Behavior planning device, vehicle control system, and behavior plan generation method

Abstract

To provide an action plan device, a vehicle control system, and an action plan generation method for stopping in an area where impact on other traffic participants is low, without obstructing the progression of the other traffic participants, when abnormality occurs to a detector that recognizes the ambient environment of the host vehicle.SOLUTION: The action plan device comprises: an emergency stoppage request unit that detects abnormality on the basis of obstruct information acquired from an obstruct information acquisition unit and a roadside information acquisition unit and outputs an emergency stoppage request; a stop position determination unit that computes the stop position of the host device on the basis of the emergency stoppage request and determines whether or not being in an area where the progression of other traffic participants is obstructed; and an action plan generation unit that, when it is determined that the host device is going to stop in an area such as an intersection where it hinders the progression of other traffic participants, generates an action plan that encourages stopping outside of the area or passing through the area before stopping.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present application relates to a behavior planning device, a vehicle control system, and a behavior plan generating method. [Background technology]

[0002] In recent years, there has been active development of autonomous driving technology for automobiles, and in addition to providing driving assistance to users, technologies that can drive autonomously without user intervention are attracting attention.When autonomous driving occurs, if an event occurs that makes it impossible to drive safely, such as a failure of one of the sensors that detects the vehicle's surrounding environment, the vehicle is required to stop in a situation where it does not interfere with other traffic participants and the risk of an accident is low.

[0003] For example, in Patent Document 1, when an abnormality is detected in an external environment recognition device that recognizes the surrounding environment of the vehicle, a process is executed to stop the vehicle. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2022-24741 Summary of the Invention [Problem to be solved by the invention]

[0005] In Patent Document 1, if an abnormality occurs in the external recognition system for recognizing the surrounding environment of the vehicle, a trajectory for the vehicle to stop is generated based on a Minimum Risk Maneuver (MRM). However, there is a possibility that the vehicle may stop in an area where roads intersect, such as an intersection. If the vehicle stops in an intersection, it may obstruct the progress of other traffic participants or may result in a collision between the vehicle and other traffic participants. This is because an intersection is an area where roads intersect, and the vehicle has a significant impact on other traffic participants. Furthermore, even if the vehicle stops on the shoulder of a road outside the intersection, it may obstruct the passage of other traffic participants attempting to pass through a road connected to the shoulder or a parking entrance / exit. These are issues that arise when considering the advancement of automated driving.

[0006] The present application discloses technology for solving the above-mentioned problems, and aims to provide a behavior planning device, a vehicle control system, and a behavior plan generation method that, when an abnormality occurs in a detector (sensor) that recognizes the surrounding environment of a vehicle, will stop the vehicle in an area that will not hinder the progress of other traffic participants and will have a low impact on other traffic participants. [Means for solving the problem]

[0007] The behavior planning device disclosed in the present application comprises: detected by at least one sensor; Obstacle information around the moving object acquired by the obstacle information acquisition unit; position information of the moving object acquired by a self-position acquisition unit; Road information around the moving object acquired by a road information acquisition unit, and An action planning device to which obstacle information around a roadside area acquired by a roadside information acquisition unit is input, an emergency stop request unit that outputs an emergency stop request when an abnormality is detected in at least one of the obstacle information around the moving object acquired by the obstacle information acquisition unit and the obstacle information around the roadside acquired by the roadside information acquisition unit; a stop position determination unit that determines whether the moving object will stop within a first area that would hinder the progress of other traffic participants when the moving object stops, based on the road information, the position information of the moving object, and the emergency stop request output from the emergency stop request unit; and and a behavior plan generation unit that generates a behavior plan for preventing the moving body from stopping in the first area when the stop position determination unit determines that the moving body will stop in the first area, which would hinder the progress of other traffic participants. 、 The action plan generation unit a candidate route generating unit that generates at least one candidate route along which the mobile object will travel based on the road information and the position information of the mobile object; a route travel difficulty calculation unit that calculates a travel difficulty level for the mobile body when traveling along each of the candidate routes generated by the candidate route generation unit, based on whether the obstacle information acquired by the obstacle information acquisition unit, the obstacle information around the roadside acquired by the roadside information acquisition unit, the position information of the mobile body, and the abnormality information detected by the emergency stop request unit are the obstacle information around the mobile body detected by the sensor or the obstacle information around the roadside acquired by the roadside information acquisition unit; and a behavior determination unit that selects a travel route with the lowest travel difficulty for each of the candidate routes calculated by the route travel difficulty calculation unit; This is what is done. [Effects of the Invention]

[0008] According to the present application, it is possible to generate an action plan for stopping in an area that does not impede the progress of other traffic participants and has a low impact on other traffic participants. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a functional block diagram showing the configuration of a behavior planning apparatus and a vehicle control system according to a first embodiment. [Figure 2] 3 is a diagram showing an example of an obstacle detection range of an obstacle information detection unit mounted on a vehicle; FIG. [Figure 3] 5 is a diagram for explaining the operation of a stop position determination unit of the behavior planning device according to the first embodiment. FIG. [Figure 4] 4 is a flowchart showing the operations of the behavior planning device and the vehicle control system according to the first embodiment. [Figure 5] 2 is a functional block diagram showing a configuration of a behavior plan generating unit of the behavior planning device according to the first embodiment. FIG. [Figure 6] 5 is a flowchart showing the operation of a behavior plan generating unit of the behavior planning device according to the first embodiment. [Figure 7]4 is a diagram for explaining the operation of a behavior plan generating unit of the behavior planning device according to the first embodiment. FIG. [Figure 8] FIG. 2 is a diagram for explaining candidate routes generated by a candidate route generating unit according to the first embodiment. [Figure 9] 4 is a diagram for explaining the travel difficulty of a candidate route calculated by a route travel difficulty calculation unit according to the first embodiment. FIG. [Figure 10] FIG. 3 is a diagram for explaining an action determined by an action determining unit according to the first embodiment. [Figure 11] FIG. 10 is a diagram for explaining the operation of a behavior plan generating unit of the behavior planning apparatus according to the second embodiment. [Figure 12] FIG. 10 is a diagram for explaining the travel difficulty of a candidate route calculated by a route travel difficulty calculation unit according to the second embodiment. [Figure 13] FIG. 10 is a diagram for explaining an action determined by an action determining unit according to the second embodiment. [Figure 14] FIG. 10 is a functional block diagram showing the configuration of a behavior planning apparatus and a vehicle control system according to a third embodiment. [Figure 15A] 11 is a flowchart showing the operation of the behavior planning device according to the third embodiment. [Figure 15B] 11 is a flowchart showing the operation of the behavior planning device according to the third embodiment. [Figure 16] FIG. 11 is a diagram for explaining the operation of a behavior plan generating unit of the behavior planning device according to the third embodiment. [Figure 17] FIG. 11 is a diagram for explaining the travel difficulty of a candidate route calculated by a route travel difficulty calculation unit according to the third embodiment. [Figure 18] FIG. 11 is a diagram for explaining an action determined by an action determining unit according to the third embodiment. [Figure 19] FIG. 1 is a diagram showing a hardware configuration of a vehicle control system according to first to third embodiments. [Figure 20] FIG. 4 is a diagram illustrating another example of the hardware configuration of the vehicle control system according to the first to third embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the behavior planning device, vehicle control system, and behavior plan generation method disclosed in the present application will be described with reference to the drawings. In the following embodiments, an automobile is taken as an example of a mobile body to which the behavior planning device and vehicle control system are applied, and an example of generating a behavior plan for the vehicle is shown. The mobile body is assumed to be capable of automated driving equivalent to level 3 or level 4 defined by the Society of Automotive Engineers (SAE International), for example. The mobile body is assumed to have acquired a driving route to a destination in advance and to be driving along that route. In addition, the same reference numerals in each drawing indicate the same or corresponding parts. Therefore, detailed descriptions thereof may be omitted to avoid duplication.

[0011] Embodiment 1 The behavior planning device, vehicle control system, and behavior plan generating method according to the first embodiment will be described below with reference to the drawings. <Device configuration> FIG. 1 is a functional block diagram showing the configurations of a behavior planning apparatus and a vehicle control system according to a first embodiment. In FIG. 1, a vehicle control system 1000 includes a behavior planning apparatus 100. The behavior planning apparatus 100 is an apparatus that plans the behavior of the host vehicle, and includes an emergency stop request unit 120, a stop position determination unit 140, and a behavior plan generation unit 160 that performs calculations to generate behavior that reduces the impact on the surrounding area. The vehicle control system 1000 includes an information acquisition unit 300 that acquires information necessary for generating a behavior plan for the host vehicle in the behavior planning apparatus 100, and the information acquired by the information acquisition unit 300 is input to the behavior planning apparatus 100. The information acquisition unit 300 includes an obstacle information acquisition unit 10 that acquires obstacle information around the host vehicle, a road information acquisition unit 20, a host position acquisition unit 30 that acquires position information of the host vehicle, and a roadside information acquisition unit 40 that acquires information from roadside units RU. Furthermore, the vehicle control system 1000 includes a vehicle control unit 200, which controls each actuator that drives the vehicle, such as the brakes and steering, based on the behavior plan generated by the behavior planning device 100.

[0012] In FIG. 1, the obstacle information acquisition unit 10, the road information acquisition unit 20, the self-position acquisition unit 30, and the roadside information acquisition unit 40 may be included in the behavior planning apparatus 100.

