Vehicle control device and vehicle control method

Abstract

To solve such a problem that passengers may experience discomfort or fear due to approach to a mobile body when traveling in cooperation with the mobile body existing in the periphery.SOLUTION: A vehicle control device includes: an approach determination unit 508 that determines approach of a mobile body to an own vehicle; a steering limitation setting unit 603 that sets an allowable range for the relative yaw angle which is the angle between the traveling direction of the own vehicle and the traveling direction of the mobile body or a change amount in the relative yaw angle; and a trajectory planning unit 507 that, when the approach determination unit 508 determines that a mobile body is approaching the own vehicle, plans a trajectory related to movement of the own vehicle such that the relative yaw angle after movement of the own vehicle or the change amount in the relative yaw angle due to movement of the own vehicle falls within the allowable range.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to a vehicle control device and a vehicle control method. [Background technology]

[0002] In recent years, the development of autonomous driving technology for automobiles and other vehicles has progressed. When autonomous driving is performed, the road on which the vehicle travels is not always of an appropriate width. For example, on a road (narrow road) where the road width is narrow and it is difficult for the vehicle and oncoming vehicles to pass each other, a different control method than that used during normal driving is required to move the vehicle to a place where they can pass each other.

[0003] For example, a technology has been disclosed that plans the actions of a vehicle, such as starting, stopping, and direction of travel, in order to control the vehicle to return to the entrance of the road where it is possible to pass each other on a road where there is no turning-off space between the vehicle and an oncoming vehicle (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2018-151177 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, with conventional methods, when the vehicle is driven autonomously (and with advanced driving assistance) on narrow urban streets or when it is driven autonomously in parking lots, the occupants may feel uncomfortable or scared due to the vehicle approaching nearby moving objects, especially when the vehicle is driven in close proximity to nearby moving objects.

[0006] In view of the above circumstances, there has been a demand for a method for mitigating the discomfort and fear felt by passengers when approaching a nearby moving object when driving cooperatively with the nearby moving object. [Means for solving the problem]

[0007] In order to solve the above problems, a vehicle control device of one embodiment of the present invention includes an approach determination unit that determines the approach of a moving body to the host vehicle, a steering limit setting unit that sets an acceptable range for the relative yaw angle, which is the angle between the traveling direction of the host vehicle and the traveling direction of the moving body, or a relative yaw angle change amount, and when the approach determination unit determines that the moving body is approaching the host vehicle, a trajectory planning unit that plans a trajectory for the movement of the host vehicle so that the relative yaw angle after the movement of the host vehicle or the relative yaw angle change amount accompanying the movement of the host vehicle is within the acceptable range. Effect of the Invention

[0008] According to at least one aspect of the present invention, when the vehicle is traveling in cooperation with a nearby moving object, a trajectory for the movement of the vehicle can be planned so as to reduce the discomfort or fear felt by occupants due to approaching the moving object. Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an example of the configuration of a driving system and sensors of a vehicle equipped with a vehicle control device according to a first embodiment of the present invention. [Diagram 2] 1 is a block diagram showing an example of the configuration of a vehicle control device according to a first embodiment of the present invention. [Diagram 3] 2 is a block diagram showing an example of the configuration of a risk map generating unit of the vehicle control device according to the first embodiment of the present invention. FIG. [Figure 4] 5 is a flowchart showing an example of a delay risk map generation process performed by the vehicle control device according to the first embodiment of the present invention. [Diagram 5] 4A to 4C are diagrams showing an example of a cooperative action plan and a delay risk map generated in the vehicle control device according to the first embodiment of the present invention. [Figure 6] 2 is a block diagram showing a configuration example of a vehicle driving planner of the vehicle control device according to the first embodiment of the present invention. FIG. [Figure 7]2 is a block diagram showing an example of the configuration of a cooperative behavior trajectory generating unit of the vehicle control device according to the first embodiment of the present invention. FIG. [Figure 8] 5 is a flowchart showing an example of a process of generating an evacuation position and attitude by the vehicle control device according to the first embodiment of the present invention. [Figure 9] 5A to 5C are diagrams illustrating an example of a process for generating candidate target turning-away position and attitude by the vehicle control device according to the first embodiment of the present invention. [Figure 10] 5 is a flowchart showing an example of a cooperative behavior trajectory generation process by the vehicle control device according to the first embodiment of the present invention. [Figure 11] 3 is a diagram showing an example of an arrival position candidate by the vehicle control device according to the first embodiment of the present invention. FIG. [Figure 12] FIG. 2 is a diagram showing an example of a coordinated behavior trajectory (passing trajectory) by the vehicle control device according to the first embodiment of the present invention. [Figure 13] FIG. 2 is a diagram showing an example of a retention risk map and a planned coordinated behavior trajectory (passing trajectory) by the vehicle control device according to the first embodiment of the present invention. [Figure 14] FIG. 2 is a diagram showing an example of an example in which a passenger of a host vehicle feels anxiety or fear when traveling along a coordinated behavior trajectory according to the first embodiment of the present invention. [Figure 15] 5 is a flowchart showing an example of a steering limit setting process performed by the vehicle control device according to the first embodiment of the present invention when approaching a surrounding object. [Figure 16] 5 is a flowchart showing an example of a process of generating a waiting position when a surrounding object approaches, performed by the vehicle control device according to the first embodiment of the present invention. [Figure 17] 5 is a flowchart showing an example of a process of generating an avoidance trajectory when a peripheral object approaches, performed by the vehicle control device according to the first embodiment of the present invention. [Figure 18] 2 is a block diagram showing an example of the configuration of a driving mode management unit of the vehicle control device according to the first embodiment of the present invention. FIG. [Figure 19] 3 is a diagram illustrating an example of control of a steering angle when approaching a surrounding object in the vehicle control device according to the first embodiment of the present invention. FIG. [Figure 20]11 is a diagram illustrating an example of a peripheral object approach determination process performed by a peripheral object approach determination unit of a vehicle control device according to a second embodiment of the present invention. FIG. [Figure 21] 13A to 13C are diagrams illustrating an example of vehicle movement, collision time, and threshold values ​​in a vehicle control device according to a second embodiment of the present invention. [Figure 22] 13 is a diagram showing an example of the relationship between the collision time and the threshold value when the differential value of the collision time is positive and negative in a vehicle control device according to a second embodiment of the present invention. FIG. [Figure 23] 13A to 13C are diagrams illustrating an example of the movement of a vehicle and an example of the visual field range of an occupant in a vehicle control device according to a third embodiment of the present invention. [Figure 24] 13 is a diagram illustrating an example of a peripheral object approach determination process performed by a peripheral object approach determination unit of a vehicle control device according to a third embodiment of the present invention. FIG. [Diagram 25] 13 is a flowchart showing an example of a visual field restriction determination process performed by a vehicle control device according to a third embodiment of the present invention. [Figure 26] 13 is a diagram illustrating an example of approach determination processing by a peripheral object approach determiner of a vehicle control device according to a fourth embodiment of the present invention. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, examples of modes for carrying out the present invention (hereinafter, referred to as "embodiments") will be described with reference to the accompanying drawings.

[0011] In this specification and the accompanying drawings, the same or similar components are given the same reference numerals, and redundant explanations may be omitted or only differences may be explained. The number of each component may be singular or plural unless otherwise specified.

[0012] <First embodiment> A vehicle control device and a vehicle control method according to a first embodiment of the present invention will be described below with reference to FIGS.

[0013] [Vehicle configuration] First, the overall configuration of a vehicle equipped with a vehicle control device according to a first embodiment of the present invention will be described with reference to FIG. 1 is a block diagram showing an example of the configuration of a driving system and sensors of a vehicle 100 equipped with a vehicle control device 1 according to a first embodiment. The vehicle 100 is automatically driven under the control of the vehicle control device 1.

[0014] As shown in FIG. 1, a vehicle 100 has a left front wheel 101FL, a right front wheel 101FR, a left rear wheel 101RL, and a right rear wheel 101RR. The vehicle 100 is equipped with a forward recognition sensor 2, a left side recognition sensor 3, a right side recognition sensor 4, and a rear recognition sensor 5 as sensors for recognizing the outside world, and can detect the relative distance and relative speed between the vehicle itself and surrounding vehicles. For example, a camera can be used as the sensor for recognizing the outside world. Information (detection signals) from these sensors 2, 3, 4, and 5 is supplied to the vehicle control device 1.

[0015] The vehicle control device 1 calculates command values ​​for a steering control mechanism 10, a brake control mechanism 13, and a throttle control mechanism 20 for controlling the traveling direction of the vehicle 100 based on information from the sensors 2, 3, 4, and 5. The vehicle 100 is equipped with a steering control device 8 that controls the steering control mechanism 10 based on a command value from the vehicle control device 1, and a braking control device 15 that controls the brake control mechanism 13 and adjusts the brake force distribution of each wheel based on a command value from the vehicle control device 1. The vehicle 100 further includes an acceleration control device 19 that controls the throttle control mechanism 20 and adjusts the torque output of the engine based on a command value from the vehicle control device 1, and a display device 24 that displays a travel plan for the vehicle 100 and predicted behavior of moving objects in the vicinity.

[0016] The vehicle 100 also includes a communication device 23 that performs road-to-vehicle or vehicle-to-vehicle communication. Note that the sensor configuration shown in Fig. 1 is an example, and is not limited to the example in Fig. 1. The types of sensors may also be various sensors such as ultrasonic sensors, stereo cameras, infrared cameras, radars, and LiDARs, or a combination of these sensors.

