle M1 has encountered a specific scene (step S101).

[0066] In step S101, a scene that the host vehicle M1 has actually encountered (hereinafter also referred to as an actual scene) is identified based on, for example, surrounding situation information. For example, the actual scene is identified based on the image from the camera 11, such as the condition of the road around the host vehicle M1, the surrounding traffic situation, and the presence or absence of pedestrians.

[0067] For example, if a puddle and a pedestrian near the puddle are captured in a video taken in front of the vehicle M1, the scene in which "there is a pedestrian near the puddle ahead" is identified as an actual scene.

[0068] For example, the actual scene may be identified based on driving information in addition to the surrounding situation information. For example, the actual scene may be identified based on the driving state of the host vehicle M1, such as the traveling direction and speed, in addition to the video.

[0069] In step S101, it is determined whether the actual scene corresponds to a specific scene. In step S101, for example, the control unit 31 refers to the recommended action DB 29A, and if the actual scene corresponds to one of a plurality of scenes stored in the recommended action DB, determines that the host vehicle M1 has encountered the specific scene.

[0070] For example, in step S101, it is determined that the host vehicle M1 has encountered a specific scene when the actual scene corresponds to any of the specific scenes shown in Fig. 4. For example, when the actual scene is a scene in which "there is a pedestrian near a puddle ahead," it corresponds to the scene ST2 shown in Fig. 4, and it is determined that the host vehicle M1 has encountered a specific scene.

[0071] When the control unit 31 determines in step S101 that the vehicle M1 has encountered a specific scene (step S101: YES), it determines whether the driver DR of the vehicle M1 performed a recommended driving behavior in the actual scene (step S102).

[0072] In step S102, a behavior determination step is executed to determine whether the driving behavior performed by the driver DR of the vehicle M1 in a specific situation that the vehicle M1 actually encountered corresponds to a recommended driving behavior recommended for the specific situation. In step S102, the control unit 31 functions as a behavior determination unit that executes the behavior determination step.

[0073] In step S102, for example, first, the driving behavior performed by the driver DR (hereinafter also referred to as actual driving behavior) is identified. The actual driving behavior is identified, for example, from the traveling state of the host vehicle M1 and the surrounding state.

[0074] Thereafter, it is determined whether the identified actual driving action corresponds to the recommended driving action associated with the scene identified in step S101. For example, the determination of whether the actual driving action corresponds to the recommended driving action is made by comparing the recommended driving action that is associated with the specific scene and stored in the recommended action DB as the driving action recommended for the specific scene with the driving action (actual driving action) performed by the driver DR of the vehicle M1 in the actual scene.

[0075] Specifically, for example, based on the driving information, the determination is made based on whether the host vehicle M1 has entered a state corresponding to the recommended driving behavior, such as being stopped. Also, for example, based on the operation information, the determination is made based on whether an operation (depressing the brake pedal) has been performed to put the host vehicle M1 into a state indicated in the recommended driving behavior (for example, decelerating or stopping).

[0076] In step S102, for example, in the table shown in Figure 4, if the specific scene identified in step S101 is "there is a pedestrian near a puddle ahead" (scene ST2), and the actual driving behavior corresponds to the recommended driving behavior associated with scene ST2, such as "drive slowly until you have passed the pedestrian" or "turn on your hazard lights to warn following vehicles when slowing down," it is determined that the driver DR has performed the recommended driving behavior.

[0077] When the control unit 31 determines in step S102 that the driver DR has performed the recommended driving behavior (step S102: YES), it evaluates the driving of the driver DR (step S103). For example, in step S103, a predetermined score for each recommended behavior is determined as a score for the driving of the driver DR.

[0078] In addition, when multiple recommended driving actions are performed as actions included in a specific scene, the contributions of those actions may be added together for evaluation. For example, in scene ST1, when two actions, "stopping and waiting until pedestrians have finished crossing" and "flashing the lights when stopping to warn oncoming vehicles," are performed, the points of the contributions of those actions may be added together to determine the score.

[0079] After executing step S103, control unit 31 causes the score to be displayed on the display of touch panel display 21 (step S104). In step S104, control unit 31 supplies an image for displaying the score as an evaluation result to the display of touch panel display 21 via output unit 33.

[0080] In steps S103 and S104, the control unit 31 functions as an evaluation information output unit that executes an evaluation information output step of outputting evaluation information that contributes to evaluating the driving of the driver DR of the vehicle M1. For example, when the control unit 31 determines in step S102 that the driver DR has performed a recommended driving behavior, it outputs evaluation information that affirms the driving behavior of the driver DR in step S104.

[0081] After executing step S104, the control unit 31 stores the score determined in step S103 in the storage unit 29 (step S105). In step S105, for example, information indicating the score may be transmitted to an external server device (not shown), and the score may be stored in the server device as an evaluation result of the driving of the driver DR of the vehicle M1.