[0013] The obstacle information acquisition unit 10 acquires information about obstacles present around the vehicle detected by the obstacle information detection unit 12 .

[0014] The obstacle information detection unit 12 detects obstacle information. The obstacles are, for example, traffic participants such as other vehicles, pedestrians, bicycles, and motorcycles present around the vehicle. The obstacle information detection unit 12 is, for example, at least one of a camera, radar, LiDAR (Light Detection And Ranging), and sonar sensor provided on the vehicle. The obstacle information detection unit 12 may output to the obstacle information acquisition unit 10 obstacle information associated with the type of traffic participant categorized as other vehicles, pedestrians, bicycles, motorcycles, and the like.

[0015] The camera is installed in a position where it can capture images of the front, sides, and rear of the vehicle, and from the captured images, it obtains information about the environment in which the vehicle is located, such as information about the lane and obstacles in front of the vehicle.

[0016] The radar emits radar light ahead of the vehicle and detects the reflected waves to measure the relative distance and relative speed of an obstacle present ahead of the vehicle, and outputs the measurement results.

[0017] LiDAR detects the position of an object by shining a laser around the vehicle and detecting the time difference between the time it takes for the laser to reflect off an object and return.

[0018] A sonar sensor detects the position and distance of an object by emitting ultrasonic waves to the area around the vehicle and detecting the time difference between the time it takes for the waves to reflect off an object and return.

[0019] FIG. 2 shows an example in which multiple obstacle information detection units 12 described above are combined and arranged on a vehicle, illustrating the detection ranges of each obstacle information detection unit 12. In FIG. 2, seven obstacle information detection units 12, from obstacle information detection unit 12a to obstacle information detection unit 12g, are mounted on the host vehicle OV, with three obstacle information detection units 12a, 12b, and 12g arranged in the front, two obstacle information detection units 12c and 12f arranged on the sides, and two obstacle information detection units 12d and 12e arranged in the rear. The detection ranges of each obstacle information detection unit 12 are indicated by fan-shaped dashed lines, and the host vehicle OV can detect obstacles in detection ranges SN1, SN2, and SN7 in the front, detection ranges SN3 and SN6 on the sides, and detection ranges SN4 and SN5 in the rear. While not limited to seven obstacle information detection units 12, it is desirable to be able to set the obstacle detection ranges to encompass the entire periphery of the host vehicle OV.

[0020] The road information acquisition unit 20 acquires information about roads around the vehicle from a road information detection unit (not shown). The road information acquisition unit 20 includes a map information acquisition unit that has acquired map data of the planned route of the vehicle in advance, and acquires road information around the vehicle based on the vehicle position information detected by the vehicle position detection unit 32. Here, the map data includes road information such as the center line of the lane in which the vehicle is traveling, lane width information, stop line information at intersections, information on the number of branches at intersections such as T-junctions and crossroads, stop line information at intersections, and information on the start position of diverging roads. Furthermore, the road information included in the map data may be acquired from the surrounding structure detection results obtained from at least one of the camera, radar, LiDAR, and sonar sensor that constitutes the obstacle information detection unit 12 provided in the vehicle.

[0021] In order to identify the position of the vehicle, the vehicle is equipped with a GNSS (Global Navigation Satellite System) sensor as a self-position detection unit 32. A GNSS antenna is connected to the GNSS sensor, and the GNSS sensor receives positioning signals from positioning satellites orbiting in satellite orbits. The GNSS antenna analyzes the received positioning signals and outputs information about the phase center of the GNSS antenna (latitude, longitude, altitude, direction, etc.) to the self-position acquisition unit 30.

[0022] In addition, the self-position, which is the position information of the vehicle, may be obtained not only by using a GNSS sensor, but also by using SLAM (Simulataneous Localization and mapping: simultaneous execution of self-position estimation and environmental map creation) technology using the detection results of surrounding structures obtained from at least one of a camera, radar, LiDAR, and sonar sensor.

[0023] For example, an obstacle information detector (hereinafter referred to as a roadside unit) provided on a roadside strip includes at least one of a camera, radar, LiDAR, and sonar sensor. Information about the roadside surroundings detected by the roadside unit RU is acquired by the roadside information acquisition unit 40 via wireless communication as obstacle information. Note that the roadside unit may be provided not only on the roadside strip, but also on the road, such as the carriageway, road shoulder, or sidewalk, or may be provided on a building or utility pole near the road. Information about the roadside surroundings may also be acquired from a remote control system or the like.

[0024] 1, the obstacle information acquisition unit 10, the road information acquisition unit 20, the own position acquisition unit 30, and the roadside information acquisition unit 40 are not shown as being included in the behavior planning device 100. This configuration is suitable for remote control of the host vehicle by a traffic control center. As an example, the components including the emergency stop request unit 120, the stop position determination unit 140, and the behavior plan generation unit 160 are provided separately from the components including the obstacle information acquisition unit 10, the road information acquisition unit 20, the own position acquisition unit 30, and the roadside information acquisition unit 40. Specifically, the obstacle information acquisition unit 10, the road information acquisition unit 20, the own position acquisition unit 30, and the roadside information acquisition unit 40 are provided in the host vehicle, and the emergency stop request unit 120, the stop position determination unit 140, and the behavior plan generation unit are provided on the traffic control side as the behavior planning device 100. However, this is not limiting, and for example, the reverse may also be possible.

[0025] The emergency stop request unit 120 detects whether or not an abnormality has occurred in the obstacle information acquired from the obstacle information acquisition unit 10 and the obstacle information acquired from the roadside information acquisition unit 40, and outputs an emergency stop request if an abnormality is detected.

[0026] Here, a method for detecting an abnormality occurring in the obstacle information will be described. First, an example of an abnormality in the obstacle information acquired from the roadside information acquisition unit 40 will be described. An abnormality in the obstacle information acquired from the roadside information acquisition unit 40 is a communication breakdown, and the presence or absence of this communication breakdown can be determined by providing the roadside device with a signal that counts up at regular intervals to the roadside information acquisition unit 40. When an event is detected in which the count up at regular intervals does not occur, this can be rephrased as a communication breakdown from the roadside device to the roadside information acquisition unit 40. As described above, the emergency stop request unit 120 determines a communication breakdown based on the obstacle information acquired from the roadside information acquisition unit 40 and detects an abnormality.

[0027] Next, an example of an abnormality in the obstacle information acquired from the obstacle information detection unit 12 provided in the vehicle will be described. An abnormality in the obstacle information acquired from the obstacle information detection unit 12 provided in the vehicle includes communication interruption and a reduction in the detection range. Communication interruption can be determined and an abnormality can be detected by using a signal that counts up at regular intervals, similar to the communication interruption from the roadside device to the roadside information acquisition unit. The presence or absence of a decrease in the detection range can be determined by checking whether snow or the like has adhered near the sensor, which is the obstacle information detection unit 12, and whether the measured distance has continued to be detected as being equal to or less than a predetermined threshold for a predetermined period of time. That is, if snow or the like has adhered so as to cover part of the sensor, the detection range will be smaller than normal, making it possible to detect an abnormality. Also, if part of the camera's imaging element is damaged, and some of the pixels in the camera image have no color or no color change for a predetermined period of time, the detection range will decrease, making it possible to detect an abnormality.

[0028] The stop position determination unit 140 determines whether or not to enter and stop in an area that will have a high impact on other traffic participants if the vehicle stops from its current position, based on the road information acquired from the road information acquisition unit 20, the vehicle's own position acquired from the own position acquisition unit 30, and the emergency stop request output from the emergency stop request unit 120.

[0029] Here, possible methods for calculating the stopping position include a method in which the current position is calculated as the stopping position, or a method in which the stopping position is calculated using the speed (deceleration) that the vehicle can output when stopping from its current vehicle speed.

[0030] Whether or not the calculated stopping position of the vehicle is within an area that will have a large impact on other traffic participants is determined based on road information acquired by the road information acquisition unit 20. An area that will have a large impact on other traffic participants refers to an area where stopping at that position will hinder the progress of other traffic participants, and specifically, is an "area where roads intersect," such as an area inside the stop line at an intersection or a merging point on an expressway. Hereinafter, "an area that will have a large impact on other traffic participants" will be read as "an area that will hinder the progress of other traffic participants."

[0031] Next, an example of a method for determining whether the host vehicle will stop in an "area that will hinder the progress of other traffic participants" will be described with reference to Fig. 3. Fig. 3 is a diagram for explaining the operation of the stop position determination unit of the behavior planning device according to the first embodiment. Fig. 3 shows a state in which the host vehicle OV, which keeps to the left, is approaching an intersection, and the rectangular area indicated by dashed lines connecting the stop lines SL1, SL2, SL3, and SL4 of the lanes that make up the intersection is the intersection area CNF. Here, the area inside the stop lines SL1, SL2, SL3, and SL4 of the intersection, i.e., the area within area CNF, is defined as the "area that will hinder the progress of other traffic participants."

[0032] First, the road information acquisition unit 20 inputs position information of the stop lines SL1, SL2, SL3, and SL4 that form the intersection into the stop position determination unit 140. By connecting the position information of these stop lines SL1, SL2, SL3, and SL4, an area CNF represented by a rectangle can be generated. Then, if the stopping position of the host vehicle OV is within the area CNF, it is determined that the host vehicle OV will stop in an area that will obstruct the progress of other traffic participants.

