Driving assistance device and computer program

Abstract

To provide a drive assistance device and a computer program which can set driving conditions for a vehicle considering a risk of damage corresponding to the intension of individual drivers from risks of damages which can arise from collision of a vehicle with an obstacle around the vehicle.SOLUTION: A drive assistance device that sets driving conditions for a vehicle on the basis of risk of collision with an obstacle around the vehicle, acquires setting information for at least one damage risk selected from options of damage risks that arise due to collision of a vehicle with an obstacle around the vehicle, detects an obstacle around the vehicle, and sets a target track of the vehicle on the basis of a collision risk of the vehicle with the detected obstacle and at least one damage risk that has been selected.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The present disclosure relates to a driving assistance device and a computer program that assists vehicle driving based on a collision risk with an obstacle around the vehicle. [Background technology]

[0002] In recent years, vehicles equipped with driving assistance functions and autonomous driving functions have been put into practical use, primarily for the purpose of reducing traffic accidents and reducing the burden on drivers. For example, there is known a device that detects obstacles around the vehicle based on information detected by various sensors, such as an exterior camera and LiDAR (Light Detection and Ranging), installed in the vehicle, and assists the driving of the vehicle to avoid collisions between the vehicle and the obstacles.

[0003] Furthermore, Patent Document 1 proposes a vehicle control device that controls a host vehicle to minimize damage in a situation where a collision between the host vehicle and an obstacle cannot be avoided. Specifically, Patent Document 1 discloses a vehicle control device that detects an obstacle with which the host vehicle may collide, determines whether a collision with the obstacle can be avoided by controlling the progress of the host vehicle, and, if it is determined that a collision between the host vehicle and the obstacle cannot be avoided, identifies a range of the obstacle that may collide with the host vehicle, identifies a portion of the obstacle that will cause the least damage if the host vehicle collides with the obstacle, and controls the progress of the host vehicle so that deformation reaches the identified portion. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-232693 Summary of the Invention [Problem to be solved by the invention]

[0005] However, there are various types of damage that can occur when a vehicle collides with a surrounding obstacle. For example, while it goes without saying that minimizing damage to the occupants of the other vehicle that is the target of collision is a high priority, when there are multiple types of potential damage, it is not possible to determine which type of damage should be minimized. The vehicle control device in Patent Document 1 controls the travel of the vehicle with only consideration given to minimizing damage to the occupants of the vehicle that may be collided with, and does not consider the risk of other damage.

[0006] 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 device and a computer program that can set vehicle driving conditions taking into account the risk of damage that may occur due to a collision between the vehicle and surrounding obstacles, in accordance with the intentions of each individual driver. [Means for solving the problem]

[0007] In order to solve the above problem, according to one aspect of the present disclosure, there is provided a driving assistance device that sets driving conditions of a vehicle based on a collision risk with an obstacle around the vehicle, the driving assistance device including one or more processors and one or more memories communicatively connected to the one or more processors, wherein the processor performs processing including acquiring setting information for at least one damage risk selected from options for damage risks that may occur due to a collision between the vehicle and an obstacle around the vehicle, detecting obstacles around the vehicle, and setting a target trajectory of the vehicle based on the collision risk of the vehicle with the detected obstacle and the at least one selected damage risk.

[0008] In addition, in order to solve the above problem, according to another aspect of the present disclosure, there is provided a computer program applicable to a driving assistance device that sets driving conditions for a vehicle based on a collision risk with an obstacle around the vehicle, the computer program causing one or more processors to execute processing including: acquiring setting information for at least one damage risk selected from options for damage risks that may arise from a collision between the vehicle and an obstacle around the vehicle; detecting obstacles around the vehicle; and setting a target trajectory for the vehicle based on the collision risk of the vehicle with the detected obstacle and the at least one selected damage risk. [Effects of the Invention]

[0009] As described above, according to the present disclosure, the driving conditions of a vehicle can be set taking into account the risk of damage that may occur due to a collision between the vehicle and surrounding obstacles, in accordance with the intentions of each individual driver. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram illustrating a configuration example of a vehicle equipped with a driving assistance device according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a block diagram showing a configuration example of a driving assistance device according to the embodiment; [Figure 3] FIG. 10 is an explanatory diagram showing data of injury risk values ​​that indicate the risk of bodily injury to the other vehicle in a collision; [Figure 4] FIG. 10 is an explanatory diagram showing data of a damage risk value that indicates the risk of bodily injury on the side of the vehicle itself. [Figure 5] FIG. 2 is an explanatory diagram showing a collision position relative to a forward vehicle. [Figure 6] FIG. 10 is an explanatory diagram showing an example of an obstacle risk potential. [Figure 7] FIG. 10 is an explanatory diagram showing a modified example of an obstacle risk potential. [Figure 8] FIG. 10 is an explanatory diagram showing an example of setting a damage risk value assuming the rate of death or injury to the other party in a collision; [Figure 9]FIG. 10 is an explanatory diagram showing an example of setting a damage risk value assuming a casualty rate on the side of the vehicle itself; [Figure 10] FIG. 10 is an explanatory diagram showing an example of setting a damage risk value that assumes the amount of damage, legal liability, and compensation that the driver of the vehicle will suffer. [Figure 11] 4 is a flowchart illustrating an example of processing performed by the driving assistance device according to the embodiment. [Figure 12] 10 is a flowchart illustrating an example of a damage risk value setting process performed by the driving assistance device according to the embodiment. [Figure 13] FIG. 10 is an explanatory diagram showing a traffic situation in a first application example. [Figure 14] FIG. 10 is an explanatory diagram showing a target trajectory according to a first application example. [Figure 15] FIG. 10 is an explanatory diagram showing a traffic situation in a second application example. [Figure 16] FIG. 10 is an explanatory diagram showing a collision position in the second application example. DETAILED DESCRIPTION OF THE INVENTION

[0011] 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.

[0012] <1. Overall vehicle configuration> Fig. 1 is a schematic diagram showing an example of the configuration of a vehicle 1 equipped with a driving assistance device 50 according to this embodiment. The vehicle 1 shown in Fig. 1 is configured as a four-wheel drive vehicle in which drive torque output from a drive force source 9 that generates drive torque for the vehicle 1 is transmitted to a left front wheel 3LF, a right front wheel 3RF, a left rear wheel 3LR, and a right rear wheel 3RR (hereinafter collectively referred to as "wheels 3" unless a distinction is required). The drive force source 9 may be an internal combustion engine such as a gasoline engine or a diesel engine, a drive motor, or both an internal combustion engine and a drive motor.

[0013] The vehicle 1 may 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 each of the wheels 3. If the vehicle 1 is an electric vehicle or a hybrid electric vehicle, the vehicle 1 is equipped with a secondary battery that stores power to be supplied to the drive motors, and a motor or a generator such as a fuel cell that generates power to charge the battery.