[0082] After executing step S105, if the control unit 31 determines in step S101 that the specific situation has not been encountered (step S101: NO), or if it determines in step S102 that the driver DR has not performed the recommended driving behavior (step S102: NO), it terminates the driving evaluation routine RT1, returns to the beginning, and repeatedly executes the driving evaluation routine RT1.

[0083] For example, the control unit 31 serving as the evaluation information output unit may output a plurality of pieces of evaluation information based on a plurality of determination results each of which is the result of the determination made in step S102. For example, points are added each time good driving behavior is performed, thereby strengthening motivation to perform good driving behavior.

[0084] The driving evaluation routine RT1 may be executed not in real time, for example, after the host vehicle M1 has finished traveling, based on surrounding situation information and traveling information acquired in advance.

[0085] Fig. 6 is a diagram showing an example of criteria for driving evaluation in the driving evaluation device 10. The table shown in Fig. 6 is stored, for example, in the storage unit 29. The control unit 31 determines a score based on the evaluation criteria shown in Fig. 6, for example, in step S103 of the driving evaluation routine RT1 shown in Fig. 5.

[0086] As shown in Fig. 6, each recommended action in the recommended action information similar to that in Fig. 4 is associated with a degree of contribution that indicates what each recommended action contributes to road traffic. For example, as shown in Fig. 6, the degree of contribution is classified into multiple items, and a score is assigned to the item to which each recommended action applies.

[0087] When the control unit 31, which serves as an evaluation information output unit, determines that the driving behavior of the driver DR of the vehicle M1 corresponds to a recommended driving behavior, it outputs information indicating the score for each contribution item associated with the recommended behavior as evaluation information.

[0088] Specifically, in the example shown in Fig. 6, the degree of contribution is classified into the following categories: "kindness," which indicates a contribution to smooth communication through mutual concession and kindness; "improvement of traffic conditions," which indicates a contribution to improving traffic conditions; "own safety," which indicates a contribution to the safety of the driver of one's own vehicle; "other party's safety," which indicates a contribution to the safety of other pedestrians and drivers of other vehicles; and "third party's safety," which indicates a contribution to the safety of third parties other than the person who took an action such as concession. The number and content of the categories for the degree of contribution are not limited to these, and any number of items with any content can be provided.

[0089] As shown in Figure 6, for example, the recommended behavior in scene ST1, "stopping temporarily and waiting until pedestrians have finished crossing," is given a score of 1 in the "kindness" category because it contributes to mutual yielding and smooth communication with pedestrians. Also, a score of 1 is given in the "safety of others" category because it contributes to the safety of pedestrians.

[0090] In this case, the control unit 31 outputs, as the evaluation information, information indicating that the contribution item "kindness" is 1 point and the item "other person's safety" is 1 point. Note that, for example, only the total points set for the corresponding items may be output.

[0091] Furthermore, for the recommended behavior in scene ST1, "Flash your lights to warn oncoming vehicles when stopping," one point is assigned to "kindness," one point to "other vehicle's safety," and two points to "third party safety." In this way, different scores may be assigned depending on the content of the recommended driving behavior, the content of the contribution, etc. For example, a high score may be assigned to a driving behavior that requires a high level of attention or advanced driving skills. Note that the same score may be assigned to all items.

[0092] In this way, by using the evaluation criteria shown in Fig. 6 in the driving evaluation device 10 of this embodiment, evaluation information on the driving of the driver of the vehicle can be output by category, indicating what contribution the driver makes to road traffic. This allows the driver to specifically recognize, for example, in numerical form, how his or her actions contribute and what positive impact the driver has on the transportation society. For example, the evaluation results categorized in this way can be used for education, corporate recruitment activities, employee evaluation, setting automobile insurance premiums, or various other businesses.

[0093] FIG. 7 is a diagram schematically showing a learning model MD1 when the learning model is used in the driving evaluation device 10 to identify a scene (actual scene) that the driver DR of the vehicle M1 actually encountered.

[0094] The learning model MD1 shown in Figure 7 is a neural network constructed by deep learning. The neural network is composed of an input layer, two or more intermediate layers (hidden layers), and an output layer.

[0095] For example, the input layer of the learning model MD1 receives ENV1 to ENVX, which are pieces of information respectively indicating the information included in the surrounding situation information, and DV1 to DVX, which are pieces of information indicating the driving state information. For example, the information indicating the surrounding situation information may be a numerical value obtained by digitizing the image analysis results, or may be a measured value obtained by measuring the distance to an object using a distance measuring sensor. Furthermore, for example, the information indicating the driving state information may be a numerical value indicating the speed, acceleration, traveling direction, steering angle, etc. of the host vehicle M1.

