Electronic control device and planning method

Abstract

This electronic control device is mounted on a vehicle, and is provided with: an information acquisition unit that acquires travel environment information relating to a travel environment around the vehicle; a retention risk region estimation unit that estimates, on the basis of the travel environment information, a retention restriction region that is a region in which the movement of a moving body other than the vehicle is obstructed when the vehicle is retained and in which the retention of the vehicle is restricted; and a travel control planning unit that plans travel control of the vehicle on the basis of the estimated retention restriction region.

Description

Technical Field

[0001] The invention relates to an electronic control device and a planning method. Background Art

[0002] In recent years, in order to realize comfortable and safe driving assistance and automatic driving of vehicles, a technology for generating a driving trajectory of a vehicle while taking into account the driving of other vehicles has been proposed. Patent document 1 discloses a path confirmation device, which is a path confirmation device used in a vehicle having a path generation unit for generating a driving plan for driving the vehicle by automatic driving and a driving control unit for controlling the driving of the vehicle according to the generated driving plan, the path confirmation device comprising: a safety distance setting unit for setting a minimum safety distance that the vehicle, which is the vehicle using the path confirmation device, should leave between the vehicle and the obstacle in order to avoid the vehicle from approaching the obstacle; an emergency control unit for judging whether the vehicle is traveling while ensuring the set safety distance, and when the distance between the vehicle and the obstacle is smaller than the safety distance, executing emergency control determined separately from the control according to the driving plan on the vehicle; a caution area setting unit for setting a caution area in an area located farther away from the vehicle than the safety distance from the vehicle and between the vehicle and the moving obstacle when there is a moving obstacle moving on the side of the vehicle in the direction of travel; and a path selection unit for selecting the driving plan in which the vehicle travels without the moving obstacle invading the set caution area.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: International Publication No. 2022 / 025087 Summary of the invention

[0006] Problems to be solved by the invention

[0007] The invention described in Patent Document 1 has room for improvement in terms of smooth vehicle passing.

[0008] Means used to solve problems

[0009] The first embodiment of the electronic control device of the present invention is an electronic control device mounted on a vehicle, comprising: an information acquisition unit, which acquires driving environment information related to the driving environment around the vehicle; a detention risk area estimation unit, which estimates a detention restriction area based on the driving environment information, and the detention restriction area is an area that hinders the movement of mobile bodies other than the vehicle when the vehicle is stranded, and is an area that restricts the detention of the vehicle; and a driving control planning unit, which plans the driving control of the vehicle based on the estimated detention restriction area.

[0010] The second mode of the planning method of the present invention is a planning method executed by an electronic control device mounted on a vehicle, which includes: obtaining driving environment information related to the driving environment around the vehicle; based on the driving environment information, estimating a detention restriction area, which is an area that hinders the movement of mobile bodies other than the vehicle when the vehicle is stranded and is an area that restricts the detention of the vehicle; and planning the driving control of the vehicle based on the estimated detention restriction area.

[0011] Effects of the Invention

[0012] According to the present invention, smooth vehicle passing can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a functional block diagram showing the configuration of the vehicle system in the first embodiment.

[0014] Figure 2 This is a diagram showing an example of a driving scene.

[0015] Figure 3 This is a diagram showing a structural example of data stored in a coordinated action data group.

[0016] Figure 4 Yes means Figure 2 FIG. 1 is a diagram showing examples of a moving body path prediction data set and a moving body trajectory prediction data set in a driving scenario.

[0017] Figure 5 Yes means Figure 2 A diagram showing an example of a collision risk map data set and a retention risk map data set in a driving scenario.

[0018] Figure 6 This is a diagram showing the correlation between functions implemented by the electronic control device.

[0019] Figure 7 It is a flowchart showing the processing of the coordinated action planning department.

[0020] Figure 8 This is a flowchart showing the processing of the mobile object behavior prediction unit.

[0021] Fig. 9 : is a flowchart showing the processing of the collision risk map generating unit.

[0022] Fig.10 This is a flowchart showing the processing of the detention risk map generating unit.

[0023] Fig.11 This is a flowchart showing the processing of the travel control planning unit.

[0024] Fig.12 It means use Figure 2 The above figure shows how the trajectory of the vehicle is planned based on the collision risk area and the detention risk area in the scenario.

[0025] Fig.13 It is right Figure 2 Figures illustrating the operation of vehicle systems in different scenarios.

[0026] Fig.14 This is a diagram showing a part of a driving scenario for explaining the operation of the second embodiment and the operation of the vehicle system in the driving scenario.

[0027] Fig.15 FIG. 1 is a diagram showing an example of a driving scene for explaining the operation of the second embodiment.

[0028] Fig.16 It is a diagram showing a processing example of the mobile object behavior prediction unit in the third embodiment.

[0029] Fig.17 It is a diagram showing a processing example of the detention risk map generating unit in the fourth embodiment.

[0030] Fig.18 It is a functional block diagram showing the configuration of a vehicle system in the fifth embodiment.

[0031] Fig.19 It is a functional configuration diagram of the second travel control planning unit in the fifth embodiment.

[0032] Fig. 20 This is a detailed diagram of the structure of the passing track generation unit.

[0033] Fig.21 This is a flowchart showing the processing of the trajectory generation unit.

[0034] Fig. 22 Yes Fig.21 FIG. 3 is a diagram for explaining a method for generating retreat position and posture candidates in step S3305.

[0035] Fig.23 Yes Fig.21A diagram illustrating a method for generating arrival position candidates in step S3306.

[0036] Fig.24 Yes Fig.21 A diagram illustrating a method for generating track candidates in step S3307.

[0037] Fig.25 It is a transition diagram of the missed vehicle status managed by the management department.

[0038] Fig.26 This is a flowchart showing the processing executed by the management unit in the initial state.

[0039] Fig. 27 This is a diagram showing an example of a passing track and a cancelled track.

[0040] Fig.28 It is a flowchart showing the processing executed by the management unit in the passing car execution state.

[0041] Fig.29 This is a flowchart showing the processing performed by the management unit in the missed vehicle state.

[0042] Fig.30 It is a flowchart showing the processing performed by the management unit in the missed vehicle cancellation state.

[0043] Fig.31 It is a schematic diagram showing the operation of the vehicle based on the processing of the electronic control device.

[0044] Fig.32 It is a diagram showing an example of a scene in which the processing in the sixth embodiment is effective.

[0045] Fig.33 It is a diagram showing an example of trajectory generation in the sixth embodiment.

[0046] Fig.34 It is a diagram showing an example of a scene in which the processing in the seventh embodiment is effective.

[0047] Fig.35 It is a functional configuration diagram of the second travel control planning unit in the eighth embodiment.

[0048] Fig.36 It is a diagram showing an example of a scene in which the processing in the eighth embodiment is effective. DETAILED DESCRIPTION

[0049] - First Embodiment -

[0050] Below, refer to Figures 1 to 13 , a first embodiment of the electronic control device is described.

[0051] (System Configuration)

[0052] Figure 1 This is a functional block diagram showing the configuration of a vehicle system 1 including an electronic control device 3 according to an embodiment of the present invention. The vehicle system 1 is mounted on a vehicle 2. The vehicle system 1 performs appropriate driving assistance and driving control based on the conditions of obstacles such as the driving road and surrounding vehicles around the vehicle 2. The driving assistance also includes presenting information to the driver driving the vehicle 2.

[0053] like Figure 1 As shown, the vehicle system 1 is composed of an electronic control device 3, an external sensor group 4, a vehicle sensor group 5, a map information management device 6, an actuator group 7, and an HMI device group 8. The electronic control device 3, the external sensor group 4, the vehicle sensor group 5, the map information management device 6, the actuator group 7, and the HMI device group 8 are connected via an in-vehicle network N. The in-vehicle network N can be a wired network, a wireless network, or a network in which wired and wireless networks are mixed. In addition, in order to distinguish the vehicle 2 from other vehicles, it is sometimes referred to as the "own vehicle" 2.

[0054] The electronic control device 3 is an ECU (Electronic Control Unit). The electronic control device 3 generates driving control information for driving assistance or automatic driving of the vehicle 2 based on various input information provided from the external sensor group 4, the vehicle sensor group 5, the map information management device 6, etc., and outputs it to the actuator group 7 and the HMI device group 8. The electronic control device 3 has a processing unit 10, a storage unit 30, and a communication unit 40.

[0055] The processing unit 10 is configured to include, for example, a CPU (Central Processing Unit) as a central processing unit. However, in addition to the CPU, it may also include a GPU (Graphics Processing Unit), an FPGA (Field-Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), etc., or may be composed of any one of them. The processing unit 10 has, as its functions, an information acquisition unit 11, a coordinated action planning unit 12, a mobile body action prediction unit 13, a collision risk map generation unit 14, a detention risk map generation unit 15, a driving control planning unit 16, and an information output unit 17. The processing unit 10 may realize them by, for example, executing a prescribed action program stored in the storage unit 30, or may partially or entirely be installed in hardware through an ASIC or the like.

[0056] The information acquisition unit 11 acquires various information from other devices connected to the electronic control device 3 via the vehicle network N, and stores the information in the storage unit 30. For example, the information acquisition unit 11 acquires a sensor detection data group 31 including information related to stationary objects or moving objects around the vehicle 2 detected by the external sensor group 4, a vehicle information data group 32 related to the movement or state of the vehicle 2 detected by the vehicle sensor group 5, etc., and a road environment data group 33 related to the driving road of the vehicle 2 from the map information management device 6, and stores the same in the storage unit 30.