[0014] The vehicle 1 is equipped with a driving force source 9, an electric steering device 15, and a brake fluid pressure control unit 20 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 drive shaft 5F and the rear drive shaft 5R via a transmission, a front wheel differential mechanism 7F, and a rear wheel differential mechanism 7R (not shown). The operation of the driving force source 9 and the transmission is controlled by a vehicle control device 41 that includes one or more electronic control units (ECUs: Electronic Control Units).

[0015] 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 device 41 to adjust the steering angles of the left front wheel 3LF and the right front wheel 3RF. During manual driving, the vehicle control device 41 controls the electric steering device 15 based on the steering angle of the steering wheel 13 by the driver. During automatic driving, the vehicle control device 41 controls the electric steering device 15 based on a target steering angle set by the driving assistance device 50.

[0016] The brake system of the vehicle 1 is configured as a hydraulic brake system. A brake fluid pressure control unit 20 adjusts the hydraulic pressure supplied to brake calipers 17LF, 17RF, 17LR, and 17RR (hereinafter collectively referred to as "brake calipers 17" unless a distinction is required) provided on the front, rear, left, and right drive wheels 3LF, 3RF, 3LR, and 3RR, respectively, to generate braking force. The operation of the brake fluid pressure control unit 20 is controlled by a vehicle control device 41. If the vehicle 1 is an electric vehicle or a hybrid electric vehicle, the brake fluid pressure control unit 20 is used in conjunction with regenerative braking using the drive motor.

[0017] The vehicle control device 41 includes one or more electronic control devices that control the drive of the driving force source 9 that outputs the driving torque of the vehicle 1, the electric steering device 15 that controls the steering wheel 13 or the steering angle of the steering wheels, and the brake fluid pressure control unit 20 that controls the braking force of the vehicle 1. The vehicle control device 41 may also have a function of controlling the drive of a transmission that changes the speed of the output output from the driving force source 9 and transmits it to the wheels 3. The vehicle control device 41 is configured to be able to acquire information transmitted from the driving assistance device 50, and is configured to be able to execute automatic driving control of the vehicle 1. Furthermore, when the vehicle 1 is being manually driven, the vehicle control device 41 acquires information on the amount of operation by the driver, and controls the drive of the driving force source 9 that outputs the driving torque of the vehicle 1, the electric steering device 15 that controls the steering wheel 13 or the steering angle of the steering wheels, and the brake fluid pressure control unit 20 that controls the braking force of the vehicle 1.

[0018] The vehicle 1 also includes front-facing cameras 31LF and 31RF, a LiDAR (Light Detection And Ranging) 31S, a vehicle state sensor 35, an output device 43, and an HMI (Human Machine Interface) 45.

[0019] The front photographing cameras 31LF, 31RF and the LiDAR 31S constitute a surrounding environment sensor for acquiring information about the surrounding environment of the vehicle 1. The front photographing cameras 31LF, 31RF photograph the area in front of the vehicle 1 and generate image data. The front photographing cameras 31LF, 31RF are equipped with imaging elements such as CCDs (Charged-Coupled Devices) or CMOSs ​​(Complementary Metal-Oxide-Semiconductors), and transmit the generated image data to the driving assistance device 50.

[0020] 1, the front imaging cameras 31LF, 31RF are configured as stereo cameras including a pair of left and right cameras, but they may also be monocular cameras. In addition to the front imaging cameras 31LF, 31RF, the vehicle 1 may also be equipped with, for example, a rear imaging camera 31R provided at the rear of the vehicle 1 to capture images of the rear, or cameras provided on the side mirrors 11L, 11R to capture images of the left rear or right rear.

[0021] The LiDAR 31S transmits optical waves and receives reflected waves of the optical waves, and detects obstacles, the distance to the obstacles, and the positions of the obstacles based on the time between transmitting the optical waves and receiving the reflected waves. The LiDAR 31S transmits the detection data to the driving assistance device 50. The vehicle 1 may be equipped with one or more sensors, instead of or in addition to the LiDAR 31S, of a radar sensor such as a millimeter-wave radar and an ultrasonic sensor as a surrounding environment sensor for acquiring information about the surrounding environment.

[0022] The vehicle state sensor 35 is composed of one or more sensors that detect the operation state and behavior of the vehicle 1. The vehicle state sensor 35 includes at least one of a steering angle sensor, an accelerator position sensor, a brake stroke sensor, a brake pressure sensor, and an engine rotation speed sensor, and detects the operation state of the vehicle 1, such as the steering angle of the steering wheel 13 or the steering wheels, the accelerator opening, the brake operation amount, and the engine rotation speed. The vehicle state sensor 35 also includes at least one of a vehicle speed sensor, an acceleration sensor, and an angular velocity sensor, and detects the behavior of the vehicle, such as the vehicle speed, longitudinal acceleration, lateral acceleration, and yaw rate. The vehicle state sensor 35 also includes a sensor that detects the operation of a turn signal, and detects the operation state of the turn signal. The vehicle state sensor 35 transmits a sensor signal including the detected information to the driving assistance device 50.

[0023] The output device 43 is driven by the driving assistance device 50 and presents various information to the driver by means of image display, audio output, etc. The output device 43 includes, for example, a display device provided in the instrument panel and a speaker provided in the vehicle. The display device may have the function of a display device of a navigation system. The output device 43 may also include a head-up display that displays an image on the front window of the vehicle 1.

[0024] The HMI 45 functions as an input unit for a user such as a driver to perform operational input. In this embodiment, the HMI 45 is used for operational input to select at least the type of damage risk described below. The HMI 45 includes, for example, one or more devices selected from a touch panel display, a voice input device, a dial switch, and a button switch. The operational input via the HMI 45 is transmitted to the driving assistance device 50.

[0025] <2. Driving assistance devices> Next, the driving assistance device 50 according to this embodiment will be described in detail. In the following description, the vehicle to be assisted is referred to as the host vehicle, and vehicles around the host vehicle 1 are referred to as other vehicles. In addition, in a collision scene, the vehicle that collides may be referred to as the host vehicle, and the vehicle that is collided with may be referred to as the other vehicle.

[0026] (2-1. Configuration example) FIG. 2 is a block diagram showing an example of the configuration of the driving assistance device 50 according to this embodiment. The driving assistance device 50 is connected to an ambient environment sensor 31 and a vehicle state sensor 35 via a dedicated line or communication means such as a CAN (Controller Area Network) or a LIN (Local Inter Net). The driving assistance device 50 is also connected to a vehicle control device 41 and an output device 43 via a dedicated line or communication means such as a CAN or a LIN. The driving assistance device 50 is not limited to an electronic control device mounted on the vehicle 1, and may be a terminal device such as a smartphone or a wearable device.

[0027] The driving assistance device 50 functions as a device that assists in driving the vehicle 1 by having one or more processors, such as CPUs (Central Processing Units), 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 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) 53 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.

[0028] Recording media for recording computer programs include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs (Compact Disk Read Only Memory), DVDs (Digital Versatile Disks), and Blu-ray (registered trademark), magneto-optical media such as floptical disks, memory elements such as RAMs (Random Access Memory) and ROMs (Read Only Memory), flash memories such as USB (Universal Serial Bus) memories and SSDs (Solid State Drives), and other media capable of storing programs.