[0017] The vehicle control device 1 is configured as an arithmetic processing device equipped with, for example, a CPU, a memory, etc., as described later in Fig. 2. A program for performing vehicle driving control processing is stored in the vehicle control device 1, and the vehicle control device 1 generates a driving plan by executing the program. The vehicle control device 1 calculates command values ​​for each control mechanism (hereinafter also referred to as "actuators") 10, 13, 20 for controlling vehicle driving in accordance with the generated driving plan. Control devices 8, 15, 19 for each actuator 10, 13, 20 receive the command values ​​of the vehicle control device 1 via communication, and control each actuator based on the command values.

[0018] The configuration for actuating the brake shown in FIG. 1 will now be described. When the driver is driving, the force generated by the driver stepping on the brake pedal 12 is boosted by a brake booster (not shown), and a corresponding hydraulic pressure is generated by a master cylinder (not shown). The generated hydraulic pressure is supplied via a brake control mechanism 13 to wheel cylinders 16FL, 16FR, 16RL, and 16RR arranged on each of the wheels 101FL to 101RR.

[0019] Wheel cylinders 16FL-16RR are composed of cylinders, pistons, pads, etc., and the pistons are driven by hydraulic fluid supplied from master cylinder 9, and pads connected to the pistons are pressed against the disc rotors. The disc rotors rotate together with the wheels constituting each of wheels 101FL-101RR. Therefore, the brake torque acting on the disc rotors becomes a braking force acting between the wheels and the road surface. With the above configuration, braking force can be generated on each wheel in response to the driver's brake pedal operation.

[0020] The braking control device 15 is configured as an arithmetic processing device equipped with, for example, a CPU, a memory, etc., similar to the vehicle control device 1. The braking control device 15 receives inputs of a combined sensor 14 capable of detecting longitudinal acceleration, lateral acceleration, and yaw rate, wheel speed sensors 11FL-11RR installed on each wheel, a braking force command from the braking control device 15, and a sensor signal from a steering wheel angle detection device 21 via a steering control device 8 described later. The output of the braking control device 15 is connected to a brake control mechanism 13 having a pump and a control valve, and can generate an arbitrary braking force on each wheel independently of the driver's brake pedal operation.

[0021] The braking control device 15 plays a role of estimating spin, drift-out, and wheel lock of the vehicle based on the input of the sensor signal, and generating a braking force of the corresponding wheel to suppress them, thereby improving the driving stability of the driver. In addition, the vehicle control device 1 can generate any braking force in the vehicle 100 by sending a brake command to the braking control device 15, and plays a role of automatically performing braking in automatic driving where no operation by the driver is required. However, the configuration for performing braking is not limited to this configuration, and other actuators such as brake-by-wire may be used.

[0022] Next, a configuration for performing a steering operation will be described. While the driver is driving the vehicle 100, the steering torque detection device 7 detects the steering torque input by the driver via the steering wheel 6, and the steering wheel angle detection device 21 detects the steering wheel angle. Based on this information, the steering control device 8 controls the motor to generate an assist torque. Note that, like the vehicle control device 1, the steering control device 8 is also configured as an arithmetic processing device equipped with, for example, a CPU, a memory, and the like.

[0023] The resultant force of the steering torque of the driver and the assist torque of the motor moves the steering control mechanism 10, changing the direction of the front wheels (turning the front wheels). Meanwhile, a reaction force from the road surface is transmitted to the steering control mechanism 10 according to the turning angle of the front wheels, and is then transmitted to the driver as a road reaction force.

[0024] The steering control device 8 can generate torque by a motor and control the steering control mechanism 10, independent of the steering operation of the driver. Therefore, the vehicle control device 1 can control the front wheels to any turning angle by communicating a steering force command to the steering control device 8, and therefore plays a role of automatically performing steering in automatic driving where no operation by the driver is required. However, this embodiment is not limited to the steering control device 8 shown in FIG. 1, and a configuration in which the steering operation is performed using another actuator such as a steer-by-wire may be used.

[0025] Next, the configuration of the accelerator will be described. The amount of depression of an accelerator pedal 17 by the driver is detected by a stroke sensor 18 and input to an acceleration control device 19. Like the vehicle control device 1, this acceleration control device 19 is also configured as an arithmetic processing device including, for example, a CPU, a memory, and the like.

[0026] The acceleration control device 19 adjusts the throttle opening according to the depression amount of the accelerator pedal 17 and controls the engine. As a result, the acceleration control device 19 can accelerate the vehicle 100 according to the accelerator pedal operation by the driver. In addition, the acceleration control device 19 can control the throttle opening independently of the accelerator operation by the driver. Therefore, the vehicle control device 1 can generate any acceleration in the vehicle 100 by communicating an acceleration command to the acceleration control device 19, and plays a role of automatically accelerating the vehicle in autonomous driving where no operation by the driver is required.

[0027] [Vehicle control device configuration] Next, the configuration of the vehicle control device 1 that performs automatic driving control implemented in the vehicle 100 of this embodiment will be described with reference to FIG. FIG. 2 is a block diagram showing an example of the configuration of the vehicle control device 1. As shown outside the blocks in FIG. 2, the vehicle control device 1 is configured by, for example, a computer which is an information processing device. That is, the computer serving as the vehicle control device 1 includes a CPU (Central Processing Unit) 211 which is a processor, a memory 212, an input / output unit 213, and an interface 214.

[0028] As the memory 212, in addition to memories such as a ROM (Read Only Memory) and a RAM (Random Access Memory), storage devices such as an HDD (Hard Disk Drive) and an SSD (Solid State Drive) are used. The memory 212 stores information such as programs for operating the vehicle control device 1, parameters (including thresholds), various risk maps, driving conditions, and history. In addition, by reading and executing the programs under the control of the CPU 211, the memory 212 is configured with processing function units 201 to 205, which will be described later.

[0029] The input / output unit 213 performs input processing of information from the sensors 2 to 5 shown in FIG. The interface 214 performs information transmission processing with other information processing devices within the vehicle 100, such as the braking control device 15, and also performs transmission and reception processing with the outside via the communication device 23 shown in FIG.

[0030] Next, a description will be given of the processing function units configured in the vehicle control device 1. The vehicle control device 1 includes an automatic driving planner 201, an automatic parking planner 202, a vehicle motion control unit 203, an actuator control unit 204, and a risk map generator 205. These processing function units 201 to 205 can communicate with each other via a vehicle network 206. The vehicle network 206 may be connected wirelessly as well as via wired connection.

[0031] The automatic driving planner 201 plans the operation of the vehicle 100 to automatically drive the vehicle 100 to a destination. The automatic parking planning unit 202 plans the operation of the vehicle 100 to automatically park the vehicle 100 in a parking space in a parking lot or the like. The vehicle motion control unit 203 generates command values ​​for controlling the motion of the vehicle 100 during autonomous driving. The actuator control unit 204 controls each actuator such as the engine, brake, steering, etc., based on the command value output from the vehicle motion control unit 203. The risk map generating unit 205 generates a risk map of vehicles and obstacles present around the host vehicle, including oncoming vehicles.

[0032] The actuator control unit 204 may be implemented in hardware different from the vehicle control device 1, such as an engine controller or a brake controller. Also, the processing function units 201 to 205 may be implemented as different arithmetic processing devices (controllers).

[0033] [Configuration of risk map generation section] Next, the configuration of the risk map generating unit 205 will be described with reference to FIG. FIG. 3 is a block diagram showing an example of the configuration of the risk map generating unit 205. As shown in FIG.

[0034] The risk map generating unit 205 is supplied with information from a radar 301, a stereo camera 302, a vehicle sensor 303, and a lidar 304 as sensors that recognize the outside world.

[0035] That is, the radar 301 can measure the distance and direction to the target by emitting radio waves toward the target and measuring the reflected waves. Information (point cloud data) on the distance and direction to the target obtained by the radar 301 is supplied to the risk map generator 205.

[0036] In addition, the stereo camera 302 can obtain information about the depth direction of an object by simultaneously capturing images of the object from a plurality of different directions. The information about the depth direction obtained by the stereo camera 302 is supplied to the risk map generating unit 205.

[0037] Furthermore, the vehicle sensor 303 is a collective term for a plurality of sensors mounted on the vehicle 100. The vehicle sensor 303 is a group of sensors that obtain information on the vehicle speed and tire rotation speed, information calculated from the average position of the autonomous vehicle using the GNSS (Global Navigation Satellite System), destination information input by the person in the autonomous vehicle using a navigation system as an interface, and destination information specified by an operator or the like in a remote location using wireless communication such as a telephone line. The information obtained by these vehicle sensors 303 is supplied to the risk map generation unit 205.

[0038] The LIDAR 304 measures scattered light in response to the pulsed laser irradiation and detects the distance to a distant target. Information (point cloud data) on the distance to a distant target obtained by the LIDAR 304 is supplied to the risk map generating unit 205. However, the LIDAR 304 is not necessarily required for the risk map generating unit 205.

[0039] The risk map generating unit 205 includes a sensor information processing unit 305, a map information processing unit 306, a solid object behavior predicting unit 307, a storage unit 308, a stay risk map generating unit 309A, and a self-position estimation processing unit 310. Furthermore, the risk map generating unit 205 includes a fixed obstacle risk map generating unit 309B, a moving obstacle risk map generating unit 309C, and the like.

[0040] The sensor information processing unit 305 receives detection information from external sensors including a radar 301, a stereo camera 302, a vehicle sensor 303, and a lidar 304. The sensor information processing unit 305 obtains information on the surrounding environment (for example, object information on moving objects existing around the vehicle) from the detection information of the external sensors. The sensor information processing unit 305 functions as a recognition unit that performs recognition processing to recognize the situation around the vehicle 100 based on information on the detection results of the external sensors provided in the vehicle 100.