[0057] The coordinated action planning unit 12 plans the necessity and process of coordinated actions between the vehicle 2 and the mobile bodies around the vehicle 2 based on the information such as the sensor detection data group 31, the vehicle information data group 32, and the road environment data group 33 acquired by the information acquisition unit 11 and stored in the storage unit 30, and stores the plans in the storage unit 30 as a coordinated action data group 34. The mobile body action prediction unit 13 predicts the future travel path and trajectory of the mobile bodies around the vehicle 2 included in the sensor detection data group 31. The vehicle information data group 32, the road environment data group 33, and the coordinated action data group 34 are used in the prediction. Then, the mobile body action prediction unit 13 stores the predicted travel path as the mobile body path prediction data group 35 in the storage unit 30, and stores the predicted trajectory as the mobile body trajectory prediction data group 36 in the storage unit 30.

[0058] The collision risk map generation unit 14 estimates the area where there is a risk of collision between the obstacle such as a stationary object or a moving object included in the sensor detection data group 31 and the vehicle 2 and the degree of the collision (hereinafter referred to as "collision risk"), and generates a collision risk map projected on a two-dimensional map. The collision risk map generation unit 14 uses the sensor detection data group 31, the vehicle information data group 32, and the moving object path prediction data group 35 in generating the risk map. Then, the collision risk map generation unit 14 stores the generated collision risk map as a collision risk map data group 37 in the storage unit 30. Hereinafter, the collision risk map generation unit 14 is also referred to as a "collision risk area estimation unit".

[0059] The detention risk map generation unit 15 takes the mobile body designated as the coordinated action object in the coordinated action data group 34 as the object, and estimates the area that hinders the movement of the mobile body when the vehicle 2 is detained, that is, the detention restriction area and the degree of obstruction (hereinafter referred to as "detention risk"). In this estimation, the predicted path of the mobile body obtained from the mobile body path prediction data group 35 is used. Based on the estimation result, the detention risk map generation unit 15 generates a detention risk map that projects the detention risk onto a two-dimensional map, and stores it in the storage unit 30 as a detention risk map data group 38. In addition, "detention" means staying in a certain place or area for more than a specified time, which is equivalent to temporarily stopping or moving at a low speed. Hereinafter, the detention risk map generation unit 15 is also referred to as a "detention restriction area estimation unit".

[0060] The travel control planning unit 16 plans the trajectory that the vehicle 2 should travel based on the vehicle information data group 32, the road environment data group 33, the coordinated action data group 34, the collision risk map data group 37, the retention risk map data group 38, etc., and determines the control command value output to the actuator group 7 for following the planned trajectory. In the case where it is necessary to take coordinated actions with the mobile body around the vehicle 2, the appropriate standby position posture in the next action of the vehicle 2 is determined based on the coordinated action data group 34 and the retention risk map data group 38, and the path and trajectory to reach the standby position posture are planned. The generated planned path and planned trajectory of the vehicle 2, the control command value output to the actuator group 7, etc. are stored in the storage unit 30 as the travel control data group 39.

[0061] The information output unit 17 outputs various information to other devices connected to the electronic control device 3 via the vehicle network N. For example, the electronic control device 3 outputs the control command value determined by the driving control planning unit 16 to the actuator group 7 to control the driving of the vehicle 2. In addition, for example, the electronic control device 3 outputs the collision risk map generated by the collision risk map generation unit 14, the retention risk map generated by the retention risk map generation unit 15, the planned path and planned trajectory generated by the driving control planning unit 16, etc. to the HMI device group 8. In this way, the electronic control device 3 prompts the occupant how the vehicle system 1 interprets the surrounding driving environment and what kind of driving is planned.

[0062] The storage unit 30 is configured to include, for example, a storage device such as a hard disk drive, a flash memory, a ROM (Read Only Memory), and a memory such as a RAM. The storage unit 30 stores the program processed by the processing unit 10, the data group required for the processing, and the like. In addition, as the main storage when the processing unit 10 executes the program, it is also used to temporarily store the data required for the operation of the program. In this embodiment, as information for realizing the functions of the electronic control device 3, a sensor detection data group 31, a vehicle information data group 32, a road environment data group 33, a coordinated action data group 34, a mobile body path prediction data group 35, a mobile body trajectory prediction data group 36, a collision risk map data group 37, a detention risk map data group 38, and a driving control data group 39 are stored.

[0063] The sensor detection data group 31 is a collection of data related to the detection information brought by the external sensor group 4. The detection information is, for example, information related to environmental elements such as stationary objects or moving objects determined by the external sensor group 4 based on its sensor detection information. The vehicle information data group 32 is a collection of data related to the action and state of the vehicle 2. The vehicle information data group 32 includes vehicle information detected by the vehicle sensor group 5 and the like acquired by the information acquisition unit 11. The vehicle information includes, for example, information such as the position of the vehicle 2, the driving speed, the steering angle, the operation amount of the accelerator, and the operation amount of the brake.

[0064] The road environment data group 33 is a collection of data related to the driving roads around the vehicle 2 obtained from the map information management device 6 or the like. The data related to the driving roads include, for example, information related to the shape or attributes (travel direction, speed limit, driving restrictions, etc.) of the road on which the vehicle 2 is traveling or the lanes constituting the road. The coordinated action data group 34 is a diagram showing the state and process of the coordinated action of the vehicle 2 and the mobile bodies around the vehicle 2.

[0065] The moving body path prediction data group 35 is a collection of data related to the future predicted path of the moving body. The moving body track prediction data group 36 is a collection of data related to the future predicted track of the moving body. "Path" does not contain the concept of time, and expresses spatial information about where on the road surface the vehicle is traveling and in what posture. In contrast, "track" adds the concept of time to the path, and expresses information about when and where the vehicle is traveling and in what posture. That is, since "track" is accompanied by time constraints, it is expressed with a specified time range (for example, 5 seconds in the future) as the object.

[0066] The collision risk map data set 37 is a map showing the locations where there is a risk of collision with obstacles such as stationary objects or moving objects around the vehicle 2 and the extent of the risk. The collision risk map data set 37 is represented by, for example, a grid-shaped map. The retention risk map data set 38 is a map showing the areas around the vehicle 2 that hinder the movement of moving objects other than the vehicle 2 when the vehicle 2 is retained and the extent of the hinderance. The retention risk map data set 38 is the same as the collision risk map data set 37 and is represented by a grid-shaped map or the like.

[0067] The travel control data group 39 is a collection of data related to the planning information for controlling the travel of the vehicle 2 generated by the travel control planning unit 16. For example, it includes the planned trajectory of the vehicle 2, the control command value output to the actuator group 7, etc. The communication unit 40 is configured to include a network card that complies with communication standards such as IEEE802.3 or CAN (Controller Area Network). The communication unit 40 sends and receives data with other devices in the vehicle system 1 based on various protocols.

[0068] In addition, in the present embodiment, the communication unit 40 and the processing unit 10 are described separately, but part of the processing of the communication unit 40 may be executed in the processing unit 10. For example, the corresponding hardware device in the communication processing may be located in the communication unit 40, and the other device driver group, communication protocol processing, etc. may be located in the processing unit 10.

[0069] The external sensor group 4 is a collection of devices that detect the state of the surroundings of the vehicle 2. The external sensor group 4 corresponds to, for example, a camera device, a millimeter wave radar, a LiDAR, a sonar, etc. The external sensor group 4 detects environmental elements such as stationary objects or moving objects within a specified range from the vehicle 2, and outputs them to the vehicle network N. "Stationary objects" refer to obstacles that cannot be moved from the location, such as buildings or road ends. "Moving objects" refer to obstacles that can be moved from the location, such as other vehicles other than the vehicle 2, pedestrians, objects falling onto the road, etc. Therefore, even when these movable obstacles are stationary, they are also referred to as "moving objects."

[0070] The vehicle sensor group 5 is a collection of devices that detect various states of the vehicle 2. Each vehicle sensor detects, for example, the position information, driving speed, steering angle, accelerator operation amount, brake operation amount, etc. of the vehicle 2, and outputs them to the vehicle network N. The map information management device 6 is a device that manages and provides digital map information around the vehicle 2. The map information management device 6 is composed of, for example, a navigation device. The map information management device 60, for example, has digital road map data of a specified area including the surroundings of the vehicle 2, and is configured to determine the current position of the vehicle 2 on the map, that is, the road and lane on which the vehicle 2 is traveling, based on the position information of the vehicle 2 output from the vehicle sensor group 5. In addition, the determined current position of the vehicle 2 and the map data of its surroundings are output to the vehicle network N.

[0071] The actuator group 7 is a device group that controls control elements such as steering, braking, and acceleration that determine the behavior of the vehicle. The actuator group 7 controls the behavior of the vehicle based on the driver's operation information on the steering wheel, brake pedal, accelerator pedal, etc., and the control information output from the electronic control device 3. The HMI device group 8 is a device group for the driver and passengers to input information to the vehicle system 1, or the vehicle system 1 to notify the driver and passengers of information. The HMI device group 8 includes a display, a speaker, a vibrator, a switch, etc.

[0072] Figure 2 This is a diagram showing an example of a driving scene for explaining the operation of the present embodiment. Figure 2 Separate from top to bottom, Figure 2 The above picture to Figure 2 The following graph shows the time elapsed. Figure 2 In the driving scenario, on a narrow road 210 where vehicles cannot pass each other, there is a retreat area 211 where the width of a part of the road is widened. In this road environment, the host vehicle 2 has to pass another vehicle 200. Figure 2 In the upper figure of FIG. 2 , an action 252 of the host vehicle 2 retreating toward the action target 262 in the retreat area 211 is depicted. Beside it, an action 251 of the other vehicle 200 standing by at the action target 261 in order not to hinder the action of the host vehicle 2 retreating to the retreat area 211 is depicted.

[0073] In addition, the so-called action target is temporarily set as a standard of the target position and posture of the action step in order to express the action process in the coordinated action, and is different from the actual target position and posture in the driving control plan or the actual action of other vehicles 200. In addition, "standby" refers to a state below a specified speed, including not only zero speed but also extremely low speeds such as creep speed.