[0029] The driving assistance device 50 includes a processing unit 51, a memory unit 53, and a damage database 55. The processing unit 51 is configured with one or more processors such as CPUs (Central Processing Units). Part or all of the processing unit 51 may be configured with updatable firmware or the like, or may be a program module or the like executed by commands from the CPU or the like. The memory unit 53 is configured with memory such as RAM (Random Access Memory) or ROM (Read Only Memory). However, the number and type of memory units 53 are not particularly limited. The memory unit 53 stores information such as computer programs executed by the processing unit 51, various parameters used in arithmetic processing, detection data, and arithmetic results.

[0030] The damage database 55 is configured by a memory such as RAM, or an updatable recording medium such as a hard disk drive (HDD), a compact disk (CD), a digital versatile disk (DVD), a solid state drive (SSD), a USB flash drive, or a storage device. However, the type of recording medium is not particularly limited. A part or all of the damage database 55 may be mounted on the vehicle 1, or may be stored on a server that can communicate with the driving assistance device 50 via wireless communication means such as mobile communication.

[0031] The damage database 55 is a database that stores data on damage situations when collision accidents have occurred in the past between a vehicle and an obstacle around the vehicle. The data on damage situations stored in the damage database 55 is not limited to data on damage situations when a specific vehicle collided, but also includes data on damage situations when various vehicles collided. The damage database 55 stores information on damages caused to the vehicle and the other vehicle in each accident, in association with at least information on the vehicle and the vehicle's surrounding environment at the time of the accident, and information on the collision location at the time of each accident.

[0032] The information on the damage caused to the host vehicle includes, for example, information on the fatality rate or the degree of injury (risk of personal injury) of the occupants of the host vehicle. The information on the damage caused to the other party in the collision includes information on the fatality rate or the degree of injury (risk of personal injury) of the occupants or pedestrians of the other party in the collision. In this embodiment, the information on the fatality rate or the degree of injury is converted into a numerical value in the range of "0" to "1" that indicates a damage risk value according to a preset standard and stored. The closer the damage risk value is to "1", the greater the degree of damage. In this embodiment, the obstacle risk potential set for each obstacle is expressed as a numerical value in the range of "0" to "1", as will be described later, so the damage risk value to be added is expressed as a numerical value in the range of "0" to "1", but the damage risk value is not limited to this range.

[0033] 3 and 4 show an example of damage situation data stored in the damage database 55. The damage situation data shown in Fig. 3 and 4 is damage risk value data that respectively represent the fatality and injury rates of occupants of the other vehicle and the occupants of the own vehicle when an accident occurs in which the own vehicle rear-ends a vehicle ahead. This damage situation data represents the fatality and injury rates of occupants when the own vehicle rear-ends a vehicle ahead in a rear-end collision accident that occurred in a situation in which only occupants were in the driver's seat of each of the own vehicle and the front vehicle, and divides the collision position with respect to the front vehicle Ve into rear left A, rear center B, and rear right C, as shown in Fig. 5, and represents the fatality and injury rates of occupants when the own vehicle rear-ends a vehicle ahead in each collision position for each speed (collision speed) of the own vehicle at the time of the collision.

[0034] In the examples shown in Figures 3 and 4, the faster the rear-end collision speed is on the host vehicle side and the front vehicle side, the higher the fatality and injury rate is, but the fatality and injury rate differs depending on the collision position. Specifically, for the front vehicle, the fatality and injury rate is relatively highest when the collision position is on the rear right side, and relatively lowest when the collision position is on the rear left side. Also, for the host vehicle, the fatality and injury rate is relatively highest when the collision position is on the rear center, followed by the relatively high fatality and injury rate when the collision position is on the rear left side, and relatively lowest when the collision position is on the rear right side.

[0035] The damage situation data stored in the damage database 55 may be stored in association with not only the collision speed but also data on traffic conditions at the time of the accident, such as the relative speed between the host vehicle and the other vehicle, the types (weights) of the host vehicle and the other vehicle, and road surface conditions. Specifically, the damage situation data may be associated with at least one of the following information about the other vehicle, such as the type of obstacle in the other vehicle, the relative speed, relative position, and relative traveling direction of the other vehicle relative to the host vehicle 1, and, if the other vehicle is another vehicle, the model of the other vehicle and the positions of the occupants. Furthermore, the damage situation data may be associated with at least one of the following information about the host vehicle 1, such as the speed, traveling position, occupant positions, and model of the host vehicle 1. The more associated data there is, the more detailed the damage risk value can be calculated for each collision accident.

[0036] The information on the damage caused to the vehicle may include information on the amount of damage (risk of compensatory damage) suffered by the driver of the vehicle due to the accident. The information on the damage caused to the vehicle may also include information on the legal liability (risk of punitive damage) and amount of compensation (risk of compensatory damage) imposed on the driver of the vehicle due to the accident. The information on the amount of damage, legal liability, and amount of compensation is also converted into a numerical value within the range of "0" to "1" that indicates a damage risk value according to a preset standard and stored.

[0037] (2-2. Setting of driving conditions based on risk potential) Before describing the specific processing of the driving support device 50, a brief outline of the processing for setting driving conditions based on the risk potential executed by the driving support device 50 will be given.

[0038] 6 and 7 are explanatory diagrams showing the risk potential (obstacle risk potential) set for each obstacle. Fig. 6 and Fig. 7 show examples of obstacle risk potentials set for a vehicle. The value of the obstacle risk potential (risk value) R i The risk value R is maximum in the area where the obstacle (other vehicle) overlaps with the vehicle's position, and decreases as the vehicle moves away from the outer edge of the obstacle (other vehicle). i is the distance l from the obstacle i It can be expressed as an exponential function of , for example, as shown in the following formula (1).

[0039]

number

[0040] R i :Risk value C i : Risk absolute value (gain) l i :Distance from obstacles σ i :Slope coefficient r i : Obstacle radius i: Numbering to distinguish obstacles

[0041] Risk score R i is defined within the range of "0" to "1", and the distance to the obstacle l i The absolute risk value C is the risk value when i is set to "1" and the area is deemed untravelable. However, the absolute risk value C i may be set for each obstacle as a value that depends on the obstacle. For example, if the obstacle is a "vehicle" or a "low curb", the risk absolute value C for the "vehicle" is set as follows, assuming that the risk of collision with a vehicle is higher than the risk of collision with a low curb. iis the absolute risk value C for "low curb" i Alternatively, the absolute risk value C may be set to a value larger than the value σ for each obstacle type, reflecting the risk sensitivity that each driver feels to the obstacle. i may be set.

[0042] Gradient coefficient σ i is a value that is set depending on the type of obstacle. i is set according to, for example, a Gaussian function or an exponential function. When the obstacle is a moving object such as another vehicle traveling around the host vehicle, the risk in the direction of travel of the other vehicle is high, so the depth of the risk ahead of the other vehicle may be set wider than the risk behind it, as shown in Fig. 7. In this case, the depth of the risk ahead may be variable depending on the vehicle speed of the other vehicle or its relative vehicle speed with respect to the host vehicle.