[0041] Specific object information includes attribute information of pedestrians, bicycles, vehicles, etc., and their current positions and current speed vectors. Moving objects also include parked vehicles that may move in the future even if their speed at the current time is zero.

[0042] The storage unit 308 stores road information and traffic light information from the point where the vehicle starts autonomous driving to the target point and the surrounding areas, route information from the current position to the target point, a traffic rule database for the travel section, etc. The storage unit 308 also stores a point cloud database used by the self-position estimation processing unit 310.

[0043] The map information processing unit 306 obtains road lane center line information and traffic light information required for autonomous driving from the information stored in the memory unit 308. The map information processing unit 306 then organizes information such as the illumination information of traffic lights through which the autonomous vehicle is scheduled to pass, and converts the lane center line information and traffic light information into information in a usable format.

[0044] Furthermore, the self-position estimation processing unit 310 estimates the location of the vehicle based on surrounding information obtained by the external sensor, the point cloud database, the steering angle of the vehicle 100, the vehicle speed, and information obtained by the GNSS.

[0045] The output of the sensor information processing unit 305 , the output of the map information processing unit 306 , and the output of the self-position estimation processing unit 310 are supplied to a three-dimensional object behavior prediction unit 307 .

[0046] Based on these input information, the solid object behavior prediction unit 307 calculates the future position and speed information (object prediction information) of each solid object. A solid object is a general term for moving objects and stationary objects that exist around the vehicle. In order to predict the movement of each moving object, the solid object behavior prediction unit 307 first predicts the position R(X(T), Y(T)) of each object at future time T based on the object information. As a specific prediction method, assuming that the current position of the moving object is Rn0(Xn(0), Yn(0)) and the current speed is Vn(Vxn, Vyn), the solid object behavior prediction unit 307 performs prediction calculation based on the following linear prediction formula [Mathematical formula 1], for example.

[0047] [Number 1] TIFF2025035908000002.tif10168

[0048] The calculation of formula [1] is performed on the assumption that each object moves at a constant speed in a straight line while maintaining its current speed in the future. This makes it possible to predict many objects in a short period of time. As another calculation method, the position and speed information of other vehicles obtained by a sensor or the like and image information obtained by a camera may be input into a trained neural network model to obtain a prediction result of the position and speed information of other vehicles in the future. This calculation also makes it possible to calculate the reliability of the prediction result.

[0049] The stay risk map generating unit 309A generates a stay risk map indicating the stay risk of surrounding vehicles such as oncoming vehicles based on the processing results of the sensor information processing unit 305, the map information processing unit 306, the self-location estimation processing unit 310, and the solid object behavior prediction unit 307. Collisions and deadlocks may occur when the vehicle does not act in a cooperative manner with surrounding objects such as vehicles, pedestrians, and bicycles. For such scenes, the stay risk map generating unit 309A generates a stay risk map using a predicted trajectory calculated based on the target behavior of the object to be coordinated, and outputs the generated stay risk map.

[0050] The fixed obstacle risk map generating unit 309B generates a fixed obstacle risk map indicating the fixed obstacle risk around the vehicle based on the processing results of the sensor information processing unit 305, the map information processing unit 306, the self-position estimation processing unit 310, and the solid object behavior prediction unit 307. Arrows between these processing units and the fixed obstacle risk map generating unit 309B are omitted.

[0051] Similar to the fixed obstacle risk map generating unit 309B, the moving obstacle risk map generating unit 309C generates a moving obstacle risk map indicating the moving obstacle risk around the host vehicle based on the processing results of each processing unit.

[0052] [Delay risk map generation process] Next, the retention risk map generating process by the risk map generating unit 205 (retention risk map generating unit 309A) will be described with reference to FIG.

[0053] FIG. 4 is a flowchart illustrating an example of a stagnation risk map generating process. First, the risk map generating unit 205 acquires various information including surrounding information (step S401). Next, the three-dimensional object behavior prediction unit 307 of the risk map generation unit 205 predicts the target behavior of the target vehicle based on the acquired surrounding information, such as the current position and speed information of oncoming vehicles that need to pass each other in cooperation with the host vehicle, and road environment information on which the host vehicle and the target vehicle are traveling (step S402). Note that the road environment information may include road shape, information on objects existing in the vicinity, surrounding map information, congestion information, and the like.

[0054] Then, the stay risk map generating unit 309A of the risk map generating unit 205 determines whether or not the target vehicle is a moving object that requires a coordinated action with the host vehicle (step S403). If it is determined in step S403 that cooperative action is necessary (YES in step S403), the delay risk map generation unit 309A generates and outputs a cooperative action plan and a delay risk map based on the target actions of the target vehicles that require cooperative action (step S404). Moreover, if it is determined in step S403 that cooperative behavior is not necessary (NO in step S403), the stay risk map generating unit 309A ends the process without generating a stay risk map.

[0055] The results of the generated collaborative action plan and congestion risk map are explained using Figure 5. Fig. 5 is a diagram showing an example of a generated cooperative action plan and a congestion risk map. Fig. 5A and Fig. 5B each show an example of a situation in which a host vehicle M1 and an oncoming vehicle M2 that requires cooperative action are about to pass each other on a narrow road. The example of Figure 5A is a case where the road boundary 741 on the left side of the host vehicle M1 is not straight and there is a bypass road 2200, and the example of Figure 5B is a case where the road boundary 741 on the left side of the host vehicle M1 is straight and the bypass road 2200 is on the opposite side (the right side as seen from the host vehicle M1).

[0056] In this way, in the situation shown in Figures 5A and 5B, the risk map generation unit 205 predicts the target arrival point 2201 of the oncoming vehicle M2 at a future time (a specified time until the cooperative behavior is completed) based on various information. Then, the risk map generating unit 205 predicts a route for the oncoming vehicle M2 to reach the predicted destination point 2201, and calculates an area where the oncoming vehicle M2 will pass along the route. The result calculated by the risk map generating unit 205 becomes a retention risk map 701. The retention risk map 701 in Fig. 5A is an example of a case where the host vehicle M1 moves to the bypass road 2200, and the retention risk map 701 in Fig. 5B is an example of a case where the oncoming vehicle M2 moves to the bypass road 2200.

[0057] Furthermore, the risk map generating unit 205 calculates the host vehicle waiting position 2202 where the host vehicle M1 will wait, based on the arrival target point 2201 of the oncoming vehicle M2 and the retention risk map 701. Then, the risk map generating unit 205 considers a sequence for executing each waiting action in series or in parallel so that the actions of the host vehicle M1 and the oncoming vehicle M2 are both completed, and sets the sequence that can realize this as the cooperative action plan.

[0058] As the cooperative action plan, first, the risk map generating unit 205 makes a plan for the host vehicle M1 to enter the host vehicle waiting position 2202 (step 1), then makes a plan for the oncoming vehicle M2 to pass beside the host vehicle M1 (step 2), and finally makes a plan for the host vehicle M1 to exit the waiting area (step 3). If a sequence that completes such cooperative behavior cannot be found, the target destination, the congestion risk map, and the vehicle's waiting position are reviewed again, and a sequence is recursively searched for.

[0059] [Configuration of the Autonomous Driving Planning Department] Next, the configuration of the automatic driving planning unit 201 will be described with reference to FIG. FIG. 6 is a block diagram showing an example of the configuration of the automatic driving planning unit 201. The automatic driving planning unit 201 includes a driving planning unit 501 that calculates a target trajectory, a driving mode management unit 509, a trajectory planning unit 507, and a surrounding object approach determination unit 508.

[0060] The driving plan unit 501 is supplied with a delay risk map, a cooperative action plan, lane information, map information, environmental information, route information, UI (User Interface) information, etc. The driving plan unit 501 calculates weights of candidate target actions that the vehicle can take based on the route information, environmental information, detection information of the vehicle sensor 303, and occupant state information.

[0061] The target action candidate weights are weights for actions that the vehicle can take, such as an LK candidate weight for maintaining the lane in which the vehicle is currently located, an LC candidate weight for changing lanes from the lane in which the vehicle is currently located to an adjacent lane, an OA candidate weight for avoiding an obstacle in front, and a CO candidate weight for cooperative behavior with other vehicles. For example, when traveling on a straight road, in a situation where there are no vehicles or objects in front that need to be avoided and the route information indicates that there is no need to change lanes to an adjacent lane, the weights are LK=100, LC=0, OA=0, and CO=0.

[0062] The trajectory planning unit 507 includes a lane keeping trajectory generating unit (LK) 502, a lane change trajectory generating unit (LC) 503, an obstacle avoidance trajectory generating unit (OA) 504, a cooperative behavior trajectory generating unit (CO) 505, and a trajectory arbitration unit 506. The trajectory planning unit 507 is an example of a trajectory planning unit that performs a traveling trajectory generation process that generates a traveling trajectory from the current position of the vehicle to a target position. The lane keeping trajectory generating unit 502 generates a trajectory for keeping the host vehicle in the center of the lane in which it is currently traveling. The lane change trajectory generating unit 503 generates a trajectory for changing lanes to an adjacent lane of the lane in which the host vehicle is currently traveling.