[0033] Next, the stopping position of the host vehicle OV is calculated. Since center line information of the lane on which the host vehicle is traveling is acquired from the road information acquisition unit 20, if that information is taken as a straight path STR, which is a target route that the host vehicle should follow, the stopping position of the host vehicle OV is expressed as a stopping position SP on the straight path STR in Fig. 3. The stopping position SP of the host vehicle OV is calculated using the deceleration of the host vehicle OV on the straight path STR.

[0034] In Figure 3, the position of the center of gravity of the host vehicle OV when stopped is represented by the stopping position SP, and if this position is within the intersection area CNF, it is determined that the host vehicle OV will enter an area that will hinder the progress of other traffic participants when stopped. The stop position SP may be any position that allows identification of the host vehicle OV, such as the leading or trailing edge of the host vehicle OV. Whether the host vehicle OV is within the area CNF may also be determined by generating a rectangle (simulating the external shape of the host vehicle) from the position (stop position) taking into account the size of the host vehicle OV, and if part of the rectangle is within the intersection area CNF, determining that the host vehicle OV will enter an area that will obstruct the progress of other traffic participants when stopped.

[0035] In the above description, a method has been shown in which the area CNF is generated as an intersection area based on the position information of the stop line at the intersection input from the road information acquisition unit 20 as an area that may hinder the progress of other traffic participants. However, this is not limiting. The area CNF may be input directly to the stop position determination unit 140 based on intersection information, etc., held by the road information acquisition unit 20 as an area that may have a large impact on other traffic participants. Furthermore, by using divergence start position information held by the road information acquisition unit 20, an area including the divergence start position can be used as the area CNF, and an area CNF that is not limited to an intersection area can be set.

[0036] As described above, the stop position determination unit 140 determines whether or not the host vehicle OV will enter and stop in an area that will obstruct the progress of other traffic participants when the host vehicle OV stops from its current position.

[0037] Next, the action plan generating unit 160 will be described. The behavior plan generation unit 160 generates a behavior plan for preventing the vehicle from stopping in an area that would hinder the progress of other traffic participants, based on the obstacle information around the vehicle output from the obstacle information acquisition unit 10, the road information output from the road information acquisition unit 20, the vehicle's own position output from the self-position acquisition unit 30, the obstacle information output from the roadside information acquisition unit 40, the emergency stop request output from the emergency stop request unit 120, and the determination result of whether or not to enter and stop in an area that would hinder the progress of other traffic participants output from the stop position determination unit 140.

[0038] The behavior plan of the host vehicle generated by the behavior plan generating unit 160 specifically includes a target route, target speed, and target position when the host vehicle travels. It may also include information indicating upper and lower limits of acceleration when the host vehicle travels, and a steering angle for following the target route.

[0039] <Operations of the vehicle control system 1000 and the behavior planning device 100> Next, the operation of the vehicle control system 1000 and the behavior planning device 100 according to the first embodiment will be described using the flowchart in Fig. 4. The processing of the flowchart in Fig. 4 is repeatedly executed while the host vehicle is traveling. Each step in Fig. 4 will be described in association with each functional unit shown in the functional block diagram in Fig. 1.

[0040] First, in step S101, the obstacle information acquisition unit 10 acquires information on obstacles present around the vehicle, which is output from the obstacle information detection unit 12. In step S102, the self-position acquisition unit 30 acquires the self-position output from the self-position detection unit 32.

[0041] In step S103, the road information acquisition unit 20 acquires road information output from a road information detection unit (not shown) or road information from a map information acquisition unit. In step S104, the roadside information acquisition unit 40 acquires the roadside information output from the roadside unit RU.

[0042] In step S105, the emergency stop request unit 120 detects whether an abnormality has occurred in the obstacle information based on the obstacle information output from the obstacle information acquisition unit 10 and the obstacle information output from the roadside information acquisition unit 40, and outputs an emergency stop request if an abnormality is detected. If an abnormality is detected and a stop request is to be output (Yes in step S105), the process proceeds to step S106. If no abnormality is detected, a stop request is not output (No in step S105), and the process proceeds to step S109.

[0043] When the process proceeds to step S106, the stop position determination unit 140 determines whether the vehicle will stop in an area that will hinder the progress of other traffic participants if it stops from its current position. If the vehicle will stop in an area that will hinder the progress of other traffic participants (Yes in step S106), the process proceeds to step S107. If the vehicle will stop without entering an area that will hinder the progress of other traffic participants (Yes in step S106), the process proceeds to step S108. 106 If the answer is No in step S104, the process proceeds to step S108.

[0044] When the process proceeds to step S107, the behavior plan generating unit 160 generates a behavior plan that prevents the host vehicle from stopping in an area that would obstruct the progress of other traffic participants. If the process proceeds to step S108, the behavior plan generating unit 160 outputs an instruction to stop the vehicle immediately because the stopping position of the vehicle is not in an area that will obstruct the progress of other traffic participants.

[0045] When the process proceeds to step S109, the behavior plan generating unit 160 outputs a command to continue following the route on which the host vehicle is currently traveling. The output of the action plan generating unit 160 based on steps S107 to S109 is input to the vehicle control unit 200, which controls each actuator (not shown) that drives the vehicle, such as the brakes and steering wheel.

[0046] As described above, when it is determined that the host vehicle will stop in an area that would hinder the progress of other traffic participants, the behavior planning device 100 generates a behavior plan to avoid stopping in the area that would hinder the progress of other traffic participants, and when it is determined that the host vehicle will stop outside the area that would hinder the progress of other traffic participants, it outputs a command to stop the host vehicle immediately. Furthermore, when an emergency stop request has not been issued, the behavior planning device 100 generates a behavior plan to continue following the currently traveling route.

[0047] <Processing in the action plan generation unit 160> Next, we will explain the process of generating a behavior plan that has minimal impact on the surrounding area in the behavior plan generation unit 160. Figure 5 is a functional block diagram showing the configuration of the behavior plan generation unit 160. In Figure 5, the behavior plan generation unit 160 includes a candidate route generation unit 162, a route travel difficulty calculation unit 164, and a behavior decision unit 166.

[0048] The candidate route generation unit 162 generates routes that can be selected by the vehicle as candidate routes based on the road information acquired by the road information acquisition unit 20 and the vehicle's own position acquired by the own position acquisition unit 30.

[0049] Here, the candidate routes will be explained. Taking the case of turning right at a crossroads intersection as an example, the road information acquired from the road information acquisition unit 20 is only route information for a right turn. However, based on the information that it is a crossroads intersection, the candidate route generation unit 162 also generates a route going straight and a route turning left as candidate routes. Taking the case of turning right at a T-junction intersection where there is no straight destination as an example, the road information acquired from the road information acquisition unit 20 is only route information for a right turn, but based on the information that it is a T-junction intersection, the candidate route generation unit 162 also generates a route turning left as a candidate route.

[0050] The route travel difficulty calculation unit 164 calculates the difficulty of traveling along the generated candidate route for each route generated by the candidate route generation unit 162, based on the obstacle information acquired from the obstacle information acquisition unit 10 and the obstacle information output from the roadside information acquisition unit 40. The route travel difficulty will be described later.

[0051] The behavior decision unit 166 selects the route with the lowest travel difficulty based on each candidate route and its travel difficulty calculated by the route travel difficulty calculation unit 164, and generates behavior that avoids stopping in areas that would hinder the progress of other traffic participants. In other words, the behavior decision unit 166 sets a stopping position in an area that will have little impact on other traffic participants and guides the vehicle.

[0052] Next, the process of generating a behavior plan with minimal impact on the surroundings in the behavior plan generation unit 160 will be described using the flowchart shown in Fig. 6. The process of the flowchart in Fig. 6 is a detailed version of the operation of step S107 in Fig. 4. Each step in Fig. 7 will be described in association with each functional unit shown in the functional block diagram in Fig. 5.

[0053] First, in step S1071, the candidate route generating unit 162 generates at least one candidate route based on the road information acquired from the road information acquiring unit 20 and the self-position acquired from the self-position acquiring unit 30.

[0054] In step S1072, the route travel difficulty calculation unit 164 calculates the travel difficulty level for the vehicle to travel on each of the candidate routes generated by the candidate route generation unit 162, based on the obstacle information acquired from the obstacle information acquisition unit 10 and the obstacle information acquired from the roadside information acquisition unit 40.

[0055] In step S1073, the behavior decision unit 166 selects the route with the lowest travel difficulty from among the travel difficulties of the respective candidate routes calculated by the route travel difficulty calculation unit 164.

[0056] In step S1074, the behavior decision unit 166 generates an action plan based on the selected route to guide the vehicle to avoid areas that may hinder the progress of other traffic participants and to stop in an area that will not hinder the passage of other traffic participants and will have little impact on other traffic participants, and outputs the action plan to the vehicle control unit 200.

[0057] <Operation of the behavior planning device 100> Next, detailed operations of the behavior planning apparatus 100 will be described with reference to FIGS. FIG. 7 is a diagram for explaining a detailed operation example of the behavior planning apparatus 100, showing a situation in which an emergency stop request is output from the emergency stop request unit 120 to the host vehicle OV as it turns right and passes through an intersection. In FIG. 7, the area inside the stop line at the intersection is represented as an area CNF that obstructs the progress of other traffic participants. The roadside unit RU can detect obstacles within an area RUA indicated by a dotted fan, and here, it shows the detection of a pedestrian PD. That is, the roadside information acquisition unit 40 acquires the pedestrian PD as obstacle information. The host vehicle OV acquires obstacle information from the obstacle information detection unit 12, which is an obstacle detection sensor provided in the host vehicle OV, and from the roadside unit RU.