[0074] exist Figure 2The lower figure shows the action performed after the action in the upper figure is completed. When the host vehicle 2 reaches the action target 262 of the retreat area 211, the other vehicle 200 moves toward the action target 263 (action 253) because it is in a state where it can pass the vehicle. Then, the host vehicle 2 moves toward the action target 264 (action 254) after the other vehicle 200 disappears from the vicinity, completing the coordinated action related to passing the vehicle. In this way, the coordinated action is expressed between the host vehicle 2 and other moving bodies through a combination of action steps with a dependency relationship. The action step is characterized by the standard of the target position posture of the action target at the end point of the action step.

[0075] In addition, not only Figure 2 For example, in this embodiment, the vehicle 2 and the other vehicle 200 do not communicate with each other and predict each other's actions. Figure 2 The smooth passing shown in the figure, however, in this embodiment, the action is explained on the premise that the other party's action can be correctly predicted. In addition, the vehicle 2 and other vehicles 200 can also communicate and send subsequent actions to each other.

[0076] Figure 3 34 is a diagram showing a structural example of data stored in the coordinated action data group 34. The coordinated action data group 34 stores Figure 2 Information related to the process of the coordinated action described. The coordinated action data group 34 is composed of multiple records, each of which contains an action ID 301, a vehicle ID 302, an action target 303, a dependent action ID 304, etc. The action ID 301 is an identifier of the action step. In the following, when it is expressed as "action XXX", it means that the action ID 301 is "XXX".

[0077] Vehicle ID 302 is information related to the identifier of the action subject of the action step. The subject refers to the vehicle 2 or a mobile object that is the other party of the coordinated action of the vehicle 2, and the IDs used to identify them are used. Action target 303 is information related to the end point of the action step, corresponding to Figure 2 The action target is shown. In addition, the expression form of the action target is not particularly limited, and it can be expressed as the position coordinates corresponding to the end point, can be expressed as an area, or can be expressed as including a posture.

[0078] Dependent action ID 304 is the action ID of the action step that this action step depends on. When dependent action ID 304 is specified, it means that the specified action step must be completed before this action step. For example, since actions 251 and 252 do not have dependent action steps, they are expressed as "N / A". Since actions 253 and 254 depend on actions 252 and 253 respectively, they are recorded as "252" and "253".

[0079] Figure 4 It means about Figure 2 The diagram shows an example of data stored as a moving body path prediction data set 35 and a moving body trajectory prediction data set 36, based on the actions 251 and 253 of other vehicles 200 in the driving scene. The moving body path prediction data set 35 is a collection of data related to the future predicted path of the moving body. The predicted path of the moving body that is the target of the coordinated action is generated for each coordinated action step. Figure 4 The predicted paths 281 and 283 shown correspond to the predicted paths related to the behaviors 251 and 253 of the other vehicles 200, respectively. The moving body trajectory prediction data group 36 is a collection of data related to the predicted future trajectory of the moving body. Figure 4 , the predicted trajectory 271 of the other vehicle 200 is shown. Since the predicted trajectory is not generated for each coordinated action step, but for a predetermined time range in the future, Figure 4 The trajectory of the specified time range in action 251 is shown in FIG.

[0080] Figure 5 Yes means Figure 2 FIG. 3 is a diagram showing an example of a collision risk map data set 37 and a retention risk map data set 38 in a driving scene. In detail, Figure 5 The figure above shows an example of the collision risk map data set 37. Figure 5 The figure below shows an example of the detention risk map data group 38.

[0081] The collision risk map is a map that maps locations where there is a risk of collision between the vehicle 2 and surrounding obstacles such as stationary objects or moving objects, and the degree of the risk. Figure 5 In the example shown in the figure above, the collision risk between the road boundary (road end) as a stationary object and the other vehicle 200 as a moving object is indicated by the dotted shadows indicated by the reference numeral 291. As an example of a representation method of the collision risk map, there is a grid map (grid map). In the grid map, in a specified area specified by a rectangular coordinate system centered on the current position of the vehicle 2, the collision risk value at each position of the coordinate value (x, y) represented by variables for x and y is stored.

[0082] The detention risk map is a map that maps the area where the vehicle 2 is blocked from moving and the detention risk as the degree of the blockage. Figure 5In the example shown, the detention risk area 292, which is the movement of the other vehicle 200 that is the target of the coordinated action, is represented by diagonal hatching. In addition, in the detention risk map, the detention risk can also be arranged in the area where the vehicle 2 cannot travel. Since the detention risk map is used to determine the appropriate waiting position posture of the vehicle 2, in order to search for the area where the vehicle 2 can stay, it is preferable to arrange the risk not only in the area where the movement of the target mobile body is hindered, but also in the area where the vehicle 2 cannot travel originally.

[0083] However, in the example shown in the present embodiment, since the presence or absence of a collision risk and a detention risk is illustrated by the presence or absence of a shadow, the degree of risk is not shown in the accompanying drawings. The degree of risk can be represented by a binary value of the presence or absence of a risk, or can be represented by a continuous value such as 0 to 100. Hereinafter, an area where there is a collision risk is also referred to as a "collision risk area", and an area where there is a detention risk is also referred to as a "detention risk area". Furthermore, the collision risk area and the detention risk area are collectively referred to as a "risk area".

[0084] exist Figure 5 In the example shown in the figure below, as in the collision risk map, a detention risk is also configured at the roadside as a stationary object, that is, the area represented by dotted shading. However, since the meaning of the non-drivable area is different from the original detention risk, it is desirable to configure it so that both can be identified on the detention risk map. Figure 5 In the example, the risk level is determined by the degree of detention, and the area that cannot be driven is shown with dotted shading, and the original detention risk area is shown with diagonal shading. The risk level can be shown in discrete levels such as high, medium, and low, or in continuous numerical values.

[0085] Based on the information obtained from the external sensor group 4, the vehicle sensor group 5, the map information management device 6, etc., the electronic control device 3 determines the collision risk and the detention risk with obstacles such as stationary objects or moving objects existing around the vehicle 2, maps them, and generates and outputs the driving control information of the vehicle 2. The actuator group 7 controls each actuator of the vehicle 2 according to the above-mentioned driving control information. In this way, the driving control of the vehicle 2 is realized. In addition, when controlling the driving of the vehicle 2, the electronic control device 3 generates HMI information as information to be notified to the driver and passengers, and outputs it to the HMI device group 8. In this way, the driver can be made aware of the risks in driving and promote safe driving, or assist in coordinated actions with other vehicles, and the state of the vehicle system 1 in automatic driving can be prompted to the driver and passengers.

[0086] Figure 6 The electronic control device 3 is configured to execute the functions in an appropriate order. Figure 1The processes of the information acquisition unit 11, the coordinated action planning unit 12, the mobile body behavior prediction unit 13, the collision risk map generation unit 14, the retention risk map generation unit 15, the travel control planning unit 16 and the information output unit 17 are shown. For example, a series of processes are regularly executed every 100 ms.

[0087] The information acquisition unit 11 acquires necessary information from other devices via the vehicle network N and stores it in the storage unit 30. The information acquisition unit 11 acquires the sensor detection data group 31 from the external sensor group 4, the vehicle information data group 32 from the vehicle sensor group 5, and the road environment data group 33 from the map information management device 6, and transfers them to the subsequent processing unit.

[0088] The coordinated action planning unit 12 determines whether coordinated action with the mobile bodies around the vehicle 2 is necessary or not based on the sensor detection data group 31, the vehicle information data group 32, and the road environment data group 33 obtained from the information acquisition unit 11. When it is determined that coordinated action is necessary, the coordinated action planning unit 12 determines and manages the coordinated action process with the target mobile body. Then, the coordinated action planning unit 12 outputs the coordinated action data group 34 related to the coordinated action process to the mobile body behavior prediction unit 13 and the driving control planning unit 16 respectively. When it is determined that coordinated action is not necessary, the coordinated action planning unit 12 may not perform special processing, or may output the determination that coordinated action is not necessary to the information output unit 17 via the HMI device group 8.

[0089] The mobile body behavior prediction unit 13 predicts the path and trajectory related to the mobile body around the vehicle 2, and generates a mobile body path prediction data group 35 and a mobile body trajectory prediction data group 36. The mobile body behavior prediction unit 13 uses the sensor detection data group 31 and the road environment data group 33 obtained from the information acquisition unit 11 and the coordinated action data group 34 output from the coordinated action planning unit 12 in these generation. The mobile body path prediction data group 35 is output to the retention risk map generation unit 15 together with the coordinated action data group 34, and the mobile body trajectory prediction data group 36 is output to the collision risk map generation unit 14.

[0090] The collision risk map generation unit 14 estimates the area where there is a risk of collision with the vehicle 2 and the degree of the collision risk in each area for each obstacle included in the sensor detection data group 31 based on the vehicle information data group 32 and the moving body trajectory prediction data group 36. Then, the collision risk map generation unit 14 maps the calculation results to generate a collision risk map data group 37. The generated collision risk map data group 37 is output to the travel control planning unit 16.

[0091] The retention risk map generation unit 15 extracts the predicted path information of the mobile body of the coordinated action object based on the coordinated action data group 34 and the mobile body path prediction data group 35, and determines the area that hinders the action of the mobile body when the vehicle 2 is detained. In addition, the retention risk map generation unit 15 determines the area where driving is not allowed based on the information such as driving restrictions contained in the sensor detection data group 31 and the road environment data group 33. The retention risk map generation unit 15 combines this information, estimates the area where there is a risk of detention and the degree of detention risk in each area, and maps the estimation results to generate the retention risk map data group 38. The generated retention risk map data group 38 is output to the driving control planning unit 16.

[0092] The travel control planning unit 16 plans the trajectory that the vehicle 2 should travel based on the coordinated action data group 34, the collision risk map data group 37, the retention risk map data group 38, etc., and generates control command values ​​that follow the trajectory. Then, the travel control data group 39 containing information such as the control command values ​​and various input information used for information presentation in the HMI device group 8 are output to the information output unit 17. The information output unit 17 outputs the control command values ​​to the actuator group 7 based on the travel control data group 39. In addition, the HMI device group 8 outputs information for presentation to the occupant based on the coordinated action data group 34, the collision risk map data group 37, and the retention risk map data group 38.