[0063] The obstacle avoidance trajectory generation unit 504 generates a trajectory that avoids objects that exist in the lane in which the host vehicle is currently traveling and that become obstacles to traveling. The cooperative behavior trajectory generating unit 505 generates a cooperative behavior trajectory for performing cooperative behavior with a peripheral object such as an oncoming vehicle. For example, as the cooperative behavior trajectory, a trajectory relating to movement of the host vehicle to a waiting space at a waiting position where the host vehicle and a moving body (e.g., an oncoming vehicle) pass each other is generated. The generation of the cooperative behavior trajectory takes into consideration the determination result by the peripheral object approach determining unit 508 as to whether or not an object around the host vehicle is approaching the host vehicle.

[0064] The peripheral object approach determination unit 508 determines the approach of a peripheral object by comparing distance information to the peripheral object obtained from the detection information of the external sensor with a threshold (distance determination). The threshold is stored in advance in the memory 212 (FIG. 2). The external sensor is, for example, a camera, a radar 301, a stereo camera 302, a lidar 304, or the like.

[0065] The trajectory arbitration unit 506 evaluates each of the lane keeping trajectory, lane change trajectory, obstacle avoidance trajectory, and cooperative behavior trajectory based on the safety level with respect to surrounding objects and the weighting of the target behavior candidates, selects the trajectory with the best evaluation, and generates the target trajectory.

[0066] The driving mode management unit 509 calculates previous selection information for calculating the target behavior candidate weight at the next sampling time based on the target driving mode selected by the trajectory arbitration unit 506, the trajectory evaluation value based on each target behavior candidate, and the manual driving request by the cooperative behavior trajectory generation unit 505. For example, when LK (maintain the current lane: lane keep) is selected based on the evaluation values ​​of LK=60, LC=40, OA=0, and CO=0, the driving mode management unit 509 generates the previously selected current driving information (current driving mode) so that LK is more likely to be selected for the continuity of behavior even at the next sampling time.

[0067] [Configuration of Cooperative Action Trajectory Generation Unit] Next, the configuration of the cooperative behavior trajectory generating unit 505 will be described with reference to FIG. 7 is a block diagram showing an example of the configuration of the cooperative behavior trajectory generating unit 505. The cooperative behavior trajectory generating unit 505 is supplied with various information such as a stay risk map, cooperative behavior plan information, environmental information, lane information, map information, and peripheral object approach determination information.

[0068] The cooperative behavior trajectory generation unit 505 includes a cooperative behavior state management unit 600, an avoidance position and attitude generation unit 601, a cooperative behavior basic trajectory generation unit 602, a peripheral object approach steering limit setting unit 603, a peripheral object approach avoidance position generation unit 604, a peripheral object approach trajectory generation unit 605, and a cooperative behavior trajectory selection unit 606. As can be seen from their names, the peripheral object approach steering limit setting unit 603, the peripheral object approach avoidance position generation unit 604, and the peripheral object approach trajectory generation unit 605 are used when a peripheral object (for example, a target vehicle of cooperative behavior) approaches the host vehicle.

[0069] The cooperative behavior state management unit 600 has a function of judging (first judgment) whether the vehicle is capable of tracking the cooperative behavior trajectory. In addition, the cooperative behavior state management unit 600 has a function of judging (second judgment) whether the vehicle is in a surrounding object approaching state when the vehicle is unable to track the cooperative behavior trajectory. The cooperative behavior state management unit 600 outputs each judgment result to the cooperative behavior trajectory selection unit 606.

[0070] The turnaround position and posture generation unit 601 generates candidates for a target turnaround position and posture in a collaborative action plan. The cooperative behavior basic trajectory generating unit 602 calculates a traveling trajectory (cooperative behavior basic trajectory) in the cooperative behavior mode based on the target turnaround position / posture candidates generated by the turnaround position / posture generating unit 601.

[0071] The steering limit setting unit 603 for when a surrounding object is approached performs a setting (steering limit for when a surrounding object is approached) to limit the steering of the vehicle when the vehicle approaches a surrounding object, based on the judgment of the approach of a surrounding object and the cooperative behavior basic trajectory generated by the cooperative behavior basic trajectory generating unit 602.

[0072] The peripheral object approaching waiting position generating unit 604 generates a waiting position when a peripheral object is approaching (peripheral object approaching waiting position) based on the peripheral object approaching determination and the peripheral object approaching steering limit set by the peripheral object approaching steering limit setting unit 603.

[0073] The peripheral object approach trajectory generation unit 605 generates a cooperative behavior trajectory when a peripheral object is approached based on the peripheral object approach judgment, the peripheral object approach steering limit set by the peripheral object approach steering limit setting unit 603, and the peripheral object approach avoidance position generated by the peripheral object approach avoidance position generation unit 604.

[0074] The cooperative behavior trajectory selection unit 606 selects an appropriate trajectory from the cooperative behavior basic trajectory calculated by the cooperative behavior basic trajectory generation unit 602 and the cooperative behavior trajectory when approaching a peripheral object generated by the peripheral object approach trajectory generation unit 605, and controls the traveling of the vehicle 100. This selection reflects the result of the first judgment or the second judgment of the cooperative behavior state management unit 600.

[0075] For example, in the first judgment, if the vehicle is capable of tracking the cooperative behavior trajectory, the peripheral object approaching trajectory generating unit 605 selects the cooperative behavior basic trajectory. In addition, in the second judgment, if the vehicle is unable to track the cooperative behavior trajectory and is in a peripheral object approaching state, the peripheral object approaching trajectory generating unit 605 selects the cooperative behavior trajectory when the peripheral object is approaching.

[0076] Next, the save position and orientation generation process performed by the save position and orientation generation unit 601 will be described with reference to FIG. FIG. 8 is a flowchart illustrating an example of the evacuation position and orientation generation process.

[0077] First, the evacuation position and posture generation unit 601 acquires various information such as a retention risk map, cooperative action plan information, environmental information, lane information, map information, etc. (Step S801). Next, the evacuation position and posture generation unit 601 generates a target evacuation position and posture candidate in the current cooperative action step in the cooperative action plan (Step S802).

[0078] Next, the process of generating candidate target escape position and orientation in step S802 will be described with reference to FIG. FIG. 9 is a diagram illustrating an example of a process for generating a candidate target evacuation position and orientation. In the example of Fig. 9, an oncoming vehicle M2 with which the host vehicle M1 should take a coordinated action is present ahead of the host vehicle M1. Also, a waiting space is present ahead of the host vehicle M1 on the left side. In Fig. 9, a road boundary 741 is shown.

[0079] The stay risk map 701 generated by the stay risk map generating unit 309A (FIG. 3) exists in front of and on the vehicle M1. Therefore, in order to realize the cooperative behavior of passing each other, the vehicle M1 needs to move to a place where the stay risk map 701 does not exist and wait there. Therefore, the stay risk map generating unit 309A generates turn-off position and attitude candidates (N1, θ1) to (N5, θ5) in a turn-off space that is a surrounding drivable area (inside the road boundary 741) where the stay risk map 701 does not exist. N represents the planar position coordinate, and θ represents the head angle of the vehicle. For example, the head angle is the angle between the road direction and the vehicle. The number of turn-off position and attitude candidates generated at this time is arbitrary, but the place where the turn-off position and attitude candidates are generated is selected to be close to the stay risk map 701 within a range considering the size of the vehicle M1.

[0080] [Cooperative action trajectory generation processing] Next, the cooperative behavior basic trajectory generation process performed by the cooperative behavior basic trajectory generating unit 602 will be described with reference to the flowchart of FIG. FIG. 10 is a flowchart showing an example of a cooperative behavior basic trajectory generation process.

[0081] First, the cooperative behavior basic trajectory generating unit 602 acquires various information such as a stay risk map, cooperative behavior plan information, environmental information, lane information, map information, and surrounding object approach determination (step S1001). Next, the cooperative behavior basic trajectory generating unit 602 generates arrival position candidates which are arrival positions at which the traveling mode is changed from the cooperative behavior mode to another mode after passing the waiting position (step S1002). Thereafter, the cooperative behavior basic trajectory generating unit 602 generates a cooperative behavior trajectory candidate that passes through the turnaround position candidate and the arrival position candidate (step S1003).

[0082] Furthermore, the cooperative behavior basic trajectory generating unit 602 evaluates the generated cooperative behavior trajectory candidates and selects the optimal cooperative behavior trajectory (step S1004). In the present invention, the selected cooperative behavior trajectory is called a "cooperative behavior basic trajectory" and is used as a base for the cooperative behavior trajectory when approaching a peripheral object that is generated by the peripheral object approach trajectory generating unit 605.

[0083] Finally, the cooperative behavior basic trajectory generating unit 602 stores information on the cooperative behavior trajectory (cooperative behavior basic trajectory) selected in step S1004 in the storage unit 308 (the memory 212 in FIG. 2).

[0084] Here, the process of evaluating the generated cooperative behavior trajectory candidates in step S1004 and selecting the optimal cooperative behavior trajectory will be described below. In order to select the optimal cooperative behavior trajectory from the generated cooperative behavior trajectory candidates, it is possible to use, for example, the equation of [Mathematical formula 2] as a method of evaluating and calculating each cooperative behavior trajectory candidate. As described above, since cooperative behavior trajectory candidates are generated for each of the turnaround position candidates and arrival position candidates, it is necessary to select the optimal one from among these candidates. Therefore, for each cooperative behavior trajectory candidate, the following evaluation function is used to determine the overall evaluation value of each cooperative behavior trajectory candidate.