[0058] First, in FIG. 7, the situation before an emergency shutdown request is output from the emergency shutdown request unit 120 will be described. The vehicle OV follows and travels along the right-turn route RTR, which is acquired from the road information acquisition unit 20 and connects the centers of the roads generated for turning right and passing through the intersection, based on the position information acquired by the vehicle's own position acquisition unit, while being careful of pedestrians PD, acquired as obstacle information, jumping into the right-turn route RTR.

[0059] It is assumed that the emergency stop request unit 120 detects a malfunction in the obstacle information detection unit 12 (obstacle detection sensor) that detects the right side of the host vehicle OV with respect to the obstacle information acquired from the obstacle information acquisition unit 10. Then, the emergency stop request unit 120 outputs an emergency stop request to the stop position determination unit 140 and the action plan generation unit 160.

[0060] The stop position determination unit 140 calculates the stop position SP where the host vehicle OV will move to and stop when it stops from its current position based on an emergency stop request. As shown in Fig. 7, the stop position SP is set within an intersection within the area CNF, and if the host vehicle OV stops inside the stop line at the intersection, it will obstruct the progress of other vehicles. The stop position determination unit 140 then determines that the host vehicle OV will stop within the area CNF and outputs the determination result to the action plan generation unit 160.

[0061] Based on the determination result of the stop position determination unit 140, the host vehicle OV generates at least one or more candidate routes in the candidate route generation unit 162 based on the self-position information acquired from the self-position acquisition unit 30 and the road information acquired from the road information acquisition unit 20. Specifically, the host vehicle OV determines the exit direction of the intersection from information corresponding to the type of intersection (crossroads), information on the stop line SL, and information on the road width RW acquired from the road information acquisition unit, and generates a route from the host vehicle OV's own position in the exit direction. FIG. 8 shows an example of candidate routes generated by the candidate route generation unit 162, which illustrates candidate routes corresponding to the situation of the host vehicle in FIG. 7. That is, the candidate route STR in the straight direction, the left-turn route LTR for turning left, and the right-turn route RTR for turning right are generated. The generated candidate routes are then output to the route travel difficulty calculation unit 164.

[0062] 9 is a diagram for explaining the driving difficulty of each candidate route. The route driving difficulty calculation unit 164 calculates the driving difficulty of the vehicle for each of the candidate routes generated by the candidate route generation unit 162, i.e., the straight route STR, the left-turn route LTR, and the right-turn route RTR, using obstacle information acquired from the obstacle information acquisition unit 10, self-position information acquired from the self-position acquisition unit 30, and roadside information acquired from the roadside information acquisition unit 40. A specific calculation method will be described below.

[0063] Because the emergency stop request unit 120 determines that the obstacle information detection unit 12, which detects the right side of the host vehicle OV, has failed, the detectable area on the right side of the host vehicle OV is narrowed. When the obstacle information detection unit 12 mounted on the host vehicle OV is normal, the vehicle travels with increased redundancy by using the obstacle information acquired by the obstacle information acquisition unit 10 and the obstacle information acquired by the roadside information acquisition unit 40. On the other hand, when the detection area on the right side of the host vehicle OV is narrowed, traveling on the right-turn route RTR that turns right at the intersection means that, although the roadside unit RU detects that a pedestrian PD is near the right-turn route RTR, there is a possibility that the vehicle will be slow to respond to the pedestrian PD's behavior, such as if the pedestrian jumps out into the road. Therefore, the difficulty of traveling on the right-turn route RTR is calculated as high.

[0064] Next, for the left turn route LTR, it is determined that there are no obstacles around based on the results acquired from the roadside information acquisition unit 40 and the obstacle information acquisition unit 10 for the current position. However, since the plan was to turn right, the steering amount will be large. Therefore, the driving difficulty level of the left turn route LTR is calculated as medium.

[0065] Regarding the straight route STR, it can be determined that there are no obstacles beyond the area CNF by using the results obtained from the roadside information obtaining unit 40 and the results of the obstacle information detecting unit 12 provided in the host vehicle OV. In addition, since the straight route STR requires less steering of the steering wheel than the left-turn route LTR, the travel difficulty level of the straight route STR is calculated as low.

[0066] The above-mentioned three candidate routes LTR, STR, RTR and the calculation results of the respective driving difficulty levels are output to the behavior decision unit 166. The behavior decision unit 166 selects the straight route STR, which has the lowest driving difficulty level, as the route that the host vehicle OV should take, as shown in Fig. 10. Then, the behavior plan that stops the host vehicle OV at the stop position MRP after passing through an area CNF that obstructs the progress of other traffic participants on that route is output from the behavior plan generation unit 160.

[0067] In the example of calculating the driving difficulty of each candidate route described above, if an abnormality is detected in the obstacle information detection unit 12 that detects the right side of the host vehicle OV and the host vehicle is scheduled to travel on the straight route STR, the driving difficulty is calculated as follows: the difficulty of traveling on the right turn route RTR is high, the difficulty of traveling on the straight route STR is low, and the difficulty of traveling on the left turn route LTR is medium. In addition, if an abnormality is detected in the obstacle information detection unit 12 that detects the right side of the host vehicle OV, and the host vehicle is scheduled to travel on the left-turn route LTR, the travel difficulty levels are calculated as follows: the difficulty level for traveling on the right-turn route RTR is high, the difficulty level for traveling on the straight-ahead route STR is medium, and the difficulty level for traveling on the left-turn route LTR is low.

[0068] In the above, an example was shown in which an abnormality was detected in the obstacle information detection unit 12 that detects the right side of the host vehicle OV. However, even if an abnormality is detected in the obstacle information of the roadside information acquisition unit 40, the behavior of the pedestrian PD on the right side must be detected only by the obstacle information detection unit 12, and therefore a similar driving difficulty level is calculated.

[0069] As described above, according to the first embodiment, the behavior planning device includes an emergency stop request unit, a stop position determination unit, and a behavior plan generation unit. The emergency stop request unit detects an abnormality based on obstacle information acquired from the obstacle information acquisition unit and the roadside information acquisition unit, and outputs an emergency stop request if an abnormality is detected. The stop position determination unit calculates a stopping position for the host vehicle based on the emergency stop request and determines whether the host vehicle will stop in an area that will obstruct the progress of other traffic participants, such as an intersection. If the behavior plan generation unit determines that the host vehicle will stop in an area that will obstruct the progress of other traffic participants, such as an intersection, it generates a behavior plan to stop the host vehicle outside the area or after passing through the area. Then, a vehicle control unit of the vehicle control system drives each actuator based on the generated behavior plan. This makes it possible to stop the host vehicle in an area that will not obstruct the progress of other traffic participants and will have minimal impact on other traffic participants.

[0070] In addition, the behavior plan generation unit of the behavior planning device includes a candidate route generation unit, a route travel difficulty calculation unit, and a behavior decision unit. The candidate route generation unit generates at least one candidate route based on the road information acquired by the road information acquisition unit and the self-position acquired by the self-position acquisition unit. The route travel difficulty calculation unit calculates the travel difficulty of traveling along each candidate route based on the obstacle information acquired by the obstacle information acquisition unit and the obstacle information and abnormality detection information acquired by the roadside information acquisition unit. The behavior decision unit selects a route with a low travel difficulty, which has the effect of not only generating a behavior plan that stops after passing through the area, but also selecting a route that has a small impact on other traffic participants even when passing through the area.

[0071] Embodiment 2 The behavior planning device, vehicle control system, and behavior plan generating method according to the second embodiment will be described below with reference to the drawings. In addition, The configurations of the behavior planning apparatus and vehicle control system according to the second embodiment are the same as those of the first embodiment shown in FIGS. 1 and 5, and therefore a description thereof will be omitted.

[0072] <Operation of the behavior planning device 100> The operation of the behavior planning apparatus 100 according to the second embodiment will be described with reference to FIGS. FIG. 11 is a diagram for explaining a detailed example of the operation of the behavior planning apparatus 100 according to the second embodiment. The diagram illustrates how the host vehicle OV turns left and passes through an intersection by following the left-turn route LTR acquired from the road information acquisition unit 20 using the obstacle information detection unit 12 provided in the host vehicle OV and obstacle information acquired from the roadside unit RU. As in the first embodiment, the area inside the stop line at the intersection is represented as an area CNF that obstructs the progress of other traffic participants. However, the difference is that the road width in the direction in which the host vehicle OV turns right or left is wider than the road width in the direction in which the host vehicle OV travels straight ahead. The roadside unit RU can detect obstacles within the area RUA. Here, the diagram illustrates how pedestrians PD1 and PD2 are detected attempting to cross the road just beyond the intersection as viewed from the host vehicle OV, and how another vehicle VE is detected stopped by the roadside after the host vehicle OV has turned left and passed the intersection. That is, the roadside information acquisition unit 40 acquires the pedestrians PD1 and PD2 and other vehicles VE (stationary obstacles) as obstacle information.