[0096] When this input is made, the output layer outputs a numerical value indicating whether the scene related to the input information corresponds to any of the specific scenes ST1 to STX and ST0 stored in the recommended action DB. For example, ST0 indicates that the scene related to the input does not correspond to any of the specific scenes stored in the recommended action DB.

[0097] That is, the learning model MD1 is constructed to receive information about the surroundings and driving conditions of the vehicle M1 as input, and to output information indicating which of the specific scenes the situation corresponds to.

[0098] Therefore, when information indicating surrounding situation information and information indicating driving state information is input to the learning model MD1, information indicating which of the specific scenes it corresponds to is output.

[0099] The learning model MD1 is constructed, for example, by supervised learning as follows: A numerical value representing a specific scene ST1 is used as the correct answer data. Furthermore, a state in which a vehicle encounters the specific scene ST1 is reproduced, and an image of the surroundings of the vehicle and its driving state are acquired and used as input data.

[0100] The input data is input to a neural network with multiple hidden layers, and learning is performed by updating the neural network parameters using the backpropagation method so that the output becomes a numerical value that indicates the scene of the correct data. By performing this type of learning for other specific scenes (for example, ST2, ST3, etc. in Figure 4), a learning model MD1 can be constructed.

[0101] In this way, by using the learning model MD1 to identify scenes, it is possible to identify scenes efficiently. In addition, by constructing the learning model MD1 appropriately, it is also possible to identify scenes in detail.

[0102] The evaluation of driving behavior may be performed by AI. In this case, a learning model may be used that inputs a numerical value indicating a specific situation encountered and a numerical value indicating the driving operation or driving state performed in the specific situation encountered, and outputs a numerical value indicating the evaluation.

[0103] As described above in detail, the driving evaluation device 10 of this embodiment includes a surrounding situation acquisition unit that acquires surrounding situation information that indicates the surrounding situation, and a driving information acquisition unit that acquires information that indicates the driving state of the host vehicle. The driving evaluation device 10 also includes a behavior determination unit that determines whether the driving behavior performed by the driver of the host vehicle in a situation that the driver actually encountered corresponds to the recommended driving behavior, based on the surrounding situation information, the driving state information, and the recommended behavior information.

[0104] The recommended action information is information in which each of a plurality of road traffic situations is associated with a recommended driving action that is a driving action recommended to the driver of the vehicle for each of the situations. The recommended driving action is a driving action that is not indicated by road signs, road markings, or traffic lights.

[0105] The driving evaluation device 10 also has an evaluation information output unit that outputs evaluation information that contributes to evaluating the driving of the driver of the subject vehicle, based on the determination by the behavior determination unit.

[0106] With the above-described configuration, when the driver of the vehicle encounters a specific scene, the driving evaluation device 10 can evaluate whether the driving behavior performed by the driver in that scene was a recommended behavior in that scene.

[0107] According to the driving evaluation device 10, when the driver of the vehicle performs driving behavior with good manners, a good evaluation can be given.

[0108] Therefore, according to the driving evaluation device of this embodiment, it is possible to provide an evaluation for driving behavior that shows good manners, and this evaluation encourages drivers to be considerate of others and to give way to others, thereby contributing to the realization of a better transportation society.

[0109] Furthermore, by presenting the evaluation information to the driver as a score or the like, the driver can recognize his or her own good driving behavior, which will motivate the driver to take the recommended driving behavior the next time the driver encounters a similar situation.

[0110] Furthermore, by presenting multiple pieces of evaluation information and adding up points, for example, the motivation to perform the recommended driving behavior is strengthened.

[0111] In the above embodiment, an example in which the surrounding situation information is acquired from the camera 11 has been described, but the present invention is not limited to this. For example, the host vehicle M1 may be equipped with one or more sensors, such as a LiDAR (Light Detection and Ranging), a millimeter-wave radar, or a SONAR (Sound Navigation and Ranging), in addition to the camera 11. The control unit 31 may use the sensor to detect the distance between the host vehicle M1 and pedestrians or other vehicles around the host vehicle M1, the presence or absence of obstacles, and so on, and acquire this as surrounding situation information. Furthermore, the actual scene and actual driving behavior may be identified by combining and analyzing the data acquired from the sensor with the video from the camera 11.

[0112] In the above-described embodiment, the driving evaluation device 10 is described as a device attached to the host vehicle M1, but is not limited to this. The driving evaluation device of the present invention may be a portable device such as a smartphone or tablet carried by the user. In this case, the portable device serving as the driving evaluation device of the present invention may be communicatively connected via wireless or wired communication to at least some of the camera 11, steering sensor 13S, accelerator sensor 15S, brake sensor 17S, GPS receiver 19, gyro sensor GY, and acceleration sensor AC mounted on the host vehicle M1.