[0085]

number

[0086] In formula [2], a weighting coefficient (i) is set for each of the five individual evaluation values, and the sum of the products of the weighting coefficient (i) and the individual evaluation value (i) is calculated. The weighting coefficient is a value determined in advance according to the scene. The smaller the overall evaluation value, the more preferable the trajectory candidate is. The five individual evaluation values ​​are an evaluation of safety, an evaluation of convenience, an evaluation of ride comfort, an evaluation of discomfort, and an evaluation of the feeling of pressure from oncoming vehicles.

[0087] Regarding the evaluation of safety, it is evaluated whether a sufficient distance is secured to avoid contact or approach with surrounding objects while traveling on a passing route. For this purpose, a safety evaluation value is calculated using the distance to the surrounding objects and an apparent risk value (probability) not shown. For example, a method can be considered in which the inverse of the minimum distance between the road boundary and the route candidate or the value (probability) of a collision risk map not shown is used as the evaluation value. In this embodiment, the route is intended to be planar coordinate information, and the trajectory is intended to include time information in addition to route information.

[0088] Regarding the evaluation of convenience, when an oncoming vehicle is present, if cooperative action, in this case the action to pass each other, takes time, the oncoming vehicle will have to wait longer, which may cause distrust among the other vehicles and the occupants of the vehicle itself. Therefore, assuming that the speed of the vehicle itself is constant and does not depend on the length of the route, the evaluation value of convenience is calculated using the length of the evacuation route for the vehicle itself. For example, a method can be considered in which the length of the route on the entrance side (the route entering the waiting area) is used as the evaluation value.

[0089] The evaluation of ride comfort is based on whether the acceleration and jerk (time derivative of acceleration) occurring in the vehicle increase when the vehicle follows the evacuation route. For example, a route with a large lateral acceleration and a long time for which lateral acceleration occurs is considered to have a poor ride comfort. In addition, when the turning radius of the route is small, the larger the total turning angle, the less comfortable the ride is. Therefore, it is possible to use the value of (reciprocal of turning radius) x (total turning angle) as an evaluation index.

[0090] Regarding the evaluation of discomfort, it is considered that the occupants of the vehicle feel uncomfortable when they perform a passing maneuver that requires them to turn around, and an evaluation value is calculated using the number of times that the vehicle turns around.

[0091] Regarding the evaluation of the pressure on the oncoming vehicle, a route where the vehicle approaches too close to the oncoming vehicle may cause the occupants of the vehicle and the other vehicle to feel distrustful or scared. Therefore, an evaluation value is calculated based on the distance between the candidate cooperative behavior trajectory of the vehicle and the oncoming vehicle. For example, a method of using the reciprocal of the minimum distance between the candidate cooperative behavior trajectory and the center position coordinates of the other vehicle as the evaluation index can be considered.

[0092] [Generation of arrival position candidates] Next, a method for generating arrival position candidates in step S1002 will be described with reference to FIG. FIG. 11 is a diagram showing examples of arrival position candidates.

[0093] Here, the candidate arrival position is selected as a point where a transition from the cooperative behavior mode to another mode (e.g., lane keeping mode) is expected. In the example of Fig. 11, in a situation where a place where passing is possible (e.g., a turning-off space) is set by a road boundary 741, a position on the center line 1101 of the driving lane of the host vehicle M1 stored in the map information and line-symmetrical (a position where the length of L is equal in Fig. 11) between the start point of the emphasizing behavior mode and each turning-off position and attitude candidate point is set as the candidate arrival position.

[0094] [Generation of candidate cooperative action trajectories] Next, a method for generating cooperative behavior trajectory candidates in step S1003 will be described with reference to FIG. FIG. 12 is a diagram showing an example of a cooperative behavior trajectory (passing trajectory). In order to generate a cooperative behavior trajectory, a cooperative behavior target route is generated, and then a cooperative behavior target speed for traveling on the generated route is generated. As a process for generating a cooperative behavior target route, for example, a method of generating arcs, straight lines, and clothoid curves for the target evacuation position and posture candidates and arrival position candidates using the above-mentioned retention risk map and evacuation position and posture candidates can be considered.

[0095] Fig. 12 shows the result of generating a target route for the host vehicle M1 from the current position to the waiting position using straight lines and circular arc curves. In the example of Fig. 12, the route for the host vehicle M1 from the current position to the waiting position is a straight line that is approximately parallel to the center line 1101 until the road boundary 741 is linear and the waiting position begins. After that, at the point where the road boundary 741 deforms to the outside of the road, the route is a curved route using a circular arc curve toward the waiting position (N3, θ3). Then, after the host vehicle M1 passes the oncoming vehicle M2, the route returns to the center line 1101.

[0096] Next, the congestion risk map and cooperative behavior trajectory when there is an oncoming vehicle ahead of the host vehicle will be explained using the schematic diagram of a typical scene shown in FIG. 13. FIG. 13 shows an example of a typical scene of a congestion risk map and a cooperative behavior trajectory when an oncoming vehicle M2 is present ahead of the host vehicle M1. Here, as shown in the upper part of Fig. 13, the host vehicle M1 and the oncoming vehicle M2, which is a target of cooperative behavior, are traveling on either side of a passing point. There is a waiting area on the left side of the host vehicle M1. Also, a retention risk map 701 calculated based on the surrounding environment and the arrangement of the oncoming vehicle M2 is acquired. In such a situation, as shown in the lower part of Fig. 13, a waiting position 702 for the host vehicle M1, a trajectory 704 from the current position to the waiting position 702, and a trajectory 705 from the waiting position 702 to a candidate arrival position 703 are calculated based on the trajectory risk map 701.

[0097] [When vehicle occupants feel anxious or scared] Next, with reference to FIG. 14, a case will be described in which an occupant of the vehicle may feel uneasy or scared due to an oncoming vehicle or the surrounding environment when traveling along the above-mentioned cooperative behavior trajectory (following the planned cooperative behavior trajectory). FIG. 14 is a diagram showing an example in which a passenger in the host vehicle feels anxiety or fear when traveling along a cooperative behavior trajectory. Here, as shown in the upper part of Fig. 14, the host vehicle M1 is trying to realize cooperative behavior by following trajectories 704 and 705 on the cooperative behavior trajectory. In the middle of the behavior process, the oncoming vehicle M2, which is a cooperative behavior target that was located far away when the cooperative behavior trajectory was planned, approaches the host vehicle M1. The oncoming vehicle M2 will not collide with the host vehicle M1, and even if the host vehicle M1 evacuates to the evacuating position 702, it will not hinder the oncoming vehicle M2 from passing each other.

[0098] The vehicle control device 1 of the present embodiment plans a waiting position and a trajectory to the waiting position in order to reduce the fear of the occupants when the host vehicle M1 is waiting in a safe and secure state, even if the host vehicle M1 is in a state where passing can be realized without impeding the traveling of the oncoming vehicle M2. It is therefore desirable to wait in a safe and secure state, so as not to give the occupants a sense of anxiety.

[0099] For this purpose, in this embodiment, when a surrounding object is approached as shown in Figure 7, a steering limit setting unit 603 for when a surrounding object is approached, a turnaround position generating unit 604 for when a surrounding object is approached, and a trajectory generating unit 605 for when a surrounding object is approached generate a trajectory for when a surrounding object is approached.

[0100] 14, a waiting position 1401 for the host vehicle M1, a trajectory 1402 from the current position to the waiting position 1401, and a trajectory 1403 from the waiting position 1401 to a destination position candidate 703 are calculated. The waiting position 1401 is farther away from the oncoming vehicle M2 during passing than the initial waiting position 702. Also, at the waiting position 702 in the upper part of FIG. 14, the host vehicle M1 was parallel to the road (head angle = 0 degrees), but the posture of the host vehicle M1 that has reached the waiting position 1401 is not parallel but oblique to the road and the oncoming vehicle M2 (head angle ≠ 0 degrees).

[0101] [Steering limit setting process when approaching nearby objects] Next, the steering limit setting process when the vehicle is approaching a nearby object performed by the nearby object approach steering limit setting unit 603 will be described with reference to FIG. FIG. 15 is a flowchart showing an example of a steering limit setting process when approaching a nearby object.

[0102] First, the peripheral object approach steering restriction setting unit 603 acquires various information such as a retention risk map, cooperative action plan information, environmental information, lane information, map information, and peripheral object approach determination (step S1501).

[0103] Next, when approaching a peripheral object, the peripheral object approach steering limit setting unit 603 calculates (step S1502) a target yaw angle (yaw angle profile) of the vehicle 100 when tracking the target cooperative behavior trajectory (cooperative behavior basic trajectory) calculated by the cooperative behavior basic trajectory generating unit 602. Specifically, the target yaw angle of the vehicle 100 can be calculated from the tangential direction of the cooperative behavior basic trajectory.

[0104] Next, the peripheral object approach steering limit setting unit 603 calculates the relative yaw angle between the host vehicle M1 and the oncoming vehicle M2 based on the predicted trajectory of the oncoming vehicle and the target yaw angle calculated in step S1502. The relative yaw angle is the angle between the traveling direction of the host vehicle M1 and the traveling direction of the oncoming vehicle M2. The peripheral object approach steering limit setting unit 603 also calculates the relative yaw angle change rate using the time series prediction result of the relative yaw angle (step S1503).

[0105] Next, the peripheral object approach steering limit setting unit 603 calculates the steering limit angle based on the traveling speed of the vehicle and the cooperative action trajectory (step S1504). The peripheral object approach steering limit setting unit 603 calculates the position on the cooperative action trajectory where the relative yaw angle change rate is equal to or greater than a predetermined value. For example, it is desirable to limit the upper limit of the yaw angle change rate to about 1.0 [rad / sec] or less, taking into account the ride comfort and fear.