[0073] The vehicle OV not only follows and travels along the left-turn route LTR, which is acquired from the road information acquisition unit 20 and connects the center of the road, and is generated to turn left and pass through the intersection, but also avoids the other vehicle VE, which is a stationary obstacle, based on the position information acquired by the vehicle's own position acquisition unit 30.

[0074] It is assumed that the emergency stop request unit 120 determines that an abnormality has occurred based on the detection result that an obstacle detection sensor that detects the right side of the host vehicle OV has failed, in relation to the obstacle information acquired from the obstacle information acquisition unit 10. Then, the emergency stop request unit 120 outputs an emergency stop request to the stop position determination unit 140 and the action plan generation unit 160.

[0075] The stop position determination unit 140 calculates the stop position SP where the host vehicle OV will move and stop when it stops from its current position based on the emergency stop request, as in embodiment 1. Then, as shown in Fig. 11, if the stop position SP is within the area CNF, it determines that the host vehicle OV will stop within the area CNF, and outputs the determination result to the behavior plan generation unit 160.

[0076] Based on the determination result of the stop position determination unit 140, the host vehicle OV generates at least one or more candidate routes in a candidate route generation unit 162 based on the self-position information acquired from the self-position acquisition unit 30 and the road information acquired from the road information acquisition unit 20. The method of generating candidate routes is the same as in the first embodiment, and a straight route STR, a left-turn route LTR, and a right-turn route RTR are generated and output to a route travel difficulty calculation unit 164.

[0077] 12 is a diagram for explaining the driving difficulty of each candidate route. The route driving difficulty calculation unit 164 calculates the driving difficulty for each of the routes generated by the candidate route generation unit 162, i.e., the straight route STR, the left-turn route LTR, and the right-turn route RTR, using obstacle information acquired from the obstacle information acquisition unit 10, self-position information acquired from the self-position acquisition unit 30, and roadside information acquired from the roadside information acquisition unit 40. In addition, road information acquired from the road information acquisition unit 20 is also used as necessary. The specific calculation method will be described below.

[0078] The detection area on the right side of the host vehicle OV has narrowed because the emergency stop request unit 120 has determined that the obstacle detection sensor installed on the right side of the host vehicle OV has failed. In a situation where the detection area has narrowed, the travel difficulty level of the route traveling in the corresponding direction, i.e., the right turn route RTR, is calculated as high.

[0079] Next, for the straight route STR, the roadside unit RU detects that pedestrians PD1 and PD2 are crossing the road at the point where the vehicle has passed through the intersection after going straight ahead, so the driving difficulty is calculated as medium, in that it is necessary to be careful of the presence of pedestrians PD1 and PD2 after passing through the intersection.

[0080] For the left-turn route LTR, the roadside unit RU detects the presence of another vehicle VE stopped at the side of the road as an obstacle, and therefore, the remaining route width LFW for the width of the left-turn route LTR is calculated by subtracting the width information of the other vehicle VE present on the left-turn route LTR from the road width RW2. FIG. 12 illustrates a situation in which the width of the left-turn route LTR of the host vehicle OV is wider than the road width RW1 of the straight route STR in the forward direction, and it is determined that the remaining route width LFW is greater than the width of the host vehicle OV by a predetermined value or more. Here, the fact that the remaining route width LFW is greater than the width of the host vehicle OV by a predetermined value or more means that there is no need to travel into other lanes, and the influence of obstacles in other lanes can be reduced, so the difficulty of traveling the left-turn route LTR is also calculated as medium.

[0081] The above-mentioned three candidate routes LTR, STR, RTR and the calculation results of their respective driving difficulty levels are output to the behavior decision unit 166. The behavior decision unit 166 determines the candidate route calculated to have the lowest driving difficulty level as the route that the host vehicle OV should take. Here, the straight route STR and the left-turn route LTR are calculated to have the same driving difficulty level, and if they are calculated to have the same driving difficulty level, it is determined that the left-turn route LTR acquired from the road information acquisition unit 20, i.e., the originally planned left-turn route LTR, is to be given priority.

[0082] That is, as shown in Fig. 13, the left-turn route LTR is determined as the route that the host vehicle OV should take. Then, the behavior plan generating unit 160 generates a behavior plan for the host vehicle OV to stop at a stop position MRP after passing through the area CNF on that route. The stop position MRP may also be determined to be a position where the host vehicle OV stops after passing through another vehicle VE, which is a stationary obstacle on the left side of the host vehicle OV.

[0083] In this embodiment, a method of prioritizing the route acquired from the road information acquisition unit 20 has been described, but the present invention is not limited to this example. A method of calculating the driving difficulty in advance from only the candidate routes generated by the candidate route generation unit 162 is also conceivable. For example, a method is conceivable in which the driving difficulty of the straight route STR is determined in advance as low, the driving difficulty of the left-turn route LTR as medium, and the driving difficulty of the right-turn route RTR as high, and the behavior decision unit 166 determines the driving route as the straight route STR based only on this ranking. Furthermore, as described in the second embodiment, when the straight route STR and the left-turn route LTR have the same medium driving difficulty, a method is conceivable in which the straight route STR is determined by combining the predetermined ranking with the driving difficulty calculated by the route driving difficulty calculation unit.

[0084] As described above, according to the second embodiment, the same effect as that of the first embodiment can be achieved. That is, when an abnormality is detected based on the obstacle information, it is possible to stop the vehicle in an area where the vehicle does not impede the progress of other traffic participants and where the impact on other traffic participants is minimal. Furthermore, if multiple calculation results from the route driving difficulty calculation unit are identical, priority is given to the one that is consistent with the route acquired from the road information acquisition unit, thereby minimizing the difficulty of driving while also achieving the effect of enabling the vehicle to perform actions to follow the route set as its target.

[0085] Embodiment 3 The behavior planning device, vehicle control system, and behavior plan generating method according to the third embodiment will be described below with reference to the drawings. <Device configuration> Fig. 14 is a functional block diagram showing the configurations of a behavior planning apparatus and a vehicle control system according to Embodiment 3. In Fig. 14, a vehicle control system 1000 includes a behavior planning apparatus 100. Note that descriptions overlapping with those of Embodiments 1 and 2 will be omitted. As shown in Fig. 14, the behavior planning apparatus 100 further includes an information accumulation unit 180 in addition to the configuration of the behavior planning apparatus 100 shown in Fig. 1, and the behavior plan generated by the behavior plan generation unit 160 includes obstacle information acquired by a roadside information acquisition unit and accumulated in the information accumulation unit 180, thereby generating a behavior plan for avoiding the host vehicle from stopping in an area that would obstruct the progress of other traffic participants.

[0086] The information accumulation unit 180 continues to accumulate obstacle information acquired by the roadside information acquisition unit 40, and outputs the accumulated information to the behavior plan generation unit 160. The obstacle information accumulated in the information accumulation unit 180 makes it possible to understand the transition of the obstacle information from the past. Note that possible methods of outputting to the behavior plan generation unit 160 include a method of outputting only obstacle information from the time one cycle before the current time t, or a method of outputting information measured over T seconds together with the measurement time. Here, one cycle is the count-up cycle described above.

[0087] The behavior plan generating unit 160 includes a candidate route generating unit 162, a route travel difficulty calculating unit 164, and a behavior determining unit 166, as in the first and second embodiments (see FIG. 5). The candidate route generating unit 162 generates candidate routes that can be selected by the vehicle based on the road information acquired by the road information acquiring unit 20 .

[0088] The route travel difficulty calculation unit 164 calculates the travel difficulty when traveling along each of the candidate routes generated by the candidate route generation unit 162, based on the obstacle information acquired from the obstacle information acquisition unit 10, the obstacle information output from the roadside information acquisition unit 40, and the obstacle information accumulated in the information accumulation unit 180.

[0089] The behavior decision unit 166 selects the candidate route with the lowest driving difficulty based on each candidate route and its driving difficulty calculated by the route driving difficulty calculation unit 164, and determines a behavior plan that avoids stopping in areas that would hinder the progress of other traffic participants.

[0090] <Operations of the vehicle control system 1000 and the behavior planning device 100> 15A and 15B are flowcharts showing the overall operation of the vehicle control system 1000 and the behavior planning apparatus 100 according to Embodiment 3. The processing of the flowcharts in Figures 15A and 15B is repeatedly executed while the host vehicle is traveling.

[0091] 15A and 15B will be described below in association with the respective functional units shown in the functional block diagram of Fig. 14. Note that the operations of steps S301 to S304, step S306, steps S3071 to S3074, step S308, and step S309 are similar to the operations of steps S101 to S104, step S105, steps S1071 to S1074, step S108, and step S109 shown in Figs. 4 and 5 of the first embodiment.

[0092] First, in steps S301 to S304, each functional unit acquires each piece of information in the same manner as described in the first embodiment. In step S305, the information accumulation unit 180 accumulates the obstacle information acquired by the roadside information acquisition unit 40.

[0093] In step S306, if an abnormality is detected in the obstacle information, an emergency stop request is output (Yes in step S306), and in step S307, stop position determination unit 140 determines whether or not to stop in an area that would hinder the progress of other traffic participants. In step S307, if it is determined that the vehicle will stop in an area that would hinder the progress of other traffic participants (Yes in step S307), the process proceeds to step S3071.