[0113] Alternatively, the driving evaluation device of the present invention may be a server device installed outside the host vehicle M1. In this case, the server device as the driving evaluation device of the present invention may be configured to receive, via a wireless network, information acquired by at least some of the camera 11, steering sensor 13S, accelerator sensor 15S, brake sensor 17S, GPS receiver 19, gyro sensor GY, and acceleration sensor AC mounted on the host vehicle M1, and may perform driving evaluation of the driver DR of the host vehicle M1 based on the received information.

[0114] The configurations in the above-described embodiments are merely examples, and can be appropriately selected and changed depending on the application, etc. [Explanation of symbols]

[0115] 10 Driving evaluation device 11 Camera 13. Steering wheel 13S Steering Sensor 15 Accelerator pedal 15S accelerator sensor 17 Brake pedal 17S Brake Sensor 19 GPS receiver 21 Touch panel display 23 speakers 25 System Bus 27 Input section 29 Memory section 29A Recommended Action DB 31 Control Unit 33 Output section

Claims

1. an acquisition unit that acquires driving behavior information indicating driving behaviors performed by a driver of a vehicle in a specific situation related to road traffic; a behavior determination unit that determines, based on the driving behavior information, whether the driving behavior performed by the driver in the specific scene corresponds to a recommended driving behavior that is a driving behavior that is not instructed by a road sign, road marking, or traffic light and is recommended to the driver of the vehicle in the specific scene; an evaluation information output unit that outputs evaluation information that contributes to an evaluation of the driving of the driver of the vehicle based on the determination by the behavior determination unit, The recommended driving behavior is associated with at least one of a plurality of categories that classify contributions that the recommended driving behavior makes to road traffic; The driving evaluation device is characterized in that the evaluation information output unit outputs the evaluation information for each of the items.

2. The driving evaluation device according to claim 1, characterized in that the behavior determination unit determines whether the driving behavior performed by the driver in a scene actually encountered by the vehicle corresponds to the recommended driving behavior based on recommended behavior information in which each of the multiple specific scenes is associated with the recommended driving behavior for that scene and the driving behavior information.

3. The driving evaluation device according to claim 2, characterized in that the evaluation information output unit outputs the evaluation information that affirms the driving behavior of the driver when the behavior determination unit determines that the driving behavior performed by the driver corresponds to the recommended driving behavior.

4. the driving behavior information includes surrounding situation information indicating a situation around the vehicle, and driving information indicating information related to a driving state of the vehicle or an operation state of the vehicle, The driving evaluation device according to claim 2 or 3, characterized in that the behavior determination unit identifies a scene that the vehicle actually encountered based on the surrounding situation information and the driving information, and determines whether a recommended driving behavior associated with the identified scene corresponds to the driving behavior performed by the driver in the scene that the vehicle actually encountered.

5. 5. The driving evaluation device according to claim 1, wherein the evaluation information output unit outputs the evaluation information as an evaluation result that can be presented to a driver of the vehicle.

6. A driving evaluation method performed by a driving evaluation device, an acquisition step of acquiring driving behavior information indicating driving behaviors performed by a driver of the vehicle in a specific situation related to road traffic; a behavior determination step of determining, based on the driving behavior information, whether the driving behavior performed by the driver in the specific scene corresponds to a recommended driving behavior that is a driving behavior that is not indicated by a road sign, road marking, or traffic light and is recommended to the driver of the vehicle in the specific scene; an evaluation information output step of outputting evaluation information that contributes to an evaluation of the driving of the driver of the vehicle based on the determination made by the behavior determination step, In the behavior determination step, the recommended driving behavior is associated with at least one of a plurality of items that classify contributions that the recommended driving behavior makes to road traffic; The driving evaluation method is characterized in that the evaluation information output step outputs the evaluation information for each of the items.

7. A driving evaluation program executed by a driving evaluation device including a computer, the computer comprising: an acquisition step of acquiring driving behavior information indicating driving behaviors performed by a driver of the vehicle in a specific situation related to road traffic; a behavior determination step of determining, based on the driving behavior information, whether the driving behavior performed by the driver in the specific scene corresponds to a recommended driving behavior that is a driving behavior that is not indicated by a road sign, road marking, or traffic light and is recommended to the driver of the vehicle in the specific scene; an evaluation information output step of outputting evaluation information that contributes to evaluating the driving of the driver of the vehicle based on the determination made in the behavior determination step; Execute In the behavior determination step, the recommended driving behavior is associated with at least one of a plurality of items that classify contributions that the recommended driving behavior makes to road traffic; The driving evaluation program is characterized in that the evaluation information output step outputs the evaluation information for each of the items.

8. A computer-readable recording medium storing the driving evaluation program according to claim 7.

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