[0106] In addition, by setting the allowable range in the direction in which the relative yaw angle is constant or increases, the steering limit can prevent the approach of the oncoming vehicle M2 due to rotation in the yaw angle direction, thereby reducing the sense of fear. If the relative yaw angle is set to be greater than zero, the host vehicle moves in a direction away from the oncoming vehicle.

[0107] Moreover, the peripheral object approaching steering limit setting unit 603 (an example of a steering limit setting unit) may set the magnitude of the relative yaw angle or the allowable range of the change amount of the relative yaw angle instead of the relative yaw angle change rate. Even with such settings, the same effect as above can be obtained. When the peripheral object approach determining unit 508 determines that a moving object is approaching the host vehicle, the peripheral object approaching trajectory generating unit 605 (an example of a trajectory planning unit) generates (plans) a trajectory related to the movement of the host vehicle so that the relative yaw angle after the host vehicle moves or the amount of change in the relative yaw angle accompanying the movement of the host vehicle falls within the allowable range.

[0108] [Processing for generating evacuation positions when surrounding objects approach] Next, the process of generating a retreat position when a surrounding object is approached by the retreat position generating unit 604 will be described with reference to FIG. FIG. 16 is a flowchart showing an example of a process for generating a retreat position when a surrounding object approaches.

[0109] First, the surrounding object approach time evacuation position generating unit 604 acquires various information such as a stay risk map, cooperative action plan information, environmental information, lane information, map information, and surrounding object approach determination (step S1601).

[0110] Next, when the vehicle M1 approaches a peripheral object, the peripheral object approach time turning-off position generating unit 604 generates a turning-off position for the vehicle M1 when the vehicle M1 approaches a peripheral object (step S1602). In this embodiment, the turning-off position when the vehicle M1 approaches a peripheral object is generated at a position that satisfies the steering limit calculated by the peripheral object approach time steering limit setting unit 603 and is not on the retention risk map 701.

[0111] Finally, the peripheral object approaching waiting position generating unit 604 stores the generated peripheral object approaching waiting position information in the storage unit 308 (step S1603). In this way, when the host vehicle M1 is approaching the oncoming vehicle M2 and waiting, it is considered that the anxiety of the occupants can be reduced by making the host vehicle M1 wait at a position that does not interfere with the oncoming vehicle M2 passing by and where the rate of change of the relative yaw angle between the host vehicle M1 and the oncoming vehicle M2 is equal to or less than a predetermined value.

[0112] [Cooperative action trajectory generation process when approaching surrounding objects] Next, the process of generating an avoidance trajectory when a peripheral object is approaching, performed by the peripheral object approaching trajectory generating unit 605, will be described with reference to FIG. FIG. 17 is a flowchart showing an example of a process for generating an avoidance trajectory when a peripheral object approaches.

[0113] First, the peripheral object approaching trajectory generating unit 605 acquires various information such as a stay risk map, cooperative action plan information, environmental information, lane information, map information, and peripheral object approaching determination (step S1701).

[0114] Next, the peripheral object approach time trajectory generation unit 605 generates a candidate for a turnaround trajectory (cooperative behavior trajectory) when approaching a peripheral object, which leads to a turnaround position when approaching a peripheral object (step S1702). This turnaround position when approaching a peripheral object is the turnaround position generated by the peripheral object approach time trajectory generation unit 604. The turnaround trajectory that leads to the turnaround position when approaching a peripheral object may be created using a straight line, a circular arc curve, or the like, as shown in Fig. 12. A plurality of such trajectories may be generated by combining forward and backward movements.

[0115] Therefore, the peripheral object approach time trajectory generation unit 605 evaluates multiple avoidance trajectory (cooperative behavior trajectory) candidates, and selects the optimal cooperative behavior trajectory candidate when approaching the peripheral object from the result (step S1703). As a method for this, the method described in step S1004 of FIG. 10 can be considered.

[0116] Finally, the peripheral object approaching trajectory generation unit 605 stores in the storage unit 308 the avoidance trajectory (cooperative behavior trajectory) when the peripheral object is approaching selected in step S1703.

[0117] [Configuration of the driving mode management unit] Next, the driving mode management unit 509 (FIG. 6) will be described with reference to FIG. FIG. 18 is a block diagram showing an example of the configuration of the driving mode management unit 509.

[0118] Various information such as a target driving mode, a manual driving request, and system information is supplied to the driving mode management unit 509. The system information is, for example, information on the power switch of the vehicle 100 and information on the automatic driving switch of the automatic driving system.

[0119] 18, the driving mode management unit 509 manages three states: a manual driving mode 1801, a system off mode 1802 of the automatic driving system, and an automatic driving mode 1803. The driving mode management unit 509 outputs the current mode state as a current driving mode.

[0120] When the power switch of the vehicle 100 is turned on (an example of UI information in FIG. 6), the driving mode management unit 509 transitions from the system off mode 1802 to the manual driving mode 1801 or the like. In addition, the driving mode management unit 509 transitions from the manual driving mode 1801 or the like to the automatic driving mode 1803 when the driver or the like turns on the automatic driving switch (an example of UI information in FIG. 6).

[0121] As already explained, the automatic driving mode 1803 includes lane keep (LK) and lane change (LC). In addition, intermediate transition states exist between these states. In addition, in the cooperative behavior mode (CO), a deadlock or an event that requires a change of driving to the driver may occur, and the automatic driving system may determine that it is necessary to take over driving (give up). In such a case, the cooperative behavior trajectory selection unit 606 (FIG. 7) issues a manual driving request, and the automatic driving mode transitions to the manual driving mode 1801.

[0122] [Steering angle control when approaching surrounding objects] Next, the control of the steering angle when approaching a surrounding object will be described with reference to FIG. Fig. 19 is a diagram showing an example of steering angle control when approaching a surrounding object. In Fig. 19, the horizontal axis represents time and the vertical axis represents steering angle. Conventional steering angle control is shown by a dashed line, and steering angle control of the present invention is shown by a solid line.

[0123] As a result of controlling the steering angle according to the above embodiment, when a peripheral object approach determination is made, as shown in FIG. 19, the actual steering angle is controlled to be within the steering limit value before the host vehicle M1 moves to the waiting position. In the lower part of FIG. 14, since the operation amount of the steering angle in the negative direction is small, the posture of the host vehicle M1 that has reached the waiting position 1401 is oblique to the road and the oncoming vehicle M2. By controlling in this way, the relative yaw angle between the host vehicle M1 and the oncoming vehicle M2 is limited, making it possible to prevent the occupants from feeling scared. Conventionally, the magnitude of the actual steering angle has greatly exceeded the steering limit value, making the occupants prone to feeling scared.

[0124] According to this embodiment, when the vehicle is traveling in cooperation with a nearby moving object, a trajectory for the movement of the vehicle can be planned so as to reduce the discomfort and fear of the occupants due to the approach of the moving object. For example, in this embodiment, when it is estimated that the vehicle approaches a surrounding object (oncoming vehicle) during automatic passing driving and the occupants feel fear, it is possible to plan a trajectory when the vehicle approaches the surrounding object, taking into account the detection information of various sensors and the behavior of the vehicle and the surrounding object. In addition, for example, it is expected to reduce the sense of distrust and anxiety felt by the drivers of the vehicle and the oncoming vehicle, and to suppress the reduction in the passenger's riding time.

[0125] <Second embodiment> Next, a vehicle control device according to a second embodiment of the present invention will be described with reference to FIG.

[0126] [Processing to determine the proximity of surrounding objects] FIG. 20 is a diagram showing an example of a peripheral object approach determination process performed by the peripheral object approach determination unit 508 of the vehicle control device according to the second embodiment.

[0127] The vehicle control device of this embodiment is different from the vehicle control device 1 of the first embodiment in the method of determining the approach of a peripheral object. As shown in Fig. 20, a peripheral object approach determination unit 508 uses not only the distance information (distance determination) to an oncoming vehicle described in the first embodiment, but also the time to collision (TTC) and the rate of change of the time to collision (ΔTTC) in determining the approach of a peripheral object such as another vehicle.

[0128] The peripheral object approach determination unit 508 calculates the logical sum of the distance determination, the TTC determination, or the ΔTTC determination by a logical sum circuit, and outputs a peripheral object approach determination (approaching) if any one of them is determined to be approaching.

[0129] The peripheral object approach determination unit 508 may perform the approach determination using at least one of the time to collision (TTC) between the moving object and the host vehicle or the rate of change of the time to collision (ΔTTC).

[0130] In this embodiment, a method for determining approach using TTC will be described with reference to the explanatory diagram of FIG. FIG. 21 is a diagram showing an example of the vehicle movement, the time to collision (TTC), and the threshold value in the vehicle control device according to the present embodiment.

[0131] The upper part of FIG. 21 shows the distance from the host vehicle M1 to the oncoming vehicle M2 from time T=T0 to T=T2 when the host vehicle M1 and the oncoming vehicle M2 pass each other, expressed as TTC. The lower part of FIG. 21 shows the results of calculating the TTC of the host vehicle M1 and the oncoming vehicle M2 at each time. In this passing scene, the TTC becomes smaller as time passes when the host vehicle M1 evacuates to the evacuation road. Then, at time T2, the calculated TTC becomes smaller than the threshold value set in advance. It is determined that the host vehicle is approaching another vehicle by judging this inequality.

[0132] In addition, in FIG. 21, ΔTTC is constant (ΔTTC=0), but if ΔTTC is not linear, the threshold value may be adjusted based on the determination of ΔTTC.