[0043] When setting the target trajectory and acceleration / deceleration of the host vehicle 1 using the obstacle risk potential, an obstacle risk potential is set for each obstacle detected while the host vehicle 1 is traveling, and a basic risk map (potential field) representing the risk of collision with multiple obstacles is obtained by adding up the spatial overlap of each obstacle risk potential. In this case, the maximum risk value among the risk values ​​of the obstacle risk potentials described above may be used as the risk value of the basic risk map at that point. In such a basic risk map, the level of risk is shown as contour lines on a two-dimensional plane. Because the risk values ​​have a two-dimensional distribution, it is possible to select a trajectory that reduces risk.

[0044] The basic risk map may be calculated taking into account not only visible obstacles but also hidden risks (latent risks). For example, when a vehicle turns and passes through a blind spot caused by an obstruction, a potential risk may be added assuming that a pedestrian or another vehicle may suddenly appear from the blind spot, and this risk may be reflected in the basic risk map.

[0045] The driving assistance device 50 according to this embodiment generates a basic risk map based on the obstacle risk potential, and if it is determined that a collision between the vehicle 1 and an obstacle cannot be avoided, generates a damage risk map by adding a damage risk value corresponding to the expected damage to the obstacle risk potential. The damage risk value is calculated based on the obstacle risk potential R i The absolute risk value C set in the range of the obstacle i The greater the expected damage, the larger the value is set. i By adding the damage risk value to the above, the possibility of a collision at a collision position where damage will be greater can be reduced.

[0046] The driving support device 50 according to this embodiment is configured to be able to select which damage to reduce, and adds a damage risk value that is set reflecting the priority of at least one damage risk selected by a user such as a driver to the obstacle risk potential. In this way, the driving conditions of the host vehicle 1 are set so that, of various possible damages, damage that corresponds to the driver's intention is reduced.

[0047] (2-3. Functional configuration) 2, the processing unit 51 of the driving assistance device 50 includes a surrounding environment detection unit 61, a driving state detection unit 63, a risk map generation unit 65, a collision determination unit 67, a damage risk setting unit 69, and a driving condition setting unit 71. Each of these units has a function realized by the execution of a computer program by a processor such as a CPU. Below, the function of each unit of the processing unit 51 will be briefly described, followed by a description of the specific processing operation.

[0048] (Ambient environment detection section) The surrounding environment detection unit 61 detects the surrounding environment of the host vehicle 1 based on the detection data transmitted from the surrounding environment sensor 31. Specifically, the surrounding environment detection unit 61 calculates the type, size (width, height, and depth), and position of obstacles present around the host vehicle 1, the distance from the host vehicle 1 to the obstacles, and the relative speed between the host vehicle 1 and the obstacles. The detected obstacles include other moving vehicles, parked vehicles, pedestrians, bicycles, side walls, curbs, buildings, utility poles, traffic signs, traffic signals, natural objects, and any other objects present around the host vehicle 1. The surrounding environment detection unit 61 may also have a lane recognition function, such as detecting boundary lines on the road.

[0049] (Driving condition detection unit) The driving state detection unit 63 detects information about the operation state and behavior of the vehicle 1 based on the detection data transmitted from the vehicle state sensor 35. The driving state detection unit 63 acquires information about the operation state of the vehicle 1, such as the steering angle of the steering wheel or steering wheels, accelerator opening, brake operation amount, or engine rotation speed, and information about the behavior of the vehicle 1, such as vehicle speed, longitudinal acceleration, lateral acceleration, and yaw rate, at predetermined calculation intervals, and stores this information in the memory unit 53.

[0050] (Risk map generation section) During autonomous driving of the host vehicle 1, the risk map generation unit 65 sets an obstacle risk potential for each obstacle detected by the surrounding environment detection unit 61, and generates a basic risk map by superimposing all of the obstacle risk potentials. Furthermore, when the collision determination unit 67 determines that a collision between the host vehicle 1 and any of the obstacles cannot be avoided, the risk map generation unit 65 generates a damage risk map by adding the damage risk value calculated by the damage risk setting unit 69 to each obstacle risk potential.

[0051] (Collision determination section) The collision determination unit 67 determines whether the host vehicle 1 will collide with any obstacle. In other words, the collision determination unit 67 determines whether the host vehicle 1 is in a situation where a collision between the host vehicle 1 and any obstacle can be avoided, even if the host vehicle 1 is decelerated or the target trajectory of the host vehicle 1 is changed. For example, the collision determination unit 67 determines whether a collision between the host vehicle 1 and an obstacle can be avoided based on information about the basic risk map generated by the risk map generation unit 65 and information about the operation state and behavior of the host vehicle 1 detected by the driving state detection unit 63. Alternatively, the collision determination unit 67 may determine whether a collision between the host vehicle 1 and an obstacle can be avoided by a conventional determination process based on the distance to the obstacle present ahead in the traveling direction of the host vehicle 1, the relative speed, and the operation state and behavior of the host vehicle 1, without using information about the basic risk map.

[0052] (Damage Risk Setting Department) The damage risk setting unit 69 sets a damage risk value to be added to the obstacle risk potential based on information about the surrounding environment of the host vehicle 1 detected by the surrounding environment detection unit 61 and information about the operation state and behavior of the host vehicle 1 detected by the driving state detection unit 63. In this embodiment, based on data on past damage situations stored in the damage database 55, a damage risk value R is set in accordance with the driver's intention based on at least the damage expected to the other party in a collision and the damage expected to the host vehicle. v The device is configured to be able to set the following.

[0053] Specifically, the damage database 55 stores a damage risk value that estimates damage to the other party in a collision and a damage risk value that estimates damage to the own vehicle, in association with the traffic conditions at the time of the collision accident. The damage risk setting unit 69 calculates the damage risk value R by referring to the data on accidents under the same traffic conditions stored in the damage database 55, based on the information on the other party in a collision under the current driving environment of the own vehicle 1 and the information on the own vehicle 1. vThe information on the other vehicle includes, for example, at least one of the following: the type of obstacle that the other vehicle collided with, the relative speed, relative position, and relative traveling direction of the other vehicle with respect to the host vehicle 1, and, if the other vehicle is the other vehicle, information on the model of the other vehicle and the position of the occupants. Also, the information on the host vehicle 1 includes, for example, at least one of the following information on the speed, traveling position, position of the occupants, and model of the host vehicle 1.

[0054] Further, the damage risk setting unit 69 calculates the obstacle risk potential R that is set according to the type of each obstacle based on the type of damage risk previously selected by a user such as a driver. i Damage risk value R v The type of damage risk refers to the expected target or content of damage, such as the rate of death or injury to the other party in a collision, the rate of death or injury to the driver of the vehicle, the amount of damage suffered by the driver of the vehicle, and the legal responsibility and compensation amount imposed on the driver of the vehicle. The occupant operates the HMI 45, for example, to select the type of damage risk that they wish to prioritize reducing.