[0093] Below, use Figure 2 The operation of the electronic control device 3 will be described in detail with reference to the driving scenario shown.

[0094] (Coordination of the Action Planning Department 12)

[0095] Figure 7 is a flowchart showing the processing of the coordinated action planning unit 12. First, in step S501, the coordinated action planning unit 12 obtains the sensor detection data group 31, the vehicle information data group 32, and the road environment data group 33 as driving environment information. Next, in step S502, the coordinated action planning unit 12 determines whether the current driving road environment is difficult to pass other vehicles. For example, the coordinated action planning unit 12 uses the information such as the number of lanes and road width of the current road contained in the road environment data group 33 to determine whether it is difficult to pass other vehicles.

[0096] When the coordinated action planning unit 12 determines that it is not difficult to pass other vehicles (No in step S502), it is deemed that no coordinated action is required, and in step S506, the coordinated action data group 34 of the storage unit is reset, and the process ends. Figure 7When the coordinated action planning unit 12 determines that it is difficult to pass another vehicle (Yes in step S502 ), it determines whether there is another vehicle (oncoming vehicle) to be passed ahead based on the sensor detection data set 31 (step S503 ).

[0097] If the coordinated action planning unit 12 determines that there is no other vehicle in front of the vehicle (No in step S503), the process proceeds to step S506 and ends. Figure 7 When the coordinated action planning unit 12 determines that there is another vehicle ahead that is a target of passing (yes in step S503), it determines in step S504 a coordinated action process for achieving passing with the other vehicle, and in step S505 stores the coordinated action data set 34 in the storage unit 30, and ends. Figure 7 Processing shown.

[0098] The coordinated action process is determined by, for example, the positional relationship of the temporary retreat area for passing vehicles. Figure 2 In the case of the scenario, since the avoidance area 211 is located on the left side relative to the traveling direction of the host vehicle 2, the host vehicle 2 naturally avoids in the driving environment of left-hand traffic. Figure 2 and Figure 3 In addition, when the host vehicle 2 and other vehicles 200 complete the action steps according to the coordinated action process, the action steps as the current object are updated. In this case, the action steps that have been completed are removed from the coordinated action process.

[0099] (Processing of Mobile Object Behavior Prediction Unit 13)

[0100] Figure 8 1 is a flowchart showing the processing of the mobile body behavior prediction unit 13. First, in step S601, the mobile body behavior prediction unit 13 obtains the sensor detection data group 31, the road environment data group 33, and the coordinated action data group 34, and proceeds to step S602. The mobile body behavior prediction unit 13 sets all the mobile bodies included in the sensor detection data group 31 as processing target mobile bodies one by one in order, and in steps S602 to S607, predicts the driving path and driving track of the processing target mobile body.

[0101] In step S602, the mobile behavior prediction unit 13 determines whether there is an unprocessed mobile body. If the mobile behavior prediction unit 13 determines that there is no unprocessed mobile body (No in step S602), the process ends. Figure 8 When the moving object behavior prediction unit 13 determines that there is an unprocessed moving object, the process proceeds to step S603.

[0102] In step S603, the mobile body behavior prediction unit 13 determines whether the processing object is designated as a coordinated action object in the coordinated action data group 34. If the mobile body behavior prediction unit 13 determines that the processing object mobile body is designated as a coordinated action object, it proceeds to step S604. If it determines that the processing object mobile body is not designated as a coordinated action object, it proceeds to step S607. In step S607, the mobile body behavior prediction unit 13 predicts the driving path and driving track of the processing object mobile body based on the information such as lanes and traffic regulations included in the road environment data group 33, and proceeds to step S606.

[0103] In step S604, the mobile body behavior prediction unit 13 predicts a travel path for each coordinated behavior step corresponding to the processing target mobile body in the coordinated behavior data group 34. Figure 3 The judgment is made based on whether the vehicle ID shown is consistent with the ID of the processing object moving body. In the case of a coordination action step in which the processing object moving body is the current object, the driving path for the action target 303 is predicted based on the current state (position, posture, speed, etc.) of the processing object moving body, the state of a stationary object or other moving body (including this vehicle 2). In the case of a coordination action step in which the processing object moving body is not the current object, similarly, the driving path for the action target 303 of the coordination action step that was previously scheduled to be implemented by the processing object moving body is predicted. Figure 4 In the example shown, a predicted path 281 for the action 251 which is the current target coordinated action step and a predicted path 283 for the action 253 which is the next target coordinated action step are generated.

[0104] Next, in step S605, the mobile body action prediction unit 13 predicts the driving trajectory of the processing object mobile body based on the predicted path in each coordinated action step generated in step S604, and enters step S606. The prediction of the driving trajectory is different from the driving path, and is predicted within a specified time range. Therefore, based on the coordinated action step as the current object, the position, posture, speed, etc. within the specified time range are estimated according to the current state (position, posture, speed, etc.) of the processing object mobile body. If the current coordinated action step is completed within the specified time, continue to predict the next coordinated action step. Figure 4 In the example shown, it is assumed that the other vehicle 200 is moving at a very low speed, and a predicted trajectory 271 is generated.

[0105] In step S606, the mobile body behavior prediction unit 13 stores the driving path and driving track of the processing target mobile body predicted in step S605 or step S607 in the storage unit 30 as the mobile body path prediction data group 35 and the mobile body track prediction data group 36. Then, the process returns to step S602 and the process is repeated until there is no unprocessed mobile body MO.

[0106] (Processing of Collision Risk Map Generator 14)

[0107] Fig. 9 is a flowchart showing the processing of the collision risk map generation unit 14. First, in step S701, the collision risk map generation unit 14 obtains the sensor detection data group 31, the vehicle information data group 32, and the moving object trajectory prediction data group 36. Next, in step S702, the collision risk map generation unit 14 calculates the area of ​​collision risk and its degree for the stationary object included in the sensor detection data group 31. Since the stationary object does not move, the area where the stationary object exists directly becomes the area with collision risk regardless of the passage of time.

[0108] Then, in step S703, the collision risk map generation unit 14 calculates the area and degree of collision risk for the moving body included in the sensor detection data group 31. Since the moving body has the possibility of moving, it is desired to determine the area with collision risk based on the moving body trajectory prediction data group 36, taking into account the influence of the passage of time on the movement. For example, the probability distribution of each moving direction of the moving body and the probability distribution of each moving speed can also be calculated to calculate the degree of collision risk. In the next step S704, the collision risk map generation unit 14 maps the collision risks around the vehicle 2 calculated in steps S702 and S703 into a collision risk map. As described above, Figure 5 The figure above shows Figure 2 The example of the collision risk map in the scene shown in the figure above. The road end portion as a stationary object and the predicted track area of ​​the other vehicle 200 as a moving object are represented as collision risks. In the next step S705, the collision risk map generation unit 14 stores the generated collision risk map as a collision risk map data set 37 in the storage unit 30, and ends. Fig. 9 Processing shown.

[0109] (Processing of the Stay Risk Map Generator 15)

[0110] Fig.10It is a flowchart showing the processing of the detention risk map generation unit 15. First, in step S801, the detention risk map generation unit 15 obtains the sensor detection data group 31, the road environment data group 33, the coordinated action data group 34, and the mobile body path prediction data group 35. In the next step S802, the detention risk map generation unit 15 refers to the coordinated action data group 34 to determine whether there is a mobile body that is the object of coordinated action (hereinafter referred to as "coordinated mobile body"). The detention risk map generation unit 15 enters step S809 when it is determined that there is no coordinated mobile body. When it is determined that there is a coordinated mobile body, the detention risk for the coordinated mobile body is calculated and mapped in steps S803 to S808 as described below.

[0111] In step S803, the detention risk map generation unit 15 refers to the coordination action data group 34 and determines the coordination action step of the coordinated moving body to be implemented next (hereinafter referred to as the "next step on the other side") for the coordination action step of the current object, the vehicle 2. Figure 3 In the case where the coordinated action step currently targeted by the host vehicle 2 is action 252, the next step of the other party is action 253. By searching for an entry whose dependent action ID 304 indicates the coordinated action step of the host vehicle 2, the next step of the other party can be determined.

[0112] Next, in step S804, the retention risk map generation unit 15 refers to the mobile body path prediction data group 35, extracts the predicted path corresponding to the next step of the other party, and estimates the area where the coordinated mobile body moves in the next step of the other party, that is, the predicted action area. The predicted action area is obtained, for example, by calculating the area through which the coordinated mobile body passes according to the predicted path. The shape of the coordinated mobile body is obtained, for example, by referring to the recognition result of the external sensor group 4 included in the sensor detection data group 31. Since the recognition result of the external sensor group 4 and the predicted path contain errors, it is desirable to set the predicted action area in consideration of their margins.

[0113] Next, in step S805, the detention risk map generation unit 15 identifies the unfinished steps on the other side of the mobile body MO that are scheduled to be implemented and have not been completed before the next step on the other side. Figure 3 In the case where the next step of the other party is action 253, it corresponds to action 251. In the next step S806, the detention risk map generation unit 15 estimates the area where the coordinated moving body moves in the uncompleted step of the other party, that is, the predicted action pre-area, in the same process as step S804.

[0114] In the next step S807, the detention risk map generation unit 15 calculates the area and degree of detention risk based on the predicted action area and predicted action pre-area estimated in step S804 and step S806, and maps the result into a detention risk map in step S808. For example, the detention risk is set to a uniform degree in the area of ​​the predicted action area and the predicted action pre-area. In addition, for example, a relatively low detention risk may be set for the area of ​​the predicted action area and the predicted action pre-area within a certain distance. An embodiment of making the detention risk have a degree is Fig.14 and Fig.15 To be described later.