[0133] In addition, by using ΔTTC, it is possible to determine whether the TTC with an oncoming vehicle is increasing or decreasing over time.

[0134] Fig. 22 is a diagram showing an example of the relationship between the collision time and the threshold when the differential value (ΔTTC) of the collision time is positive and negative. The upper part of Fig. 22 shows a graph when ΔTTC is positive, and the lower part of Fig. 22 shows a graph when ΔTTC is negative.

[0135] The upper part of FIG. 22 shows an example where ΔTTC increases (positive rate of change) and TTC also increases from a certain point (a convex-downward function). When TTC is close to the threshold value, there is a possibility that TTC may fall below the threshold value due to noise or the like. However, if ΔTTC has a positive trend (increasing), it is expected that TTC will increase with the passage of time (after time T1 in the figure). In this case, even if TTC exceeds the threshold value, it is not necessary to immediately determine an approach, and it is expected that the discrepancy with the driver's sense of fear can be avoided compared to the case where the determination is made only based on TTC.

[0136] Also, when ΔTTC has a positive trend (increasing), it is possible to lower the threshold value of TTC. When ΔTTC is positive, since the risk of collision is lower than when the determination is made only based on TTC and TTC increases with the passage of time, it is considered that the driver's sense of fear will not increase significantly. In the upper part of FIG. 12, an example of lowering the threshold value of TTC from "Th1" to "Th2" is shown. As a result, although TTC < Th1 at time T1, it changes to TTC > Th2 at time T1.

[0137] The lower part of FIG. 22 shows an example where ΔTTC decreases (negative rate of change). When ΔTTC has a negative trend (decreasing), since the approach of the host vehicle and the oncoming vehicle is increasing, it is considered that the driver's sense of fear will increase compared to when the determination is made only based on the threshold value of TTC. As a countermeasure, when ΔTTC has a negative trend, it is considered to increase the threshold value of TTC. Thereby, it is possible to detect the sudden approach to the oncoming vehicle in advance and expect an effect of alleviating the driver's sense of fear.

[0138] In the lower part of FIG. 12, an example of increasing the threshold value of TTC from "Th1" to "Th3" is shown. As a result, although TTC > Th1 at time T2, it becomes TTC < Th3 at time T1, and it becomes possible to detect the sudden approach to the oncoming vehicle earlier (advanced to time T1 from time T2).

[0139] <The Third Embodiment> Next, with reference to FIG. 23, a vehicle control device according to the third embodiment of the present invention will be described. Fig. 23 is a diagram showing an example of the movement of a vehicle and the visual field of an occupant in a vehicle control device according to the third embodiment. Fig. 23A shows an example of the evacuation behavior of the host vehicle when passing another vehicle, and Fig. 23B shows an example of the change in the visual field of the occupant accompanying the movement of the vehicle.

[0140] The basic configuration of the vehicle control device according to this embodiment is the same as that of the vehicle control device according to embodiment 1. The vehicle control device according to this embodiment predicts the visual field state of the occupants at the future position and the behavior of other vehicles while performing cooperative behavior, and generates an avoidance trajectory (cooperative behavior trajectory) when other vehicles approach.

[0141] FIG. 23A shows an example in which the host vehicle M1 moves to a waiting position 702 in a waiting space by following a trajectory 704 based on a cooperative action trajectory for an oncoming vehicle M2. The host vehicle M1 reaches a position and attitude 2300 at a certain point while traveling on the trajectory 704. When there is an occupant in the rear seat of the host vehicle M1, the field of view, particularly in front of the vehicle, is limited, and the occupant grasps the state outside the vehicle from windows on the left and right of the rear seat. It is difficult for this occupant to grasp the state outside the vehicle by any means other than the windows on the left and right of the rear seat. A field of view 1601 shows the field of view from the right window of the occupant in the rear seat.

[0142] 23B, when the host vehicle M1 and the oncoming vehicle M2 start passing each other, the oncoming vehicle M2 approaching from the right front of the host vehicle M1 enters the field of view 1601 from the right window of the passenger in the back seat (left side of FIG. 23B). Then, when the host vehicle M1 transitions to the position and attitude 2300 during the passing behavior and the oncoming vehicle M2 approaches the right side of the host vehicle M1, it is considered that the oncoming vehicle M2 occupies most of the field of view 1601 from the right window of the passenger in the back seat (right side of FIG. 23B).

[0143] In this state, it is considered that control is performed to return the yaw angle so that the host vehicle M1 moves toward the waiting position 702. Since the information obtained from the occupant's field of view 1601 is limited, the occupant obtains various information such as ride comfort from the acceleration and jerk caused by the change in the yaw angle of the host vehicle M1. As a result of the change in the yaw angle of the host vehicle, acceleration (centrifugal force) is generated in the vehicle including the occupant. In addition, as a result of the change in acceleration, jerk occurs, and it is considered that the occupant predicts the direction and movement of the (automatically driven) host vehicle from the acceleration and jerk information.

[0144] When an occupant tries to understand the condition of another vehicle (here, an oncoming vehicle M2) from information obtained from the acceleration and jerk caused by changes in the yaw angle of the vehicle M1, the sensation that the vehicle M1 is approaching the other vehicle and that there is a risk of a collision may become more pronounced.

[0145] Therefore, in a situation where there is an occupant with a restricted field of view and an oncoming vehicle M2 is approaching, the occupant is likely to feel more fear. Therefore, when another vehicle is approaching, the field of view restriction determination is used to limit the yaw angle change before the occupant feels fear, thereby making it possible to alleviate the occupant's sense of fear.

[0146] [Processing to determine the proximity of surrounding objects] FIG. 24 is a diagram showing an example of a peripheral object approach determination process performed by the peripheral object approach determination unit 508 of the vehicle control device according to the third embodiment. In the peripheral object approach determination unit 508 of this embodiment, in the peripheral object approach determination, not only the information shown in the second embodiment (FIG. 20) but also a view restriction determination is used. Note that, although an example in which the peripheral object approach determination unit 508 executes the view restriction determination process will be described, a view restriction determination unit (an example of an occupant state estimation unit) (not shown) may be provided in the automatic driving planning unit 501, and a determination result may be input to the peripheral object approach determination unit 508.

[0147] Next, the view restriction determination process performed by the peripheral object approach determination unit 508 will be described with reference to FIG. FIG. 25 is a flowchart showing an example of a process for generating an avoidance trajectory when a peripheral object approaches.

[0148] First, the peripheral object approach determination unit 508 acquires detection information from external sensors such as the camera, the radar 301, the stereo camera 302, and the lidar 304 (step S2501). The peripheral object approach determination unit 508 may acquire various information such as a stay risk map, cooperative action plan information, environmental information, lane information, map information, and peripheral object approach determination.

[0149] Next, the peripheral object approach determination unit 508 performs numerical modeling of the surrounding environment of the vehicle to generate a numerical model (step S2502). In order to numerically model the surrounding environment, it is desirable to model the vehicle, oncoming vehicles, surrounding road environment, etc. while maintaining their three-dimensional shapes. In addition, it is desirable to use a motion model suitable for moving objects (for example, if the vehicle is a motorcycle, a two-wheel model, etc.).

[0150] Next, the peripheral object approach determination unit 508 uses the above numerical model to predict the occupant's future visual field state on the cooperative behavior trajectory. Based on the target trajectories of the oncoming vehicle and the vehicle itself, the position and attitude of each vehicle are estimated, and the occupant's visual field state when passing an oncoming vehicle is predicted.

[0151] Finally, the peripheral object approach determination unit 508 determines whether the host vehicle and other vehicles will move in a state in which the occupant's field of view is restricted (step S2504). The result of the field of view restriction determination is input to a logical sum circuit of the peripheral object approach determination unit 508 shown in Fig. 24. Information on the field of view restriction determination may be input to the peripheral object approach determination unit 508 only when the field of view restriction determination is "true".

[0152] In this manner, in this embodiment, the vehicle may further include an occupant state estimation unit that estimates the occupancy of a moving object (e.g., an oncoming vehicle) relative to the visual field of an occupant of the vehicle. When the occupancy of the moving object exceeds a threshold, the cooperative behavior trajectory generation unit 505 (an example of a trajectory planning unit) generates (plans) a trajectory related to the movement of the vehicle so that the relative yaw angle or the amount of change in the relative yaw angle is within an allowable range (see the description of FIG. 15).

[0153] [Example of no yaw angle change rate limit] On the other hand, when the occupant's field of vision is not restricted, when the occupant is not awake, when the occupant is looking ahead of the vehicle, etc., a relative yaw angle with the oncoming vehicle closer to zero (180 degrees) may be less likely to cause fear. In such cases, the yaw angle change rate restriction described in step S1503 of Fig. 15 is not performed. When passing an oncoming vehicle, the relative yaw angle with the oncoming vehicle being close to zero (180 degrees) can be rephrased as the oncoming vehicle and the vehicle being passed by each other while being parallel to each other.

[0154] Also, when it is difficult to change the waiting position, i.e. when it is difficult to generate a route that satisfies the steering restriction, it is desirable for the peripheral object approaching trajectory generating unit 605 to reduce the target speed of the host vehicle. By reducing the target speed of the vehicle, even if the yaw angle change of the host vehicle is moving in a direction approaching an oncoming vehicle, it is expected that the yaw angle change rate due to the speed reduction will decrease, which is expected to have the effect of reducing the fear of the occupants.

[0155] In addition, when it is determined that an oncoming vehicle is approaching, it is desirable for the peripheral object approach determination unit 508 (automatic driving planning unit 501) to notify a user interface (one example of an output device) such as a display for a navigation system of the vehicle that an oncoming vehicle is approaching. For example, the display device 24 (FIG. 1) can be used as the user interface.