[0055] In this embodiment, the user can select the risk of damage that he or she wishes to reduce from the risk of punitive damage to the driver of the vehicle 1, the risk of compensatory damage to the driver of the vehicle 1, the risk of personal injury to the other party in a collision, and the risk of personal injury to the vehicle 1. This allows the user to select the desired risk of damage according to his or her wishes from among the important risks of damage that may occur due to an accident.

[0056] Any one of a plurality of types of damage risk may be selectable, or two or more types of damage risk may be selectable. When two or more types of damage risk are selectable, weighting of each type of damage risk may be settable. The damage risk setting unit 69 selects the damage situation data to be used in calculating the damage risk value based on the selected type of damage risk, or sets the proportion to be reflected in the damage risk value.

[0057] 8 to 10, the damage risk value R v The example damage risk value R v is a damage risk value Rv set in the same traffic situation, and is set within the range of "0" to "1" based on the data of the damage situation stored in the damage database 55.

[0058] Figure 8 shows the damage risk value R v Fig. 8 shows an example of the damage risk value R set for each of the utility pole P, the pedestrian W, and the forward vehicle Ve. v Since utility pole P is not a person, the damage risk value R v is set to zero. In addition, since the fatality rate or the degree of injury is higher when the collision partner is a pedestrian W than when the collision partner is a forward vehicle Ve, the damage risk value R v is the damage risk value R set for the forward vehicle Ve. v The damage risk value R set for the forward vehicle Ve is set to a value greater than the damage risk value R (1.0 in the example of FIG. 8). v is gradient so that the risk value set for the seating position of an occupant of the forward vehicle Ve is greater than the risk value set for a position where no occupant is present. In the example shown in Figure 8, since there is an occupant only in the driver's seat, the risk value for the driver's seat side is set to the maximum value (0.6 in the example of Figure 8), and the damage risk value R v is sloped.

[0059] Figure 9 shows the damage risk value R v 9 shows an example of setting the damage risk value R set for the utility pole P. It is considered that the fatality rate due to a collision of the vehicle 1 increases as the impact force at the time of collision increases. v is set to the relatively largest value (0.7 in the example of FIG. 9), and the damage risk value R v is set to a large value (0.6 in the example in Figure 9), and the injury risk value R assigned to pedestrian W is vis set to the smallest value (0.2 in the example of FIG. 9). In addition, since the fatality and injury rate of the occupants of the host vehicle 1 differs depending on the collision position relative to the front vehicle Ve, the damage risk value R v is graded depending on the collision position. In the example shown in Fig. 9, the risk value at the rear center is set to the maximum value (0.6 in the example of Fig. 9) and the risk value at the rear right side is set to the minimum value, and the damage risk value R v is sloped.

[0060] Figure 10 shows the damage risk value R v 10 shows an example of setting a damage risk value R for pedestrian W. Colliding with utility pole P will result in at least damage to vehicle 1 and compensation for the restoration of utility pole P. Colliding with pedestrian W will result in at least damage to vehicle 1, legal liability for violation of traffic laws, and liability for compensation to pedestrian W, etc. Colliding with leading vehicle Ve will result in at least damage to vehicle 1, legal liability for violation of traffic laws, and liability for compensation to occupants of leading vehicle Ve, etc. In the example shown in FIG. 10, the damage risk value R is set for pedestrian W based on data on damage situations in the past under the same traffic conditions stored in damage database 55. v is set to the relatively largest value (1.0 in the example of FIG. 10), and the damage risk value R v is set to a large value (0.8 in the example in Figure 10), and the damage risk value R set for utility pole P is v is set to the smallest value (0.3 in the example of FIG. 10). In addition, since the degree of damage varies depending on the collision position relative to the forward vehicle Ve, the damage risk value R v is graded depending on the collision position. In the example shown in Fig. 10, the risk value on the driver's seat side is set to the maximum value (0.8 in the example of Fig. 10), and the damage risk value R v is sloped.

[0061] The damage risk setting unit 69 calculates a damage risk value R of any of the damage risk types selected by the driver or the like. v The obstacle risk potential Ri When multiple types of damage risks are selected, the damage risk setting unit 69 calculates the damage risk values ​​R v The average value of the obstacle risk potential R i The larger of the two may be added to the damage risk value R v The obstacle risk potential R i Each type of damage risk can be added to the damage risk value R v In this case, the damage risk setting unit 69 may be configured to set the proportion of the damage risk value R v The sum of the values ​​multiplied by the rate to be reflected is the damage risk value Rv.

[0062] (Operating condition setting section) The driving condition setting unit 71 sets driving conditions for the host vehicle 1 based on information on the basic risk map or damage risk map generated by the risk map generation unit 65 and information on the planned driving trajectory of the host vehicle 1. For example, when the collision determination unit 67 determines that a collision between the host vehicle 1 and a surrounding obstacle is avoidable, the driving condition setting unit 71 uses the basic risk map to set a target trajectory in which the risk value is equal to or less than a predetermined threshold. At that time, the driving condition setting unit 71 may also decelerate the host vehicle 1. The driving condition setting unit 71 sets a target steering angle and a target acceleration / deceleration based on information on the set target trajectory and target vehicle speed, and transmits this information to the vehicle control device 41. The vehicle control device 41, which has received the information on the driving conditions, controls the operation of each control device based on the information on the set driving conditions. This avoids a collision between the host vehicle 1 and a surrounding obstacle.

[0063] Furthermore, when the collision determination unit 67 determines that a collision between the host vehicle 1 and a surrounding obstacle cannot be avoided, the driving condition setting unit 71 sets a target trajectory that minimizes the risk value using a damage risk map. At that time, the driving condition setting unit 71 also decelerates the host vehicle 1. The driving condition setting unit 71 sets a target steering angle and a target acceleration / deceleration based on the set target trajectory and target vehicle speed information, and transmits this information to the vehicle control device 41. The vehicle control device 41, which has received the driving condition information, controls the operation of each control device based on the set driving condition information. As a result, even if a collision between the host vehicle 1 and a surrounding obstacle occurs, the risk of damage is reduced in accordance with the driver's intentions.

[0064] <3. Operation of driving assistance device> Next, an example of the operation of the driving assistance device 50 according to this embodiment will be specifically described.

[0065] FIG. 11 is a flowchart showing an example of processing executed by the processing unit 51 of the driving assistance device 50. First, when the in-vehicle system including the driving assistance device 50 is activated (step S11), the surrounding environment detection unit 61 of the processing unit 51 acquires surrounding environment information of the host vehicle 1 (step S13). Specifically, the surrounding environment detection unit 61 detects obstacles present around the host vehicle 1 based on detection data transmitted from the surrounding environment sensor 31. The surrounding environment detection unit 61 also calculates the position, type, and size (width, height, and depth) of the detected obstacle, the distance from the host vehicle 1 to the obstacle, and the relative speed between the host vehicle 1 and the obstacle. The detected obstacles include other moving vehicles, parked vehicles, pedestrians, bicycles, side walls, curbs, buildings, utility poles, traffic signs, traffic signals, natural objects, and any other objects present around the host vehicle 1. The surrounding environment detection unit 61 stores the acquired surrounding environment information in the memory unit 53.