[0115] In addition, the reason why the predicted path of the next step of the other side implemented by the coordinated moving body after the current coordinated action step of the host vehicle 2 and the unfinished unfinished step of the other side before that is set as the stranded risk is as follows. That is, this is because the state of the standby position and posture at the end of the current coordinated action step of the host vehicle 2 will have a direct impact. If the standby position and posture of the host vehicle 2 hinder the coordinated action step of the coordinated moving body, the coordinated moving body cannot move, resulting in a stalemate state.

[0116] After the mapping of the detention risk of the coordinated mobile body is completed through the processing of steps S803 to S808, the detention risk map generation unit 15 maps the non-travelable area on the detention risk map in step S809. Then, in the next step S810, the detention risk map generation unit 15 stores the detention risk map as the detention risk map data group 38 in the storage unit 30. The non-travelable area corresponds to, for example, an area where a stationary object exists, a prohibited travel area represented by the road environment data group 33, etc. The risk level when mapping the non-travelable area can be identifiably recorded as the detention risk of the coordinated mobile body.

[0117] In addition, by using the collision risk map together, it is possible to refer to information related to the prohibited driving area, so it is sufficient to map the detention risk to a minimum in the detention risk map. Figure 5 The figure below shows Figure 2 An example of a detention risk map for the scenario above. Figure 5 In the lower figure, the predicted action areas corresponding to the action 251 (predicted path 281 ) and the action 253 (predicted path 283 ) of the other vehicle 200 are represented as a stay risk area 292 .

[0118] (Processing of the Travel Control Planning Unit 16)

[0119] Fig.111 is a flowchart showing the processing of the driving control planning unit 16. First, in step S901, the driving control planning unit 16 obtains the sensor detection data group 31, the vehicle information data group 32, the coordinated action data group 34, the collision risk map data group 37, and the retention risk map data group 38. Next, in step S902, the driving control planning unit 16 refers to the coordinated action data group 34 to determine whether there is a coordinated moving body as a moving body for coordinated action. The driving control planning unit 16 proceeds to step S8907 when it is determined that there is no coordinated moving body, and proceeds to step S903 when it is determined that there is a coordinated moving body.

[0120] In step S903, the travel control planning unit 16 refers to the retention risk map included in the retention risk map data group 38, and first determines the target standby position posture in the current coordinated action step of the host vehicle 2. Then, in step S904, the travel control planning unit 16 refers to the collision risk map included in the collision risk map data group 37, generates a trajectory for the target standby position posture determined in step S903, and proceeds to step S905. In step S907, the travel control planning unit 16 generates a trajectory for normal travel, and proceeds to step S905.

[0121] When the track is generated in step S904 or step S907, the driving control planning unit 16 generates driving control information based on the track in step S905. In the next step S906, the driving control planning unit 16 stores the driving control information generated in step S905 as the driving control data group 39 in the storage unit 30, and ends. Fig.11 Processing shown.

[0122] use Fig.12 , examples of step S903 and step S904 are explained. Fig.12 It means use Figure 2 The collision risk area 291 and the retention risk area 292 in the scene in the above figure are used to plan the trajectory 1001 of the host vehicle 2. In step S903, referring to the retention risk area 292, Figure 2 The surrounding of the action target 262 of the current coordinated action step of the host vehicle 2 is searched for an area without a risk of detention. In the case of this scenario, since there is no risk of detention at the position of the action target 262, the position of the action target 262 is set to the target standby position posture 1011. Then, in step S904, with reference to the collision risk area 291, a track is planned in which the passing area of ​​the host vehicle 2 does not overlap with the collision risk for the target standby position posture 1011.

[0123] As described above, by effectively utilizing the retention risk map, the standby position posture when the current coordinated action step is completed does not overlap with the action area of ​​the next coordinated action step of the other vehicle 200, so the coordinated action of the other vehicle 200 is not hindered. In addition, in this embodiment, step S903 and step S904 are described separately, but they can also be implemented at the same time. That is, it is also possible to search for the conditions of the target standby position posture that does not overlap with the retention risk map and the track that does not overlap with the collision risk map at the same time.

[0124] Fig.13 Is the description and Figure 2 A diagram illustrating the operation of the vehicle system 1 in different scenarios. Fig.13 In addition to Figure 2 In addition to the composition of the scene, there is also a stationary object 1110 that becomes a traffic obstacle. Fig.13 In the scene of the above figure, the mobile body behavior prediction unit 13 predicts the driving path 1111 that avoids the stationary object 1110 based on the behavior 251 of the other vehicle 200 in step S604. Therefore, the detention risk map generation unit 15 infers the winding predicted behavior area 1134 as a detention risk based on the driving path 1111 and the like in steps S803 to S808, and generates the detention risk map 1103.

[0125] When the travel control planning unit 16 calculates the target waiting position and posture of the behavior 252 of the host vehicle 2 using the retention risk map 1103 in step S903, Fig.13 The portion indicated by the reference numeral 1131 overlaps with the detention risk. Therefore, the driving control planning unit 16 searches for a standby position posture that does not overlap with the detention risk in the vicinity of the action target 262, and determines a target standby position posture 1133. Since the standby position posture does not overlap with the action area of ​​other vehicles 200, it does not hinder the coordinated action of other vehicles 200. As described above, in the coordinated action with other mobile bodies, the action area of ​​the coordinated action step of the mobile body is predicted as the detention restriction area, and the standby position posture of the coordinated action step of the vehicle 2 is set in a manner to avoid it, thereby enabling the coordinated action to be smoothly implemented in various scenarios without falling into a stalemate.

[0126] According to the above-described first embodiment, the following effects can be obtained.

[0127] (1) The electronic control device 3 is mounted on the vehicle 2. The electronic control device 3 comprises: an information acquisition unit 11, which acquires driving environment information related to the driving environment around the vehicle 1, namely, a sensor detection data group 31, a vehicle information data group 32 and a road environment data group 33; a detention risk map generation unit 15, which estimates a detention restriction area based on the driving environment information, and the detention restriction area is an area that hinders the movement of mobile bodies other than the vehicle 2 when the vehicle 2 is detained, and is an area that restricts the detention of the vehicle 2; and a driving control planning unit 16, which plans the driving control of the vehicle 2 based on the estimated detention risk map. Therefore, if Fig.12 and Fig.13 As shown in the example, smooth passing can be achieved.

[0128] (2) When the vehicle 2 needs to stay in a predetermined area, the travel control planning unit 16 Fig.11 In step S903, the vehicle 200 is controlled to stay in a predetermined area in an area that does not overlap with the stay restriction area. Therefore, the vehicle 200 waits at a position that does not overlap with the track of other vehicles 200, so smooth passing can be achieved.

[0129] (3) A mobile body other than the vehicle 2 refers to a mobile body existing around the vehicle and included in the driving environment information. The electronic control device 3 includes a coordinated action planning unit 12 that determines a coordinated action process to be coordinated with the mobile body. The retention restriction area is an area that hinders the movement of the mobile body in the coordinated action process when the vehicle 2 is retained. Therefore, the vehicle 2 avoids being retained in the retention risk area that hinders the movement of other vehicles 200, and thus can achieve smooth passing with other vehicles 200.

[0130] (4) The retention risk map generation unit 15 is as follows Fig.10 As shown, the estimated movement area through which the moving body may pass during the movement of the moving body in the coordinated movement process is estimated, and the stay restriction area is estimated based on the estimated movement area. Therefore, it is possible to prevent the passage of other moving bodies from being obstructed.

[0131] (5) The driving control planning unit 16 is as follows: Fig.11 As shown in steps S903 and S904, the target waiting position and posture of the vehicle 2 during the coordinated action are planned so as not to overlap with the stay restriction area.

[0132] (6) The electronic control device 3 includes a collision risk map generating unit 14, which estimates a collision risk area where there is a risk of collision between the vehicle and an obstacle based on the driving environment information. The driving control planning unit 16 plans driving control such that the vehicle 2 does not enter the collision risk area and the vehicle 2 does not stay in the stay risk area.

[0133] - Second Embodiment -

[0134] Reference Figure 14-15 , a second embodiment of the electronic control device is described. In the following description, the same reference numerals are used for the same components as those in the first embodiment, and the differences are mainly described. The points not specifically described are the same as those in the first embodiment. In this embodiment, the difference from the first embodiment mainly lies in making full use of the difference in the degree of detention risk in the detention risk map to determine the appropriate standby position posture.

[0135] Fig.14 1 is a diagram showing a driving scenario for explaining the operation of the second embodiment and a part of the operation of the vehicle system 1 in the driving scenario. Driving scenario 1200 and driving scenario 1201 show the flow of coordinated operation with another vehicle 1202. Fig.14 In the scenario 1200, the vehicle 2 is traveling from the right side to the left side, and the coordinated action planning unit 12 expects other vehicles 1202 traveling on the side where the retreat area exists to retreat to the retreat area. In the driving scenario 1200, because the vehicle 2 is too close to the other vehicle 1202, it hinders the other vehicle 1202 from moving to the retreat area. Therefore, the vehicle 2 performs the action 1211 of retreating. The subsequent coordinated action process is the driving scenario 1201 and Figure 2 The driving scenario is the same as the one in the figure below.

[0136] Fig.14 Reference numerals 1202 and 1203 respectively represent a collision risk map and a retention risk map in the action 1211 of the driving scene 1200. When the retention risk of other vehicles 1202 is mapped to the retention risk map in steps S803 to S808, the retention risk map generation unit 15 in this embodiment not only configures a main retention risk area 292-1 corresponding to a predicted action area related to the action 1212 of other vehicles 1202, but also configures a low retention risk area 292-2 with a relatively low risk level around it.

[0137] The main retention risk area 292-1 is an area that definitely hinders the action 1212 of other vehicles 1202. The low retention risk area 292-2 is an area where it is likely that other vehicles 1202 will have difficulty in performing actions 1212. The low retention risk area 292-2 exists on the periphery of the main retention risk area 292-1, and is particularly widely set in a direction parallel to the traveling direction of the own vehicle.