[0156] By providing such a notification, the occupant's attention and awareness of the surroundings can be increased. This may lead to the occupant being aware of the restricted field of view and to changing his / her line of sight and posture in a direction that alleviates the restriction of the field of view. As a result, the occupant's sense of fear may be alleviated.

[0157] It is also desirable to have an in-vehicle voice notification system (one example of an output device) that can be heard inside the vehicle, in addition to visual information such as on a display. In a situation where the field of vision is limited, notifying occupants of an approaching vehicle by voice is considered to be effective in mitigating the fear felt by occupants.

[0158] In cooperative behavior (passing other vehicles) when the occupants' field of vision is restricted, by generating a passing trajectory that takes into account the field of vision restrictions at the vehicle's future position, the occupants will no longer be uncomfortable or feel anxious or scared due to approaching an oncoming vehicle during the passing maneuver.

[0159] <Fourth embodiment> Next, a vehicle control device according to a fourth embodiment of the present invention will be described with reference to FIG. FIG. 26 is a diagram showing an example of approach determination processing by the peripheral object approach determiner 508 of the vehicle control device according to the fourth embodiment.

[0160] In the peripheral object approach determination unit 508 of this embodiment, in determining the approach of a peripheral object, not only the information shown in the third embodiment (FIG. 24) but also a fear determination is used. The vehicle control device generates an avoidance trajectory (cooperative behavior trajectory) when another vehicle approaches by determining the fear based on the result of estimating the fear of the occupants at the future position of the vehicle while performing cooperative behavior.

[0161] Methods for estimating the occupant's sense of fear include using an occupant state detection system such as an occupant state estimation camera (gaze camera) installed in the vehicle cabin or a wearable sensor worn by the occupant.

[0162] For example, when the surrounding object approach determination unit 508 determines that an oncoming vehicle is approaching, it estimates the sense of fear of the occupants of the vehicle while passing the oncoming vehicle based on the detection results of a camera that detects the line of sight information of the occupants of the vehicle.

[0163] In addition, the surrounding object approach determination unit 508 acquires biometric information such as heart rate and amount of sweat detected by the occupant condition detection system, and estimates the occupant's sense of fear while passing an oncoming vehicle based on the biometric information.

[0164] When the value of the index representing the occupant's sense of fear based on the gaze information or biological information becomes equal to or greater than a predetermined value, the peripheral object approach determination unit 508 determines that the occupant is feeling a sense of fear and sets the sense of fear determination as "true." In this way, by estimating the sense of fear using a sensor that detects the state of the occupant, the cooperative behavior trajectory is changed when an oncoming vehicle approaches, which leads to a reduction in the occupant's sense of anxiety.

[0165] The present invention is not limited to the above-described embodiment, and various other applications and modifications are possible without departing from the gist of the present invention described in the claims. For example, the above-described embodiment is a detailed and specific description of the configuration in order to easily explain the present invention, and is not necessarily limited to the configuration including all of the components described. In addition, it is also possible to add, replace, or delete other components to a part of the configuration of each embodiment.

[0166] For example, the passing action described in Figure 5 etc. is an example of moving the vehicle to the left side of the road to pass another vehicle in areas where vehicles drive on the left side of the road. In areas where vehicles drive on the right side of the road, the left and right directions when passing another vehicle are reversed.

[0167] In each of the above-mentioned embodiments, a driving trajectory (cooperative behavior trajectory) is generated (calculated) and the vehicle is made to drive automatically along the driving trajectory. Generally, a driving trajectory includes information on a coordinate position on a road and the time when the vehicle passes through the coordinate position, and in the present invention, driving is controlled based on the information on the coordinate position and the time. In contrast to this, the travel trajectory may be information on a so-called travel route that does not have information on the time when the vehicle passes each coordinate position, but only has information on the coordinate positions on the road. In passing each other, it is preferable to determine the position to which the vehicle will move at each time while predicting the position of the oncoming vehicle at each time, but in a situation where the oncoming vehicle is stopped, a travel route that only has information on the coordinate positions may be generated instead of the travel trajectory. By generating a travel route in this manner, it is not necessary to handle time information, and the travel trajectory (travel route) can be generated more easily.

[0168] In addition, in the configuration shown in FIG. 2, the vehicle control device 1 configured as a computer is configured as a device that performs the processing of each of the above-mentioned embodiments, but a program implemented in an existing vehicle control device 1 may be modified to perform similar processing. In this case, the program may be prepared in the memory within the computer shown in FIG. 2, or may be stored in an external memory, an IC card, an SD card, an optical disk, or other recording medium and transferred. Furthermore, a part or the whole of the vehicle control device 1 may be realized by dedicated hardware such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC).

[0169] In the above-described embodiment, the control lines and information lines of the vehicle control device and each processing function unit are those considered necessary for explanation, and not all control lines and information lines are necessarily shown in the product. In reality, it may be considered that almost all components are connected to each other. In addition, as for the flowcharts shown in Figures 4, 8, 10, 15 to 17, and 25, the processing order may be changed or multiple processes may be executed simultaneously as long as the processing results are the same.

[0170] In addition, although the term "parallel" is used in this specification, this term does not mean only "parallel" in the strict sense, but also includes the meaning of "parallel" in the strict sense and further includes the meaning of "approximately parallel" within the range in which the function can be exerted. [Explanation of symbols]

[0171] 1...vehicle control device, 100...vehicle, 201...automatic driving planning unit, 202...automatic parking planning unit, 203...vehicle motion control unit, 204...actuator control unit, 205...risk map generation unit, 301...radar, 302...stereo camera, 303...vehicle sensor, 304...lidar, 305...sensor information processing unit, 306...map information processing unit, 307...solid object behavior prediction unit, 308...memory unit, 309A...stay risk map generation unit, 309B...fixed obstacle risk map generation unit, 309C...moving obstacle risk map generation unit, 310...self-position estimation processing unit, 501...driving planning unit, 501...automatic driving planning unit, 502...lane keeping trajectory generation unit, 503...lane change trajectory generation unit, 504...obstacle avoidance trajectory generation unit, 505...cooperative behavior trajectory generation unit, 506... trajectory arbitration unit, 507... trajectory planning unit, 508... peripheral object approach determination unit, 509... driving mode management unit, 600... cooperative behavior state management unit, 601... turnaround position and attitude generation unit, 602... cooperative behavior basic trajectory generation unit, 603... peripheral object approach steering limit setting unit, 604... peripheral object approach turnaround position generation unit, 605... peripheral object approach trajectory generation unit, 606... cooperative behavior trajectory selection unit

Claims

1. an approach determination unit that determines an approach of a moving object to the host vehicle; a steering limit setting unit that sets a relative yaw angle, which is an angle between a traveling direction of the host vehicle and a traveling direction of the moving body, or a tolerance range of a relative yaw angle change amount; and a trajectory planning unit that plans a trajectory related to the movement of the host vehicle so that, when the approach determination unit determines that the moving object approaches the host vehicle, the relative yaw angle after the movement of the host vehicle or the amount of change in the relative yaw angle associated with the movement of the host vehicle falls within the allowable range. Vehicle control device.

2. The steering limit setting unit sets the permissible range in a direction in which the relative yaw angle is constant or increases. The vehicle control device according to claim 1.

3. The trajectory planning unit plans a trajectory for movement of the host vehicle to a waiting space at a waiting position where the host vehicle and the moving body pass each other. The vehicle control device according to claim 1.

4. The approach determination unit performs the approach determination using at least one of a collision time between the moving object and the host vehicle and a rate of change of the collision time. The vehicle control device according to claim 1.

5. An occupant state estimation unit that estimates an occupancy rate of the moving object relative to a visual field area of ​​an occupant of the vehicle, The trajectory planning unit plans a trajectory related to the movement of the host vehicle such that the relative yaw angle or the amount of change in the relative yaw angle falls within the allowable range when the occupancy rate of the moving object exceeds a threshold value. The vehicle control device according to claim 1.

6. When the approach determination unit determines that the moving object is approaching, the approach determination unit notifies an output device of the host vehicle that the moving object is approaching. The vehicle control device according to claim 1.

7. When determining that the moving object is approaching, the approach determination unit estimates a sense of fear of the occupant of the vehicle while passing the moving object based on a detection result of a camera that detects line-of-sight information of the occupant, and performs an approach determination of the moving object based on the estimated sense of fear. The vehicle control device according to claim 1.

8. When determining that the moving object is approaching, the approach determination unit estimates a sense of fear of the occupant of the vehicle while passing the moving object based on a detection result of a sensor that detects biological information of the occupant, and performs an approach determination of the moving object based on the estimated sense of fear. The vehicle control device according to claim 1.

9. When it is determined that it is difficult to change the evacuation position, the trajectory planning unit reduces the target speed of the host vehicle. The vehicle control device according to claim 3.

10. A vehicle control method by a vehicle control device that controls vehicle running, A determination process for determining whether a moving object is approaching the host vehicle; A setting process for setting a relative yaw angle, which is an angle between a traveling direction of the host vehicle and a traveling direction of the moving body, or a permissible range of a relative yaw angle change amount; and a planning process for planning a trajectory related to the movement of the host vehicle so that, when it is determined by the determination process that the moving object approaches the host vehicle, the relative yaw angle after the movement of the host vehicle or the amount of change in the relative yaw angle associated with the movement of the host vehicle is within the allowable range. A vehicle control method.

Images