[0066] For example, the surrounding environment detection unit 61 detects obstacles ahead of the host vehicle 1 and the type of the obstacles by performing image processing on the image data transmitted from the front-facing cameras 31LF, 31RF, using pattern matching technology or the like. The surrounding environment detection unit 61 also calculates the position, size, and distance to the obstacle as seen from the host vehicle 1, based on the position of the obstacle in the image data, the size of the obstacle in the image data, and information on the parallax between the left and right front-facing cameras 31LF, 31RF. Furthermore, the surrounding environment detection unit 61 calculates the relative speed between the host vehicle 1 and the obstacle by differentiating the change in distance with respect to time.

[0067] Furthermore, the surrounding environment detection unit 61 estimates the positions of occupants in other vehicles based on image data transmitted from the front-view cameras 31LF, 31RF. For example, the surrounding environment detection unit 61 detects occupants of other vehicles through a matching process and identifies whether the occupants are located on the right or left side as viewed from the host vehicle 1. However, the positions of occupants in other vehicles may also be obtained from other vehicles via, for example, vehicle-to-vehicle communication.

[0068] The surrounding environment detection unit 61 may also detect an obstacle based on detection data transmitted from the LiDAR 31S. For example, the surrounding environment detection unit 61 may calculate the position, type, size, and distance from the host vehicle 1 to the obstacle based on information on the time from when the LiDAR 31S transmits an electromagnetic wave until it receives a reflected wave, the direction in which the reflected wave is received, and the range of the measurement point group of the reflected wave. The surrounding environment detection unit 61 may also calculate the relative speed between the host vehicle 1 and the obstacle by differentiating the change in distance with respect to time.

[0069] Next, the risk map generating unit 65 of the processing unit 51 calculates the obstacle risk potential R i Specifically, the risk map generating unit 65 calculates the obstacle risk potential R for each obstacle according to the type, size, relative speed, etc. of the obstacle. iIn this embodiment, the risk value is defined within a range from "0" to "1," and the risk value of an area where an obstacle exists is set to "1," making the area untravelable. The risk value is also set to gradually decrease the further away from the outer periphery of the area where the obstacle exists.

[0070] Next, the risk map generating unit 65 calculates the obstacle risk potential R i The risk map generating unit 65 generates a basic risk map by superimposing the obstacle risk potentials R i In the overlapping area, the maximum value of the risk values ​​at each position is set as the risk value of that position, and a risk map is generated that shows the distribution of risk values ​​around the vehicle 1. i In a region where these risk maps overlap, the risk values ​​at each position may be integrated to determine the risk value at that position. In a risk map, the level of risk is displayed as contour lines on a two-dimensional plane.

[0071] Next, the collision determination unit 67 of the processing unit 51 determines whether or not the host vehicle 1 is in a situation where it can avoid a collision with an obstacle present around the host vehicle 1 (step S21). For example, the collision determination unit 67 determines whether or not a collision between the host vehicle 1 and the obstacle can be avoided based on information about the basic risk map generated by the risk map generation unit 65 and information about the operation state and behavior of the host vehicle 1 detected by the driving state detection unit 63. Specifically, the collision determination unit 67 acquires information about the current operation state and behavior of the host vehicle 1, and determines whether or not a collision with the obstacle can be avoided by controlling the driving of the host vehicle 1 within a preset settable range of steering angular velocity and a preset settable range of deceleration.

[0072] Alternatively, the collision determination unit 67 may determine whether or not a collision with an obstacle can be avoided by controlling the driving of the host vehicle 1 within a preset settable range of steering angular speed and a preset settable range of deceleration, based on the distance to the obstacle ahead in the traveling direction of the host vehicle 1, the relative speed, and the operation state and behavior of the host vehicle 1, without using information from the basic risk map. Note that the method of determining whether or not a collision between the host vehicle 1 and an obstacle can be avoided is not limited to the above example.

[0073] If it is determined that the host vehicle 1 is in a situation where it can avoid a collision with an obstacle (S21 / Yes), the driving condition setting unit 71 sets the driving conditions of the host vehicle 1 using the basic risk map generated in step S19 (step S27). For example, the driving condition setting unit 71 sets a target trajectory so that the risk value is minimized or equal to or less than a predetermined threshold, based on a reference path (planned driving trajectory) set for the planned driving route of the host vehicle 1 and information on the basic risk map. The driving condition setting unit 71 may also decelerate the host vehicle 1. The driving condition setting unit 71 sets a target steering angle and a target acceleration / deceleration based on information on the set target trajectory and target vehicle speed.

[0074] On the other hand, if it is not determined that the host vehicle 1 is in a situation where it can avoid a collision with an obstacle (S21 / No), the damage risk setting unit 69 of the processing unit 51 calculates the obstacle risk potential R i Damage risk value R to be added to v is set (step S23).

[0075] Figure 12 shows the damage risk value R v 10 is a flowchart showing a process for setting the value of the parameter. First, the damage risk setting unit 69 acquires setting information for the type of damage risk set by a user such as a driver (step S41). For example, potential types of damage risk, such as "risk of personal injury to the other party in a collision," "risk of personal injury to the vehicle's own side," and "damage and legal liability suffered by the vehicle's own side," are displayed on the display of the HMI 45, and the occupant selects one or more desired types of damage risk to set the type. However, the method for selecting the type of damage risk is not limited to the above example.

[0076] Next, the damage risk setting unit 69 refers to the damage database 55 and reads data on the damage situation at the time of the occurrence of an accident that corresponds to the current traffic situation of the host vehicle 1 (step S43). Specifically, the damage risk setting unit 69 acquires information on the environment around the host vehicle 1 and information on the operation state and behavior of the host vehicle 1, and extracts data on the damage situation of accidents that occurred under similar traffic situations, such as the type, position, relative speed, vehicle speed, and steering angle of an obstacle that makes a collision unavoidable, from the damage situation data stored in the damage database 55. As conditions for determining similar traffic situations, error ranges are set in advance for each of the type, position, relative speed, vehicle speed, steering angle, etc. of the obstacle, and the damage risk setting unit 69 extracts data on the damage situation of accidents that occurred under situations that fall within each error range.

[0077] Next, the damage risk setting unit 69 calculates the obstacle risk potential R that is set for the detected obstacle based on the read damage situation data and the setting information for the type of damage risk. i Damage risk value R to be added to v Specifically, the damage risk setting unit 69 calculates the damage risk value R of the damage risk type selected by the occupant from the damage situation data read in step S43. v When only one type of damage risk is selected, the damage risk setting unit 69 calculates the damage risk value R v This is the damage risk value R v Let's say.