[0138] When the vehicle 2 approaches the action area of ​​the other vehicle 1202, the driver of the other vehicle 1202 is required to have higher operation accuracy than necessary and feels stressed. Therefore, the driver should back up to ensure sufficient space for the action 1212. The retention risk 1233 is set in this way in consideration of safety. In step S903, the driving control planning unit 16 determines the target standby position posture 1230 in a manner that avoids the retention risk 1233 with a relatively low risk level as much as possible, thereby ensuring sufficient space for the action 1212 of the other vehicle 1202. In this way, it is possible to suppress the pressure on the driver of the other vehicle 1202.

[0139] Fig.15 is a diagram showing an example of a driving scene for explaining the operation of the second embodiment. Fig.14 The same driving scenario is different in that there is another other vehicle 1253 behind the vehicle 2. In this driving scenario, since the collision risk area 1284 where there is a risk of collision with the other vehicle 1253 is set behind the vehicle 2, the vehicle 2 cannot retreat as shown by the reference numeral 1280. Therefore, there is no space to completely avoid the low retention risk area 292-2 with a relatively low risk level. In this case, the electronic control device 3 allows the target standby position posture of the vehicle 2 to overlap with the low retention risk area 292-2 with a relatively low risk level.

[0140] The retention risk 1283 is set to take into account the ease of driving of the other vehicle 1252, and does not necessarily hinder the action 1262 of the other vehicle 1252. This reflects that when there is not enough space between the two vehicles, passing each other in a close environment is a last resort. In addition, if the risk levels of the retention risks 1282 and 1283 are set to the same, it will be difficult to Fig.14 and Fig.15 Respond to the situation as required.

[0141] As described above, by considering not only the predicted action area of ​​the mobile body of the coordinated action object but also the influence on the ease of action of the mobile body, by setting a detention risk wider than the predicted action area, smooth coordinated action taking into account the ease of action of the mobile body can be achieved. In addition, by setting the detention risk in a manner that can identify the risk level in the area that completely hinders the action of the mobile body of the coordinated action object and the area that affects the ease of action of the mobile body, it is possible to determine the appropriate target standby position posture corresponding to the situation, and smooth coordinated action can be achieved.

[0142] According to the second embodiment described above, the following effects can be obtained.

[0143] (7) The detention risk area includes information related to the degree of difficulty of action given to the mobile body. That is, there is a main detention risk area 292-1 with a relatively high risk level and a low detention risk area 292-2 with a relatively low risk level. When there is no target standby position posture that does not overlap with the main detention risk area 292-1 and the low detention risk area 292-2, the travel control planning unit 16 allows planning of a target standby position posture that overlaps with the low detention risk area 292-2.

[0144] -Third Embodiment-

[0145] Reference Fig.16 , a third embodiment of the electronic control device is described. In the following description, the same reference numerals are used for the same components as those in the first embodiment, and the differences are mainly described. The points not specifically described are the same as those in the first embodiment. In this embodiment, the main difference from the first embodiment is that the mobile body behavior prediction unit 13 considers the possibility of the mobile body existing in the blind spot.

[0146] In addition to the processing in the first embodiment, the mobile body behavior prediction unit 13 in this embodiment further performs the following processing. That is, the mobile body behavior prediction unit 13 refers to the sensor detection data group 31 and the road environment data group 33 to predict that there is a mobile body in the blind spot and is moving in a manner that hinders the movement of the host vehicle 2. Fig.16 , a specific example is described.

[0147] Fig.16 FIG. 2 is a diagram showing an example of processing performed by the mobile body behavior prediction unit 13 in the third embodiment. Fig.16 The diagram includes a driving scene 1301, a driving scene 1302, a collision risk map 1303, and a detention risk map 1304. In the driving scene 1301, the vehicle 2 is parked on a congested road. There is a fork road on the left side just in front of the vehicle 2, which becomes a blind spot of the sensor of the vehicle 2, but there is a possibility that other vehicles will intrude on the road. In this case, in order to prevent other vehicles from appearing at the fork road in the future, it is hoped that the vehicle 2 will not be stranded in the area near the fork road so as not to hinder the movement of other vehicles.

[0148] In this case, the retention risk map can also be used. In the first and second embodiments of the present invention, the mobile behavior prediction unit 13 calculates the mobile body MO detected by the external sensor group 4 according to Figure 8The processing flow predicts the driving path and driving trajectory of the moving body MO, but in this embodiment, a virtual moving body VMO is also included as the moving body MO. The virtual moving body VMO is a moving body that may not be detected in the blind spot of the external sensor group 4, or a moving body that does not exist at present but may appear in the future.

[0149] exist Fig.16 In the driving scenario, assuming that other vehicles appear at the fork in the road in the future, an imaginary other vehicle 1311 is configured as shown in the driving scenario 1302. The mobile body behavior prediction unit 13 predicts a possible driving path for the imaginary other vehicle 1311. Since the concept of time is uncertain for the imaginary mobile body, the driving trajectory is not predicted. In addition, since the state of the imaginary mobile body is uncertain, there are multiple candidates for actions (action 1312 and action 1313), and the mobile body behavior prediction unit 13 predicts the driving paths for all candidates. Then, the detention risk map generation unit 15 configures the detention risk as shown in the detention risk map 1304 according to the predicted path of the imaginary mobile body generated by the mobile body behavior prediction unit 13.

[0150] exist Fig.11 In the processing flow, since the other imaginary vehicles 1311 are not the objects of coordinated action, a negative judgment is made in step S902, and the driving control planning unit 16 generates a normal driving track in step S907. At this time, the driving control planning unit 16 uses the detention risk map to determine the waiting place in congestion. That is, the driving control planning unit 16 generates a track in a way that does not stop in the area corresponding to the detention risk map 1304. Fig.16 As in the driving scenario of FIG. 1 , when the preceding vehicle 1320 of the host vehicle 2 stops immediately in front of the fork, the collision risk of the preceding vehicle 1320 exists in front, as shown in the collision risk diagram 1303. Therefore, it is determined that the host vehicle 2 cannot pass the retention risk 1323, and the host vehicle 2 does not move forward but waits at the current position.

[0151] In addition, if the preceding vehicle 1320 moves forward and a sufficient space is created between the collision risk of the preceding vehicle 1320 and the retention risk 1323, it is determined that the host vehicle 2 can pass through the retention risk 1323 without being retained, and a forward trajectory is generated. In addition, retention means staying in a specified place or area for a certain period of time or more, so even if it is not possible to pass through the retention risk at a certain moment, it is possible to enter the retention risk in the following cases. That is, when the vehicle before the preceding vehicle starts to move forward, it is predicted that it will be able to pass in the near future and it can be determined that the time spent in the retention risk area converges to within a specified value, it is possible to enter the retention risk.

[0152] According to the third embodiment described above, the following effects can be obtained.

[0153] (8) Mobile objects other than the vehicle 2 refer to mobile objects that are estimated to appear in the future around the vehicle 2 based on the driving environment information, such as Fig.16 Therefore, in the present embodiment, by assuming that there are other vehicles in the blind spot of the own vehicle 2, the detention risk map is generated, so as not to hinder the progress of the vehicle existing in the blind spot.

[0154] (9) The travel control planning unit 16 plans travel control so that the time spent in the stay restriction area falls within a predetermined value.

[0155] -Fourth Embodiment-

[0156] Reference Fig.17 , a fourth embodiment of the electronic control device is described. In the following description, the same components as those in the first embodiment are marked with the same figure marks, and the differences are mainly described. The points not specifically described are the same as the first embodiment. In this embodiment, the main difference from the first embodiment is that the detention risk map generation unit 15 also maps the areas where parking is not allowed into the detention risk map. The detention risk map generation unit 15 in this embodiment performs the following processing in addition to the processing in the first embodiment. That is, the detention risk map generation unit 15 reflects the traffic rules related to parking obtained from the road environment data group 33 in the detention risk map.

[0157] Fig.17 FIG. 4 is a diagram showing an example of processing performed by the detention risk map generation unit 15 in the fourth embodiment. Fig.17 14 shows a driving scene 1401 and a corresponding detention risk map 1402. In the driving scene 1401, a road surface marking indicating a no-stopping area 1412 and a road sign 1414 indicating a no-parking area 1413 on the road where the host vehicle 2 is traveling are shown. Fig.10 The processing flow generates a detention risk map. At this time, the detention risk map generation unit 15 maps not only the driving-prohibited area but also the parking-prohibited area into the detention risk map in step S809. By referring to the road environment data group 33 obtained from the map information management device 6, information related to road surface markings and road signs can be obtained.

[0158] The detention risk map generation unit 15 determines the no-stopping area based on the information of the road surface markings and road signs, and configures the detention risk at the corresponding location. Fig.17In the embodiment, the non-stopping area 1412 corresponds to the retention risk 1422, and the parking prohibited section 1413 corresponds to the retention risk 1423. Then, the travel control planning unit 16 generates a trajectory that does not stop at the retention risk, similarly to the third embodiment.

[0159] The driving control planning unit 16 may also directly refer to the road environment data group 33 to independently judge such road surface markings, road signs and other information related to traffic rules. However, in the automatic driving on the road, in addition to considering a plurality of various traffic rules, it is also necessary to consider the coordinated actions with the mobile body described in the first to third embodiments to determine the place where parking or retention is possible, and it is cumbersome to construct a separate judgment process. In this embodiment, by managing these elements that restrict the retention of the vehicle 2 as a retention risk map and making it possible to make judgments, the driving control planning unit 16 can easily determine the appropriate position and posture where retention is possible.

[0160] According to the fourth embodiment described above, the following effects can be obtained.

[0161] (10) The detention risk map generation unit 15 also estimates the detention risk area based on the traffic regulation information around the vehicle included in the driving environment information. Therefore, the electronic control device 3 can achieve smooth passing with other vehicles while complying with traffic regulations.