[0094] In step S3071, the candidate route generating unit 162 generates at least one candidate route based on the road information acquired from the road information acquiring unit 20 and the self-position acquired from the self-position acquiring unit 30.

[0095] In step S3072, for each of the candidate routes generated in step S3071, the route travel difficulty calculation unit 164 calculates the travel difficulty level for the host vehicle to travel on the basis of the obstacle information acquired from the obstacle information acquisition unit 10, the obstacle information acquired from the roadside information acquisition unit 40, and the obstacle information accumulated in the information accumulation unit 180.

[0096] In step S3073, the behavior decision unit 166 selects the route with the lowest travel difficulty from among the travel difficulties of the respective candidate routes calculated by the route travel difficulty calculation unit 164.

[0097] In step S3074, the behavior decision unit 166 generates an action plan based on the selected route to guide the vehicle to avoid areas that may hinder the progress of other traffic participants and to stop outside those areas or in an area that will have less impact on other traffic participants, and outputs the action plan to the vehicle control unit 200.

[0098] <Operation of the behavior planning device 100> Next, detailed operations of the behavior planning apparatus 100 according to the third embodiment will be described with reference to FIGS. FIG. 16 shows how the host vehicle OV passes through an intersection by traveling straight ahead along a straight path STR obtained from the road information acquisition unit 20, using obstacle information obtained from the obstacle information detection unit 12, which is an obstacle detection sensor provided on the host vehicle OV, and the roadside unit RU. As in the first and second embodiments, the area inside the stop line at the intersection is represented as an area CNF that has a large impact on other traffic participants. The roadside unit RU can detect obstacles within the area RUA, and this figure shows a detection situation in which the other vehicle VE has stopped on the road at a position where the host vehicle has passed through the intersection by traveling straight ahead. That is, the roadside information acquisition unit 40 acquires the other vehicle VE as obstacle information representing a stationary obstacle.

[0099] The vehicle OV not only follows the straight route STR, which is acquired from the road information acquisition unit 20 and connects the center of the road, and is generated to pass through the intersection in a straight line, but also avoids the other vehicle VE, which is a stationary obstacle, based on the position information acquired by the vehicle's own position acquisition unit 30.

[0100] It is assumed that the emergency stop request unit 120 determines that an abnormality exists in the obstacle information acquired from the roadside information acquisition unit 40 based on the detection result that communication from the roadside unit RU has been interrupted. Then, the emergency stop request unit 120 outputs an emergency stop request to the stop position determination unit 140 and the action plan generation unit 160.

[0101] The stop position determination unit 140 calculates the stop position SP to which the host vehicle OV will move and stop when it stops from its current position based on an emergency stop request, as in the first and second embodiments. As shown in Fig. 16, if the stop position SP is within the area CNF, it determines that the host vehicle OV will enter the area CNF and stop, and outputs the determination result to the action plan generation unit 160.

[0102] Based on the determination result of the stop position determination unit 140, the host vehicle OV generates at least one or more candidate routes in the candidate route generation unit 162 based on the self-position information acquired from the self-position acquisition unit 30 and the road information acquired from the road information acquisition unit 20. The method of generating candidate routes is the same as in the first and second embodiments. In this case, since the road is a T-junction, a straight route STR and a left-turn route LTR are generated as candidate routes and output to the route travel difficulty calculation unit 164.

[0103] 17 is a diagram for explaining the traveling difficulty of each candidate route. The route traveling difficulty calculation unit 164 calculates the traveling difficulty for each of the candidate routes generated by the candidate route generation unit, i.e., the straight route STR and the left-turn route LTR, using the obstacle information acquired from the obstacle information acquisition unit 10, the self-position information acquired from the self-position acquisition unit 30, the roadside information acquired from the roadside information acquisition unit 40, and the obstacle information accumulated in the information accumulation unit 180.

[0104] Here, the route travel difficulty calculation unit 164 calculates the travel difficulty for each candidate route, but at the time when communication from the roadside unit RU is lost and an abnormality determination is made, the obstacle information acquired from the roadside information acquisition unit 40 is unavailable. Therefore, the obstacle information obtained from the roadside unit RU is the obstacle information previously acquired by the information accumulation unit 180, i.e., the transition of the obstacle information accumulated up to the time of the abnormality determination. According to this information, based on the obstacle information previously acquired by the information accumulation unit 180, it is known that another vehicle VE is present at a stationary position where the vehicle has passed through the intersection after traveling straight ahead. Because the obstacle information previously acquired is of a stationary obstacle, the route travel difficulty calculation unit 164 determines that the obstacle has not moved significantly from its current position and estimates that a stationary obstacle exists on the straight route STR.

[0105] As in the second embodiment, the remaining path width LFW relative to the width of the straight path STR is calculated by subtracting width information of another vehicle VE, which is an obstacle present in the path, from the straight path STR. In the situation in FIG. 17, the remaining path width LFW is determined to be less than the width of the host vehicle OV, and in order to avoid the other vehicle VE, which is an obstacle, the host vehicle must travel by straying into another lane OL (here, the oncoming lane). However, when traveling by straying into another lane OL, it is necessary to take into account obstacle information on the other lane OL, but because information from the roadside unit RU has been interrupted, it is unclear whether another vehicle will appear on the other lane OL, and if another vehicle does appear, there is a possibility that it will obstruct travel.

[0106] Furthermore, when it is assumed that the host vehicle OV will stop after traveling to the obstacle, i.e., another vehicle VE, it is necessary to consider the size of the area FSP sandwiched between the obstacle, i.e., the other vehicle VE, and the area CNF. If the area FSP does not contain any obstacles but is not longer than the length of the host vehicle OV by a predetermined value, the area CNF will be included in the stopping position of the host vehicle OV. The situation in Figure 17 represents a case where the length of the area FSP is not longer than the length of the host vehicle OV. Therefore, if the area occupied by the host vehicle OV when traveling along the straight path STR and stopping is the area ESP indicated by the bold frame, it is estimated that the host vehicle OV will stop in a situation where part of the area ESP is included in the area CNF. Therefore, the driving difficulty of the straight path STR is calculated to be high. In this way, if an obstacle exists beyond the area CNF and at least part of the area FSP required for the host vehicle OV to stop ahead of the obstacle is included in the area CNF, the driving difficulty is calculated to be high.

[0107] On the other hand, for the left turn route LTR, it is possible to determine that there are no obstacles in the surrounding area using information from the obstacle information detection unit 12, which is an obstacle detection sensor provided in the vehicle OV, and therefore the travel difficulty of the route in the left turn direction is calculated to be low.

[0108] The calculation results of the candidate routes STR and LTR in the two directions and their respective driving difficulty levels are output to the behavior decision unit 166. The behavior decision unit 166 determines the left-turn route LTR, which has the lowest driving difficulty level, as the route that the host vehicle OV should take, as shown in Fig. 18. Then, the behavior plan for stopping the host vehicle OV at the stop position MRP after passing through the area CNF on that route is output from the behavior plan generation unit 160.

[0109] As described above, according to the third embodiment, the same effect as that of the first embodiment can be achieved. That is, when an abnormality is detected based on the obstacle information, it is possible to stop the vehicle in an area where the vehicle does not impede the progress of other traffic participants and where the impact on other traffic participants is minimal. Furthermore, since the behavior planning device according to the third embodiment further includes an information accumulation unit, when an abnormality is detected in the obstacle information acquired from the roadside information acquisition unit, the state of the obstacle can be estimated based on the information accumulated up until the occurrence of the abnormality. By using this information to calculate the difficulty of the travel route, it becomes possible to obtain a more accurate difficulty level.

[0110] In particular, the obstacle information acquired by the obstacle information acquisition unit around the vehicle, particularly in areas that have a significant impact on other traffic participants, such as intersections, varies in the range of detectable obstacle information as the vehicle approaches. However, the obstacle information acquired by the roadside information acquisition unit is obtained from obstacle detectors installed in roadside strips, so obstacle information within a predetermined range can be obtained regardless of the vehicle's position. Therefore, by storing the obstacle information acquired by the roadside information acquisition unit, even in the event of a communication outage, the position of stationary obstacles is likely to remain stable, making it useful to use the stored past information when calculating the driving difficulty of each candidate route. As a result, even if the detection range of the obstacle information detection unit (obstacle detection sensor) installed on the vehicle is short, by supplementing the information from distant areas with roadside information, it is possible to determine a route with low driving difficulty, avoid stopping the vehicle in areas that would hinder the progress of other traffic participants, and guide the vehicle to a location that will have a minimal impact on other traffic participants.

[0111] 19, that is, a vehicle control system 1000 including an arithmetic processing circuit 1001, a storage device 1002 including a ROM (Read Only Memory) storing a program for executing the functions of each functional unit and a RAM (Random Access Memory) for saving data of the execution results of each functional unit, which are the results of calculations performed by the program, and an input / output circuit 1003. The input / output circuit 1003 receives as inputs output results relating to obstacle information from an obstacle information detection unit 12 which is an obstacle detection sensor provided on the vehicle, self-position information detected by a self-position detection unit 32, and output results relating to obstacle information from a roadside unit RU, and outputs control signals for the speed, handling, etc. of the vehicle from the input / output circuit 1003 to a drive system device 2000 which is each actuator for driving the vehicle, such as a brake and a steering wheel.