[0078] In addition, when multiple types of damage risks are selected, the damage risk setting unit 69 calculates the damage risk values ​​R v The average value of the obstacle risk potential R i The larger of the two may be added to the damage risk value R v The obstacle risk potential R i Each type of damage risk can be added to the damage risk value R v When the damage risk setting unit 69 is configured to be able to set the ratio of the damage risk value R v The sum of the values ​​multiplied by the rate of reflection is the damage risk value R v Let's say.

[0079] By executing the processes of steps S41 to S43, in a situation where a collision between the vehicle 1 and any obstacle cannot be avoided, a damage risk value R that reflects the intention of a user such as a driver is calculated based on data on the damage situation of past accidents. v can be set.

[0080] Returning to FIG. 11, in step S23, a damage risk value R is added to the obstacle risk potential Ri set for the obstacle around the host vehicle 1. v After setting the obstacle risk potential R i Damage risk value R v and generate a damage risk map by updating the basic risk map (step S25).

[0081] Next, the driving condition setting unit 71 sets the driving conditions of the host vehicle 1 using the damage risk map (step S27). For example, the driving condition setting unit 71 sets a target trajectory so that the risk value is minimized or below a predetermined threshold based on a reference path (planned driving trajectory) set for the planned driving route of the host vehicle 1 and information on the damage risk map. The target trajectory set using the damage risk map is set to a trajectory different from the target trajectory set using the basic risk map. The driving condition setting unit 71 may also decelerate the host vehicle 1. The driving condition setting unit 71 calculates a target steering angle and a target acceleration / deceleration based on information on the set target trajectory and target vehicle speed.

[0082] Next, the driving condition setting unit 71 outputs information about the driving conditions set in step S27 to the vehicle control device 41 (step S29). Having acquired the information about the driving conditions, the vehicle control device 41 sets target control amounts for the driving force source 9, the electric steering device 15, and the brake fluid pressure control unit 20 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 brake fluid pressure control unit 20. This controls the driving of the host vehicle 1 along the target trajectory set by the driving assistance device 50, and can control the collision position of the host vehicle 1 so as to reduce the risk of damage in accordance with the intention of a user such as a driver.

[0083] Alternatively, the driving assistance device 50 may set the target trajectory and the target vehicle speed, and output information on the target trajectory and the target vehicle speed to the vehicle control device 41, which may then calculate the target steering angle and the target acceleration / deceleration.

[0084] Next, the driving condition setting unit 71 determines whether the in-vehicle system has stopped (step S31). If the in-vehicle system has not stopped (S31 / No), the processing unit 51 returns to step S31 and repeats the processing of each step described so far. On the other hand, if the in-vehicle system has stopped (S31 / Yes), the processing unit 51 ends the processing.

[0085] By executing the series of processes in this manner, the processing unit 51 of the driving assistance device 50 sets the driving conditions of the vehicle 1 and outputs information about the driving conditions to the vehicle control device 41. As a result, in a situation where a collision between the vehicle 1 and an obstacle cannot be avoided, the collision position of the vehicle 1 can be controlled so as to reduce the risk of damage according to the intention of a user such as a driver.

[0086] <4. Application Examples> Next, an example in which the technology of the present disclosure is applied will be described.

[0087] (4-1. First application example) An application example when the type of damage risk of the rate of fatalities and injuries to the other party in a collision is selected will be described with reference to Figures 13 and 14. Figures 13 and 14 are diagrams for explaining the target trajectory that is set when the type of damage risk of the rate of fatalities and injuries to the other party in a collision is selected.

[0088] As shown in Fig. 13, consider a traffic situation in which a pedestrian W and a preceding vehicle Ve are present in front of the host vehicle 1, and the host vehicle 1 cannot avoid colliding with either the pedestrian W or the preceding vehicle Ve. v The obstacle risk potential R i When the target trajectory Tr of the host vehicle 1 is calculated using a basic risk map in which only the pedestrian W and the preceding vehicle Ve are set, the obstacle risk potential R i and the obstacle risk potential R of the forward vehicle Ve i A target trajectory Tr is set so that the target trajectory Tr passes through the position where the two intersect. However, if the host vehicle 1 is caused to travel along the target trajectory Tr, it will collide with both the pedestrian W and the preceding vehicle Ve, and there is a possibility that the physical damage to the pedestrian W in particular will be severe.

[0089] In contrast, the damage risk value R v The obstacle risk potential R i When added to this, the injury risk value for pedestrian W is R v is the damage risk value R of the forward vehicle Ve vIn addition, since only the driver is in the vehicle in front, the damage risk value R v is set relatively small. Therefore, the target trajectory Tr' of the host vehicle 1 obtained using the damage risk map is corrected to the side of the forward vehicle Ve compared to the original target trajectory Tr. This reduces the expected physical damage to the other party in a collision.

[0090] (4-2. Second application example) An application example when the type of damage risk of the fatality and injury rate of the host vehicle is selected will be described with reference to Figures 15 and 16. Figures 15 and 16 are diagrams for explaining the target trajectory that is set when the type of damage risk of the fatality and injury rate of the occupants of the host vehicle is selected.

[0091] Consider a traffic situation in which a preceding vehicle Ve is present in front of the host vehicle 1 and the host vehicle 1 cannot avoid colliding with the preceding vehicle Ve, as shown in Fig. 15. v The obstacle risk potential R i When the target trajectory Tr of the host vehicle 1 is determined using a basic risk map in which only the forward vehicle Ve is set, the risk value of the area in which the forward vehicle Ve exists is constant, and the collision position of the host vehicle 1 with respect to the forward vehicle Ve is set according to the relative positions of the host vehicle 1 and the forward vehicle Ve. Therefore, depending on the collision position, the impact on the driver's seat side of the host vehicle 1 may become large, which may result in serious physical damage to the driver of the host vehicle 1.

[0092] In contrast, the damage risk value R v The obstacle risk potential R i , as shown in FIG. 16, since only the driver is in the host vehicle 1, the damage risk value R v is set relatively small. Therefore, the target trajectory Tr' of the host vehicle 1 obtained using the damage risk map is set to the rear right side of the leading vehicle Ve. This reduces the expected physical damage to the occupants of the host vehicle 1.

[0093] <5. Summary> As described above, the driving assistance device 50 according to this embodiment includes a damage database 55 that records multiple types of damage situations that occurred in past collision accidents, and generates a damage risk map by adding a damage risk value set according to at least one type of damage risk selected by a user such as a driver to an obstacle risk potential set for each obstacle. Based on the generated damage risk map, the driving assistance device 50 then sets driving conditions for the host vehicle 1 so that the collision position between the host vehicle 1 and the obstacle will be a collision position that reduces the risk value. This allows the host vehicle 1 to be guided to a collision position that reduces the risk of damage in line with the driver's intentions when the host vehicle 1 collides with an obstacle.

[0094] Since the damage risk value is set based on the type of damage risk and the type of obstacle, the damage risk value is set according to the expected magnitude of damage, and the vehicle 1 can be correctly guided to a collision position that reduces the risk of damage in line with the driver's intentions.

[0095] Furthermore, the driving support device 50 according to this embodiment executes the process of setting driving conditions using the basic risk map, and sets driving conditions using a damage risk map to which a damage risk value has been added only when it is determined that a collision between the vehicle 1 and an obstacle cannot be avoided, thereby reducing the load on the processor.