[0162] (11) Traffic rules information is as follows Fig.17 Therefore, the electronic control device 3 can achieve smooth passing with other vehicles while complying with traffic regulations such as the no-parking zone and the no-stopping zone.

[0163] -Fifth Embodiment-

[0164] Below, refer to Figures 18 to 31 , a fifth embodiment of the electronic control device is described. In this embodiment, the difference from the previous embodiment is that after the passing of vehicles is also considered. The same reference numerals are attached to the same components as the first embodiment and the description thereof is omitted.

[0165] Fig.18 This is a functional block diagram showing the configuration of a vehicle system 2001 including an electronic control device 2003 of the fifth embodiment. The vehicle system 2001 is mounted on another vehicle 2002. The vehicle system 2001 performs appropriate driving assistance and driving control based on the conditions of obstacles such as the driving road and surrounding vehicles around the other vehicle 2002. The driving assistance also includes presenting information to the driver of the vehicle 2.

[0166] Fig.192 is a functional structure diagram of the second driving control planning unit 2016. The second driving control planning unit 2016 calculates the target trajectory based on the risk map, environmental information, lane information, and map information. The second driving control planning unit 2016 includes a driving planning unit 2501 and a trajectory planning unit 2506. The driving planning unit 2501 calculates the driving mode candidate weight 3001 based on the route information, environmental information, and the last selected information 3005.

[0167] The driving mode candidate weight 3001 is the weight that the vehicle 2 performs for each of the predetermined multiple driving modes, in other words, the probability. The driving modes in this embodiment are lane keeping, lane changing, obstacle avoidance, and passing each other, and the values ​​of V1 to V4, whose total value is "100", represent their respective weights. That is, the driving mode candidate weight 3001 is the value of V1 to V4. For example, when the vehicle 2 is traveling on a straight road, there are no vehicles or objects to be avoided in front, and there is no need to change lanes to an adjacent lane according to the route information, V1 corresponding to lane keeping is "100", and V2 to V4 are set to "0".

[0168] The track planning unit 2506 includes a lane maintaining track generation unit 2502, a lane changing track generation unit 2503, an obstacle avoiding track generation unit 2504, a passing track generation unit 2508, and a track adjustment unit 2505. The lane maintaining track generation unit 2502 generates a track for maintaining the center of the lane in which the host vehicle 2 is currently traveling. The lane changing track generation unit 2503 generates a track for changing lanes to a lane adjacent to the lane in which the host vehicle 2 is currently traveling. The obstacle avoiding track generation unit 2504 generates a track for avoiding obstacles existing in the lane in which the host vehicle 2 is currently traveling. The passing track generation unit 2508 generates a track for passing other vehicles as described later.

[0169] The track adjustment unit 2505 evaluates each track generated by the lane maintaining track generation unit 2502, the lane changing track generation unit 2503, the obstacle avoiding track generation unit 2504, and the passing track generation unit 2508 based on the safety with the surrounding objects and the driving mode candidate weight 3001. This evaluation can be calculated, for example, as the product of the inverse of the minimum distance between the track and the object and the value of the driving mode candidate weight 3001. The track adjustment unit 2505 determines the driving mode with the best evaluation as the optimal mode, and generates driving control information in such a way that the vehicle 2 drives along the track of the optimal mode. Furthermore, the track adjustment unit 2505 outputs the optimal mode as the last selected information 3005 to the driving planning unit 2501.

[0170] Fig. 20Detailed configuration diagram of the passing track generation unit 2508. The passing track generation unit 2508 includes a management unit 2581, a track generation unit 2582, and a cancellation track generation unit 2583. The management unit 2581 manages the passing state described later. The track generation unit 2582 generates a passing track. The cancellation track generation unit 2583 generates a cancellation track. The passing track and the cancellation track will be described in detail later.

[0171] Fig.21 This is a flowchart showing the processing of the track generation unit 2582 of the passing track generation unit 2508. The track generation unit 2582 first obtains the sensor detection data group 31, the road environment data group 33, the coordinated action data group 34, the moving body track prediction data group 36, the collision risk map data group 37, and the detention risk map data group 38 in step S3301. In the next step S3302, the track generation unit 2582 refers to the coordinated action data group 34 to determine whether there is a coordinated moving body as a moving body for coordinated action. The track generation unit 2582 ends the process if it is determined that there is no coordinated moving body. Fig.21 The processing shown enters step S3305 when it is determined that a cooperative moving object exists.

[0172] In step S3305, the track generation unit 2582 generates a plurality of candidates for the retreat position posture based on the collision risk map and the detention risk map. The details of the processing of this step will be described later with reference to the accompanying drawings. In the next step S3306, the track generation unit 2582 generates a candidate for the arrival position that changes the passing mode to another mode after passing the retreat position, that is, the arrival position candidate. The details of the processing of this step will be described later with reference to the accompanying drawings.

[0173] In the next step S3307, the track generation unit 2582 generates a track candidate passing through the retreat position posture candidate and the arrival position candidate. As described above, since there are multiple retreat position posture candidates, there are also multiple track candidates generated in this step. In the next step S3308, the track generation unit 2582 evaluates the track candidates generated in step S3307 respectively, and selects the track with the highest evaluation. The evaluation value used in the evaluation can be calculated, for example, in such a way that the less the overlap between the track and the retention risk area, the higher the evaluation value, and the shorter the length of the track, the higher the evaluation value. In the next step S3309, the track generation unit 2582 stores the information of the track selected in step S3308 as the track generated by the track generation unit 2582 in the storage unit 30.

[0174] Fig. 22 Yes Description Fig.21FIG. 1 is a diagram of a method for generating a candidate for a retreat position and posture in step S3305. However, the generation method described here is only an example, and the candidate for a retreat position and posture may be generated by other methods. Fig. 22 As shown, there is an oncoming vehicle 2200 in front of the vehicle 2 with which coordinated action should be performed. Moreover, there is an evacuation space in front of the left side of the vehicle 2. Since the detention risk area 2292 generated by the detention risk map generation unit 15 exists in front of the vehicle and on the vehicle 2, in order to achieve coordinated action, in this case, passing driving, the vehicle 2 needs to be moved to a place where the detention risk area does not exist, that is, to evacuate.

[0175] Therefore, in an area where the retention risk area 2292 does not exist and does not contact the collision risk area 2291, avoidance posture position candidates (N1, θ1) to (N5, θ5) are generated. N represents the plane position, and θ represents the yaw angle of the vehicle 2. The number of avoidance posture position candidates generated at this time is arbitrary. The track generation unit 2582 considers the size of the vehicle 2 and selects a place close to the retention risk area within a range where the vehicle 2 does not overlap with the retention risk area.

[0176] Fig.23 Yes Description Fig.21 FIG. 2 is a diagram of a method for generating arrival position candidates in step S3306 of the present invention. However, the generation method described here is only an example, and arrival position candidates may be generated by other methods. First, the track generation unit 2582 refers to the road environment data group 33 to determine the center line 3501 of the driving lane in which the vehicle 2 is traveling. Next, the track generation unit 2582 calculates the interval between the positions where the passing mode start point 3502 and the retreat position posture candidate 3504 are projected onto the above-mentioned center line 3501 as the distance L. Then, the track generation unit 2582 sets the point on the above-mentioned center line 3501, that is, the point that has advanced a distance L in the opposite direction of the passing mode start point 3502 from the position where the retreat position posture candidate 3504 is projected, as the arrival position candidate 3503.

[0177] Fig.24 Yes Description Fig.21 FIG. 25 shows a method for generating track candidates in step S3307. However, the generation method described here is only an example, and track candidates may be generated by other methods. Fig.24 As shown, a path candidate is generated by combining a straight line and a plurality of circular arc curves. The track generation unit 2582 can generate a plurality of path candidates by changing the length of the straight line portion, the radius of the circular arc curve, etc. In addition, the track generation unit 2582 can also use a clothoid curve instead of a circular arc curve. The track generation unit 2582 can also set a speed for each track.

[0178] The track generation unit 2582 calculates the speed curve of the vehicle when traveling on the generated track candidate. The speed curve is, for example, a curve in which the speed is set for each hypothetical time series point set for each predetermined distance or predetermined time on the track candidate. The speed set for each time series point can be a random value or a fixed value. The track generation unit 2582 creates a plurality of speed curves and evaluates each speed curve using the following formula. In the following formula, the total calculated for all time series points on the track candidate becomes the evaluation value EVV of the speed curve. The track generation unit 2582 uses the speed curve with the minimum evaluation value EV1 as the speed curve of the track candidate.

[0179] EVV = Σ{w11 (front-rear acceleration of the vehicle) ^2 + w12 (lateral acceleration of the vehicle) ^2 + w13 (speed limit - vehicle speed) ^2 + w14 (value of the collision risk map) ^1} ···Formula 1

[0180] In Formula 1, w11 to w14 are respectively predetermined coefficients. The value of the collision risk map in Formula 1 is the sum of the values ​​of the collision risk areas passed when the time series point is included in the collision risk area, and is "0" when the time series point is not included in the collision risk area. The value of the collision risk area can be a discrete value such as 0 or 1 indicating the presence or absence of risk, or a continuous value such as 0 to 100 indicating the degree of risk.

[0181] right Fig.21 The details of step S908 are described below. The track generation unit 2582 evaluates each track candidate according to the following five viewpoints, and adopts the track candidate with the highest track evaluation value EVR, which is the sum of the evaluation value and the weight coefficient. The five viewpoints are safety, convenience, riding comfort, discomfort, and pressure on oncoming vehicles. The track evaluation value EVR is expressed by the following formula 2.

[0182] EVR=w1E1+w2E2+w3E3+w4E4+w5E5···Equation 2

[0183] In Formula 2, w1 to w5 are respectively predetermined coefficients, and E1 to E5 are respectively evaluation values ​​of the above five viewpoints.