[0112] A processor such as a CPU (Central Processing Unit) or a DSP (Digital Signal Processor) is applied to the arithmetic processing circuit 1001. Dedicated hardware may also be applied to the arithmetic processing circuit 1001. When the arithmetic processing circuit 1001 is dedicated hardware, the arithmetic processing circuit 1001 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a combination of these.

[0113] Furthermore, the functional units of the behavior planning device 100 and the vehicle control system 1000 may be realized by individual arithmetic processing circuits, or may be collectively realized by a single arithmetic processing circuit. Furthermore, each functional unit of the behavior planning device 100 and the vehicle control system 1000 can realize each of the above-mentioned functions by hardware, software, or a combination of these, with some functions being realized by dedicated hardware processing circuits and other functions being realized by software.

[0114] 20 shows another example of the hardware configuration of the vehicle control system 1000. A communication circuit 1004 is further provided in addition to the configuration of FIG. The communication circuit 1004 includes a wide-area communication unit and a short-range communication unit as a communication module. The wide-area communication unit uses a predetermined wide-area wireless communication standard, such as LTE (Long Term Evolution), 4G, or 5G (5th Generation; fifth generation mobile communication system). The short-range communication unit uses, for example, DSRC (Dedicated Short Range Communications), and although not described in the above embodiment, it can be used for communication with other vehicles to obtain information about other vehicles around the vehicle. can These communications are guaranteed to have a certain communication speed.

[0115] Since the roadside unit RU is installed outside the vehicle or outside of control, the obstacle information from the roadside unit RU is received through communication with the vehicle control system 1000. Here, the communication uses, for example, LTE or 5G.

[0116] Each sensor of the obstacle information detection unit 12 and the GNSS sensor of the self-position detection unit 32 are mounted on the vehicle, and information is output from each sensor to the information acquisition unit 300 via a communication line, and the sensors are connected using, for example, a CAN (Control Area Network: registered trademark) or the like.

[0117] Furthermore, even when a part of the vehicle control system 1000 is outside the vehicle, such as a traffic control station, and activates an emergency stop, signals are sent and received via the communication circuit 1004.

[0118] <Other embodiments> In the above description, an automobile is used as an example of a moving body to which the behavior planning device 100 and the vehicle control system 1000 are applied, but the application is not limited to automobiles and can be applied to various other moving bodies. The behavior planning device 100 can be used as a device for planning the behavior of moving bodies such as an in-building mobile robot that inspects the inside of a building, a line inspection robot, and personal mobility. When the moving body is other than an automobile, the information detected by the road information detection unit includes road information indicating the drivable area of ​​the route along which the moving body will travel. as The obstacle information acquired by the roadside unit RU may be information from an obstacle information detection unit provided within a building, a road, or within the range in which the personal mobility moves.

[0119] Although the present application describes various exemplary embodiments and examples, the various features, aspects, and functions described in one or more embodiments are not limited to application to a particular embodiment, but may be applied to the embodiments alone or in various combinations. Therefore, countless variations not illustrated are conceivable within the scope of the technology disclosed in the present specification, including, for example, cases where at least one component is modified, added, or omitted, and cases where at least one component is extracted and combined with components of another embodiment.

[0120] Various aspects of the present disclosure are summarized below as appendices.

[0121] (Appendix 1) Obstacle information around the moving object acquired by the obstacle information acquisition unit; position information of the moving object acquired by a self-position acquisition unit; Road information around the moving object acquired by a road information acquisition unit, and an action planning device to which obstacle information around a roadside acquired by a roadside information acquisition unit is input, the action planning device including an emergency stop request unit that outputs an emergency stop request when an abnormality is detected in at least one of the obstacle information around the moving object acquired by the obstacle information acquisition unit and the obstacle information around the roadside acquired by the roadside information acquisition unit; a stop position determination unit that determines whether the moving object will stop within a first area that would hinder the progress of other traffic participants when the moving object stops, based on the road information, the position information of the moving object, and the emergency stop request output from the emergency stop request unit; and and a behavior plan generation unit that generates a behavior plan to prevent the moving object from stopping in the first area when the stop position determination unit determines that the moving object will stop in the first area, which would hinder the progress of other traffic participants. (Appendix 2) The action plan generation unit The road information and the mobile Location information a candidate route generating unit that generates at least one candidate route along which the moving object will travel based on the The obstacle information acquired by the obstacle information acquisition unit, the obstacle information around the roadside acquired by the roadside information acquisition unit, Location information and a route travel difficulty calculation unit that calculates a travel difficulty level for the moving object to travel along each of the candidate routes generated by the candidate route generation unit based on the abnormality information detected by the emergency stop request unit; The route travel difficulty calculation unit calculates the route travel difficulty for each of the candidate routes, and low a behavior determination unit that selects a travel route, 2. The behavior planning device according to claim 1, wherein a behavior plan is generated in which the moving body stops outside the first region. (Appendix 3) The route travel difficulty calculation unit If an obstacle exists beyond the first area, a second area is calculated as a stopping area required for the moving body to stop in front of the obstacle; 3. The behavior planning device according to claim 2, wherein the travel difficulty level is calculated to be high when at least a portion of the second area exists within the first area. (Appendix 4) The candidate route generation unit generating a route along which the moving body is scheduled to travel to a target position as one of candidate routes; The behavior determination unit 4. The behavior planning device according to claim 2 or 3, wherein when the travel difficulty levels are the same, the route along which the moving object is scheduled to move to a target position is selected with priority. (Appendix 5) an information storage unit that stores the obstacle information around the roadside area acquired by the roadside information acquisition unit, The action plan generation unit 5. The behavior planning device according to claim 1, wherein, when the stop position determination unit determines that the vehicle will stop in the first area, which will obstruct the progress of other traffic participants, the obstacle information accumulated in the information accumulation unit is added to generate a behavior plan for avoiding the vehicle from stopping in the first area. (Appendix 6) an information storage unit that stores the obstacle information around the roadside area acquired by the roadside information acquisition unit, The route travel difficulty calculation unit 5. The behavior planning device according to claim 2, wherein the obstacle information accumulated in the information accumulation unit is added to calculate a degree of difficulty of travel when the moving object travels along each of the candidate routes generated by the candidate route generation unit. (Appendix 7) The action plan generation unit The behavior planning device described in Appendix 5, wherein, when the emergency stop request unit detects an abnormality in the obstacle information around the roadside acquired by the roadside information acquisition unit, the emergency stop request unit generates a behavior plan to avoid stopping within the first area using the obstacle information accumulated in the information accumulation unit, without using the obstacle information around the roadside acquired by the roadside information acquisition unit. (Appendix 8) 8. The behavior planning device according to claim 1, further comprising: the obstacle information acquisition unit, the self-position acquisition unit, the road information acquisition unit, and the roadside information acquisition unit. (Appendix 9) A vehicle control system comprising: a behavior planning device according to any one of Supplementary notes 1 to 8; and a vehicle control unit that controls a moving object. (Appendix 10) A behavior plan generation method executed by using a behavior planning device, comprising: acquiring obstacle information around the moving object; acquiring location information of the moving object; acquiring road information around the mobile object; acquiring obstacle information around the roadside; outputting an emergency stop request when an abnormality is detected in at least one of the acquired obstacle information around the moving body and the acquired obstacle information around the roadside; determining whether the moving body will stop in an area that would hinder the progress of other traffic participants when stopping, based on the acquired road information and position information of the moving body and the output emergency stop request; If it is determined that the moving body will stop within the area, generating a behavior plan to prevent the moving body from stopping within the area. (Appendix 11) In the step of generating an action plan, generating at least one candidate route for the moving object based on the road information and the position information of the moving object; calculating a degree of difficulty of travelling when the mobile body travels along each of the candidate routes based on obstacle information around the mobile body, obstacle information around the roadside, position information of the mobile body, and detected abnormality information; The most difficult driving difficulty among the calculated driving difficulties low selecting a travel route; 11. A behavior plan generating method according to claim 10, comprising: generating a behavior plan for stopping the moving body outside the area based on the selected travel route. (Appendix 12) After the step of acquiring obstacle information around the roadside, The method further comprises a step of storing the acquired obstacle information around the roadside, In the step of generating an action plan, 12. The behavior plan generating method according to claim 10 or 11, further comprising: generating a behavior plan for the moving object by adding the accumulated information about obstacles around the roadside. [Explanation of symbols]

[0122] 10: Obstacle information acquisition unit, 12, 12a, 12b, 12c, 12d, 12e, 12f, 12g: Obstacle information detection unit, 20: Road information acquisition unit, 30: Self-position acquisition unit, 32: Self-position detection unit, 40: Roadside information acquisition unit, 100: Behavior planning device, 120: Emergency stop request unit, 140: Stop position determination unit, 160: Behavior plan generation unit, 162: candidate route generation unit; 164: route travel difficulty calculation unit; 166: action decision unit; 180: information storage unit; 200: Vehicle control unit, 300: Information acquisition unit, 1000: Vehicle control system, 1001: Arithmetic processing circuit, 1002: Storage device, 1003: Input / output circuit, 1004: Communication circuit, 2000: Drive system device, OV: Vehicle, RU: Roadside unit, RUA: Area, CNF: Area, VE: Other vehicle, SN1, SN2, SN3, SN4, SN5, SN6, SN7: Detection range, SL, SL1, SL2, SL3, SL4: Stop line, SP, MRP: Stop position, STR: Straight route, LTR: Left turn route, RTR: Right turn route, PD, PD1, PD2: Pedestrian, RW, RW1, RW2: Road width, LFW: Remaining route width, FSP: Area, ESP: Area, OL : Other lanes.