[0096] Furthermore, the driving assistance device 50 according to this embodiment adds a damage risk value to the obstacle risk potential, which indicates the risk of collision with each obstacle, to set driving conditions that reduce the risk of damage in line with the driver's intention. This allows the processor to execute a single process, rather than executing multiple different processes, to set driving conditions that reduce the risk of damage by distinguishing between cases where a collision with an obstacle can be avoided and cases where it cannot be avoided.

[0097] Although the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art to which the present disclosure pertains can conceive of various modifications or alterations within the scope of the technical ideas set forth in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure.

[0098] For example, in the above embodiment, all of the functions of the driving assistance device 50 are installed in the vehicle 1, but the present disclosure is not limited to such an example. For example, some of the functions of the driving assistance device 50 may be provided in a server device that can communicate via mobile communication means, and the driving assistance device 50 may be configured to transmit and receive data to and from the server device.

[0099] Furthermore, in the above embodiment, when it is determined that the host vehicle 1 cannot avoid a collision with an obstacle, the driving conditions of the host vehicle 1 are set using a damage risk map in which a damage risk value is added to the obstacle risk potential, but the technology of the present disclosure is not limited to such an example. The driving assistance device 50 may also set the driving conditions of the host vehicle 1 using a damage risk map in which a damage risk value is always added to the obstacle risk potential. This makes it easier to reduce damage that occurs when an obstacle makes an unexpected movement.

[0100] The following aspects also fall within the technical scope of the present disclosure. In the driving assistance device according to the above embodiment, the damage risk value to be added is set based on the type of damage risk and the type of obstacle. A recording medium having recorded thereon a computer program applied to a driving assistance device that sets driving conditions for a vehicle based on the risk of collision with an obstacle around the vehicle, the computer program causing one or more processors to execute processes including: acquiring setting information for at least one damage risk selected from options for the risk of damage caused by a collision between the vehicle and an obstacle around the vehicle; detecting obstacles around the vehicle; and setting a target trajectory for the vehicle based on the risk of collision of the vehicle with the detected obstacle and the at least one selected damage risk. [Explanation of symbols]

[0101] 1: Vehicle (host vehicle), 31: Surrounding environment sensor, 35: Vehicle state sensor, 41: Vehicle control device, 50: Driving assistance device, 51: Processing unit, 53: Storage unit, 55: Damage database, 61: Surrounding environment detection unit, 63: Driving state detection unit, 65: Risk map generation unit, 67: Collision determination unit, 69: Damage risk setting unit, 71: Driving condition setting unit

Claims

1. 1. A driving assistance device that sets driving conditions for a vehicle based on a collision risk with an obstacle around the vehicle, one or more processors; and one or more memories communicatively coupled to the one or more processors; The collision risk is set for each of the obstacles so that the maximum value is a range that overlaps with the location of the obstacle, and the value decreases as the distance from the obstacle increases, the one or more processors: acquiring setting information for at least one damage risk selected from options for damage risks that may occur due to a collision between the vehicle and an obstacle around the vehicle; Detecting obstacles around the vehicle; and executing a process including adding a risk value of the damage risk to a maximum value of the collision risk in a range overlapping with the position of the obstacle based on the collision risk of the vehicle with the detected obstacle and the selected at least one damage risk, and setting a target trajectory of the vehicle; When a risk of bodily injury to the other party of a collision is set as the damage risk, a risk value to be added to an area where the other party of a collision is expected to have a large bodily injury is set to be larger than a risk value to be added to an area where the other party of a collision is expected to have a small bodily injury, even within a range overlapping with the location of the obstacle. A driving assistance device that performs processing including the steps of:

2. The risk of damage is: The driving assistance device according to claim 1, wherein the user selects from among a risk of punitive harm to the driver of the vehicle, a risk of compensatory harm to the driver of the vehicle, a risk of personal injury to the other party in the collision, and a risk of personal injury to the vehicle.

3. the one or more processors: If the target trajectory can be set so as not to collide with the detected obstacle, the target trajectory is set based only on the collision risk; The driving assistance device according to claim 1 , wherein the target trajectory is set based on the collision risk and the damage risk when a collision with at least one of the obstacles cannot be avoided.

4. A driving assistance device that sets driving conditions for a vehicle based on a collision risk with an obstacle around the vehicle, one or more processors; and one or more memories communicatively coupled to the one or more processors; The collision risk is set for each of the obstacles so that the maximum value is a range that overlaps with the location of the obstacle, and the value decreases as the distance from the obstacle increases, the one or more processors: acquiring setting information for at least one damage risk selected from options for damage risks that may occur due to a collision between the vehicle and an obstacle around the vehicle; Detecting obstacles around the vehicle; and executing a process including adding a risk value of the damage risk to a maximum value of the collision risk in a range overlapping with the position of the obstacle based on the collision risk of the vehicle with the detected obstacle and the selected at least one damage risk, and setting a target trajectory of the vehicle; When a risk of bodily injury to the vehicle is set as the damage risk, a driving assistance device varies the risk value to be added so as to reduce the expected bodily injury to the vehicle even within an area overlapping with the location of the obstacle.

5. A computer program applied to a driving assistance device that sets driving conditions for a vehicle based on a collision risk with an obstacle around the vehicle. one or more processors, acquiring setting information of at least one damage risk selected from options of damage risks that may occur due to a collision between the vehicle and an obstacle around the vehicle; Detecting obstacles around the vehicle; a collision risk of the vehicle that is set so that the range overlapping with the location of the obstacle becomes a maximum value and the value decreases as the distance from the obstacle increases, based on the at least one selected damage risk, and adding a risk value of the damage risk to the maximum value of the collision risk in the range overlapping with the location of the obstacle, and setting a target trajectory of the vehicle; When a risk of bodily injury to the other party of a collision is set as the damage risk, a risk value to be added to an area where the other party of a collision is expected to have large bodily injury is made larger than a risk value to be added to an area where the other party of a collision is expected to have small bodily injury, even within a range overlapping with the location of the obstacle. A computer program that causes a process including the steps of:

6. A computer program applied to a driving assistance device that sets driving conditions for a vehicle based on a collision risk with an obstacle around the vehicle. one or more processors, acquiring setting information of at least one damage risk selected from options of damage risks that may occur due to a collision between the vehicle and an obstacle around the vehicle; Detecting obstacles around the vehicle; a collision risk of the vehicle that is set so that the range overlapping with the location of the obstacle becomes a maximum value and the value decreases as the distance from the obstacle increases, based on the at least one selected damage risk, and adding a risk value of the damage risk to the maximum value of the collision risk in the range overlapping with the location of the obstacle, and setting a target trajectory of the vehicle; When a risk of bodily injury to the vehicle is set as the damage risk, the risk value to be added is varied so as to reduce the bodily injury expected to the vehicle even within a range overlapping the position of the obstacle; A computer program that causes a process including the steps of:

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