Claims

1. Obstacle information around the moving object detected by at least one sensor and acquired by an obstacle information acquisition unit; position information of the moving object acquired by a self-position acquisition unit; Road information around the moving object acquired by a road information acquisition unit, and An action planning device to which obstacle information around a roadside area acquired by a roadside information acquisition unit is input, an emergency stop request unit that outputs an emergency stop request when an abnormality is detected in at least one of the obstacle information around the moving object acquired by the obstacle information acquisition unit and the obstacle information around the roadside acquired by the roadside information acquisition unit; a stop position determination unit that determines whether the moving object will stop within a first area that would hinder the progress of other traffic participants when the moving object stops, based on the road information, the position information of the moving object, and the emergency stop request output from the emergency stop request unit; and a behavior plan generation unit that generates a behavior plan for preventing the moving object from stopping in the first area when the stop position determination unit determines that the moving object will stop in the first area where the stopping position determination unit will hinder the progress of other traffic participants, The action plan generation unit a candidate route generating unit that generates at least one candidate route along which the mobile object will travel based on the road information and the position information of the mobile object; a route travel difficulty calculation unit that calculates a travel difficulty level for the mobile body when traveling along each of the candidate routes generated by the candidate route generation unit, based on whether the obstacle information acquired by the obstacle information acquisition unit, the obstacle information around the roadside acquired by the roadside information acquisition unit, the position information of the mobile body, and the abnormality information detected by the emergency stop request unit are the obstacle information around the mobile body detected by the sensor or the obstacle information around the roadside acquired by the roadside information acquisition unit; and a behavior decision unit that selects a travel route with the lowest travel difficulty for each of the candidate routes calculated by the route travel difficulty calculation unit.

2. The candidate route generation unit generating a route along which the moving body is scheduled to move to a target position as one of candidate routes; The behavior determination unit 2. The behavior planning device according to claim 1, wherein, when the travel difficulty levels are the same, a route along which the moving object is scheduled to move to a target position is selected with priority.

3. Obstacle information around the moving object acquired by an obstacle information acquisition unit; position information of the moving object acquired by a self-position acquisition unit; Road information around the moving object acquired by a road information acquisition unit, and An action planning device to which obstacle information around a roadside area acquired by a roadside information acquisition unit is input, an emergency stop request unit that outputs an emergency stop request when an abnormality is detected in at least one of the obstacle information around the moving object acquired by the obstacle information acquisition unit and the obstacle information around the roadside acquired by the roadside information acquisition unit; a stop position determination unit that determines whether the moving object will stop within a first area that would hinder the progress of other traffic participants when the moving object stops, based on the road information, the position information of the moving object, and the emergency stop request output from the emergency stop request unit; and a behavior plan generation unit that generates a behavior plan for preventing the moving object from stopping in the first area when the stop position determination unit determines that the moving object will stop in the first area where the stopping position determination unit will hinder the progress of other traffic participants, The action plan generation unit a candidate route generating unit that generates at least one candidate route along which the mobile object will travel based on the road information and the position information of the mobile object; a route travel difficulty calculation unit that calculates a travel difficulty level for the mobile body when traveling along each of the candidate routes generated by the candidate route generation unit, based on the obstacle information acquired by the obstacle information acquisition unit, obstacle information around the roadside acquired by the roadside information acquisition unit, position information of the mobile body, and abnormality information detected by the emergency stop request unit; and a behavior determination unit that selects a travel route with the lowest travel difficulty for each of the candidate routes calculated by the route travel difficulty calculation unit; The candidate route generation unit generating a route along which the moving body is scheduled to move to a target position as one of candidate routes; The behavior determination unit A behavior planning device characterized in that, when the travel difficulty levels are the same, a route along which the moving object is scheduled to move to a target position is selected with priority.

4. The route travel difficulty calculation unit If an obstacle exists beyond the first area, a second area is calculated as a stopping area required for the moving body to stop in front of the obstacle; The behavior planning device according to claim 1 , wherein the travel difficulty level is calculated to be high when at least a part of the second area is present within the first area.

5. an information storage unit that stores the obstacle information around the roadside area acquired by the roadside information acquisition unit, The action plan generation unit 4. The behavior planning device according to claim 1, wherein, when the stop position determination unit determines that the vehicle will stop in the first area where the stop will obstruct the progress of other traffic participants, the behavior planning device generates a behavior plan to avoid the vehicle from stopping in the first area by adding the obstacle information accumulated in the information accumulation unit.

6. an information storage unit that stores the obstacle information around the roadside area acquired by the roadside information acquisition unit, The route travel difficulty calculation unit 4. The behavior planning device according to claim 1, wherein the obstacle information stored in the information storage unit is added to calculate a degree of difficulty of travel for the mobile object when traveling along each of the candidate routes generated by the candidate route generation unit.

7. Obstacle information around the moving object acquired by an obstacle information acquisition unit; position information of the moving object acquired by a self-position acquisition unit; Road information around the moving object acquired by a road information acquisition unit, and An action planning device to which obstacle information around a roadside area acquired by a roadside information acquisition unit is input, an emergency stop request unit that outputs an emergency stop request when an abnormality is detected in at least one of the obstacle information around the moving object acquired by the obstacle information acquisition unit and the obstacle information around the roadside acquired by the roadside information acquisition unit; a stop position determination unit that determines whether the moving object will stop within a first area that would hinder the progress of other traffic participants when the moving object stops, based on the road information, the position information of the moving object, and the emergency stop request output from the emergency stop request unit; and a behavior plan generation unit that generates a behavior plan to prevent the moving object from stopping in the first area when the stop position determination unit determines that the moving object will stop in the first area where the stopping position determination unit will hinder the progress of other traffic participants; an information storage unit that stores the obstacle information around the roadside area acquired by the roadside information acquisition unit, The action plan generation unit When the stop position determination unit determines that the vehicle will stop in the first area where the vehicle will hinder the progress of other traffic participants, the obstacle information stored in the information storage unit is added to generate an action plan to avoid the vehicle from stopping in the first area; and an action planning device that, when the emergency stop request unit detects an abnormality in the obstacle information around the roadside acquired by the roadside information acquisition unit, generates an action plan to avoid stopping within the first area using the obstacle information accumulated in the information accumulation unit, without using the obstacle information around the roadside acquired by the roadside information acquisition unit.

8. 8. The behavior planning device according to claim 1, further comprising: the obstacle information acquisition unit, the self-position acquisition unit, the road information acquisition unit, and the roadside information acquisition unit.

9. 10. A vehicle control system comprising: a behavior planning device according to claim 1; and a vehicle control unit that controls a moving object.

10. A behavior plan generation method executed by using a behavior planning device, comprising: acquiring obstacle information around the moving object detected by at least one sensor; acquiring location information of the moving object; acquiring road information around the mobile object; acquiring obstacle information around the roadside; outputting an emergency stop request when an abnormality is detected in at least one of the acquired obstacle information around the moving object and the acquired obstacle information around the roadside; determining whether the moving body will stop in an area that would hinder the progress of other traffic participants when stopping, based on the acquired road information and position information of the moving body and the output emergency stop request; and generating an action plan to prevent the moving body from stopping in the area when it is determined that the moving body will stop in the area; In the step of generating an action plan, generating at least one candidate route for the mobile object based on the road information and the position information of the mobile object; calculating a degree of difficulty of travelling when the mobile body travels along each of the candidate routes, based on which of the sensors has detected the obstacle information around the mobile body, the obstacle information around the roadside, the position information of the mobile body and the detected abnormality information; selecting a travel route with the lowest travel difficulty level from the calculated travel difficulty levels; generating a behavior plan for stopping the moving body outside the area based on the selected travel route.

11. A behavior plan generation method executed using a behavior planning device, comprising: acquiring obstacle information around the moving object; acquiring location information of the moving object; acquiring road information around the mobile object; acquiring obstacle information around the roadside; outputting an emergency stop request when an abnormality is detected in at least one of the acquired obstacle information around the moving object and the acquired obstacle information around the roadside; determining whether the moving body will stop in an area that would hinder the progress of other traffic participants when stopping, based on the acquired road information and position information of the moving body and the output emergency stop request; and generating an action plan to prevent the moving body from stopping in the area when it is determined that the moving body will stop in the area; In the step of generating an action plan, generating at least one candidate route for the moving object based on the road information and the position information of the moving object, and generating a route along which the moving object is scheduled to travel to a target position as one of the candidate routes; calculating a degree of difficulty of travelling when the mobile body travels along each of the candidate routes based on obstacle information around the mobile body, obstacle information around the roadside, position information of the mobile body, and detected abnormality information; selecting a travel route with the lowest travel difficulty from among the calculated travel difficulties, and, if the travel difficulties are the same, preferentially selecting a route along which the moving body is scheduled to move to a target position; generating a behavior plan for stopping the moving body outside the area based on the selected travel route.

12. After the step of acquiring obstacle information around the roadside, The method further comprises a step of storing the acquired obstacle information around the roadside, In the step of generating an action plan, The method for generating a behavior plan according to claim 10 or 11, further comprising the step of generating a behavior plan for the mobile object by adding the accumulated information about obstacles around the roadside.

Images