[0184] In the evaluation of safety, the distance to the surrounding objects and the apparent risk value are used. For example, a method can be considered to use the inverse of the minimum distance between the road and the path candidate, or the value of the collision risk map as the evaluation value. In the evaluation of convenience, the length of the entire track or the length of the track from the starting point of the passing mode to the candidate of the retreat position posture can be used. The shorter the track, the higher the evaluation. The reason is that if the action for passing the vehicle takes time, the waiting time of the oncoming vehicle becomes longer, which may cause the occupants of other vehicles and this vehicle to feel distrustful.

[0185] In the evaluation of ride comfort, the acceleration or time change of acceleration generated by the vehicle traveling on the calculated path, i.e., jerk, etc. is used. For example, the value of (the inverse of the turning radius) × (the total turning angle) can be used as an evaluation index. This is based on the consideration that the ride comfort is poor on the path with a long lateral acceleration and a long time for the lateral acceleration to be generated. That is, in a state where the turning radius is small, the larger the turning angle, the greater the evaluation value of the ride comfort.

[0186] In the evaluation of discomfort, the number of turns is used. This is based on the consideration that the greater the number of turns, the more discomfort the occupants of the host vehicle 2 will feel. In the evaluation of oppression, the closest distance between the calculated path and other vehicles is used. For example, the inverse of the minimum distance between the center position coordinates of other vehicles and the path candidate can be used as an evaluation index. The reason is that a path that is too close to the oncoming vehicle will make the occupants of the host vehicle and other vehicles feel oppressive.

[0187] Fig.25 2701 is a transition diagram of the passing state managed by the management unit 2581. In the management unit 2581, the passing state indicating the passing state with the oncoming vehicle is managed. The passing state has four states: initial state 2701, passing execution state 2702, passing completion state 2703, and passing cancellation state 2704. The passing state at the start of the action is the initial state 2701, and the initial state 2701 is transformed as described below.

[0188] In the initial state 2701, if it is determined that the passing car can be driven, the state 2702 of the passing car execution is changed. In the initial state 2701 or the passing car execution state 2702, if it is determined that the passing car cannot be driven, the state 2704 of the passing car cancellation is changed. In the passing car execution state 2702, if the passing car is completed, the state 2703 of the passing car completion is changed. If the state of the oncoming vehicle or the environmental conditions change during the passing car driving and it is determined that the passing car cannot be driven, the state 2704 of the passing car cancellation is changed. After changing to the passing car completion state 2703 and the passing car cancellation state 2704, the state 2701 is returned to the initial state 2701 again. The following describes each state.

[0189] Fig.26 2 is a flowchart showing the processing performed by the management unit 2581 in the initial state 2701. The management unit 2581 first confirms the request for passing the vehicle in step S2801. Specifically, when the value of the weight of the driving mode corresponding to the "passing vehicle" generated by the driving planning unit 501, that is, "V4", is greater than the prescribed value, the management unit 2581 makes an affirmative judgment and proceeds to step S2802. When the value of "V4" is less than the prescribed value, the management unit 2581 makes a negative judgment and returns to step S2801.

[0190] In step S2802, the management unit 2581 generates the track required for the passing vehicle using the passing track generation unit 602. The detailed processing of this step is as follows: Fig.21 In the next step S2803, the management unit 2581 generates a cancellation track. The cancellation track is a track from the current position of the vehicle 2 to the candidate arrival position, and is a track different from the passing track. The cancellation track is, for example, a track connecting the current position of the vehicle 2 to the candidate arrival position with a straight line.

[0191] Fig. 27 This is a diagram showing an example of a passing track and a cancelled track. Fig. 27 , the path from the current position of the vehicle 2 to the arrival position candidate 3503 via the evacuation position posture candidate 3504 is the passing track. On the other hand, the path from the current position of the vehicle 2 to the arrival position candidate 3503 without passing through the evacuation position posture candidate 3504 is the cancellation track. Fig.26 Continue with the description.

[0192] In the next step S2804, the management unit 2581 determines whether passing is necessary. Specifically, the management unit 2581 refers to the collision risk map data group 37 and the detention risk map data group 38, and determines that passing is necessary when the cancellation track overlaps with the risk area, and determines that passing is not necessary when the cancellation track does not overlap with the risk area. The management unit 2581 enters step S2805 when it is determined that passing is necessary, and enters step S2806 when it is determined that passing is not necessary. In step S2805, the management unit 2581 changes the passing state to the passing execution state 2702, and ends. Fig.26 In step S2806, the management unit 2581 changes the missed vehicle state to the missed vehicle cancellation state 2704, and ends Fig.26 Processing shown.

[0193] Fig.28 2811 is a flowchart showing the processing performed by the management unit 2581 in the passing vehicle execution state 2702. The management unit 2581 first generates a track required for passing vehicle running in step S2811. The detailed processing of this step is as follows: Fig.21In the next step S2812, the management unit 2581 generates a cancellation track. The generation method of the cancellation track is as follows: Fig.26 As described in step S2803.

[0194] In the next step S2813, the management unit 2581 compares the generated passing track and the canceled track, and evaluates them based on the safety and riding comfort indicators. For example, if the management unit 2581 determines that there is a risk of rapid approach with other vehicles or surrounding objects when the vehicle is driven based on the passing track, it determines that the passing driving cannot continue. If the management unit 2581 determines that the passing driving can continue, it proceeds to step S2814, and if it determines that the passing driving cannot continue, it proceeds to step S2817.

[0195] In step S904, the management unit 2581 outputs the generated passing track to the track adjustment unit 505. The track output here, when selected by the track adjustment unit 505, is controlled so that the vehicle 2 travels along the track. In the next step S2815, the management unit 2581 determines whether the position of the vehicle 2 has reached the end area of ​​the passing mode, that is, the arrival position candidate, based on its own position information, lane information, etc. The management unit 2581 enters step S2816 when it is determined that the arrival position candidate has been reached, and returns to step S2811 when it is determined that the arrival position candidate has not been reached. In step S2816, the management unit 2581 changes to the passing completion state 2703, ending. Fig.28 In step S2817, the management unit 2581 changes the missed-car state to the missed-car cancellation state 2704, and ends Fig.28 Processing shown.

[0196] Fig.29 2 is a flowchart showing the processing performed by the management unit 2581 in the vehicle passing completion state 2703. The management unit 2581 first generates a lane maintaining track in step S2821. Specifically, the management unit 2581 generates a track for maintaining the driving lane in which the host vehicle 2 is currently traveling using the lane maintaining track generation unit 2502 or through the same processing as the lane maintaining track generation unit 2502. In the next step S2822, the management unit 2581 outputs the track generated in step S2821 to the track adjustment unit 505. When the track output here is selected by the track adjustment unit 505, the host vehicle 2 is controlled to travel along the track.

[0197] In the next step S2823, the management unit 2581 determines whether the same lane is maintained within the prescribed time. If the management unit 2581 determines that the lane is maintained for more than the prescribed time, it proceeds to step S2824. If it determines that the lane is maintained for less than the prescribed time, it returns to step S2821. In step S2824, the management unit 2581 changes the passing state to the initial state 2701, and ends. Fig.29 Processing shown.

[0198] Fig.30 This is a flowchart showing the processing performed by the management unit 2581 in the missed vehicle cancellation state 2704. The management unit 2581 first outputs the calculated cancellation track to the track adjustment unit 505 in step S2831. The track output here, when selected by the track adjustment unit 505, is controlled so that the vehicle 2 travels along the track. In the next step S2832, the management unit 2581 determines whether the cancellation track is maintained within a specified time, in other words, determines whether the vehicle 2 has successfully traveled along the cancellation track. If the management unit 2581 determines that the cancellation track is maintained for more than the specified time, it proceeds to step S2833, and if the management unit 2581 determines that the time for maintaining the cancellation track is less than the specified value, it returns to step S2831. In step S2833, the management unit 2581 changes the missed vehicle state to the initial state 2701, and ends. Fig.30 Processing shown.

[0199] Fig.31 2 is a schematic diagram showing the operation of the vehicle 2 based on the processing of the electronic control device 2003. Fig.31 In the scene shown, the road is narrow, the vehicle 2 is driving automatically from the left side to the right side in the figure, and there is an oncoming vehicle 3200 in front of the vehicle 2. The vehicle 2 detects the existence of the retreat area 211 in the left front through at least one of the sensor detection data group 31 and the road environment data group 33. The electronic control device 3002 generates a collision risk map data group 37 and a retention risk map data group 38, and based on this, generates a passing track 3003 from the perspective of riding comfort, safety, etc. By generating the passing track 3003, the vehicle and the oncoming vehicle will not collide, and it can also prevent the riding comfort and the occupants from feeling uneasy.

[0200] According to the fifth embodiment described above, the following effects can be obtained.

[0201] (12) The electronic control device 3 is mounted on the vehicle 2 and plans a passing action with another moving body. The electronic control device 3 includes a passing track generation unit 2508, which generates a candidate of a retreat position for the vehicle to retreat from the moving body during the passing action, that is, a retreat position candidate ( Fig.21S3305) generates a candidate for the arrival position that is reached after passing through the backed-off position candidate, that is, the arrival position candidate ( Fig.21 S3306 of the invention) and generates a trajectory ( Fig.21 Therefore, the electronic control device 3 can generate a track that takes into account the passing of other moving bodies.

[0202] (13) The track generation unit 2582 of the passing track generation unit 2508 generates an evacuation position candidate based on at least one of the size of the moving object and the speed of the moving object.

[0203] (14) The track generation unit 2582 of the passing track generation unit 2508 generates a plurality of tracks, evaluates each of the plurality of tracks, and selects the best track ( Fig.21 S3308).

[0204] (15) The track generation unit 2582 of the passing track generation unit 2508 evaluates the plurality of tracks ( Fig.21 S3308).

[0205] (Variation 1 of the Fifth Embodiment)

[0206] In the fifth embodiment described above, the track generation unit 2582 determines the candidates for the retreat position and posture with reference to the collision risk map and the detention risk map. However, the track generation unit 2582 may determine the candidates for the retreat position and posture without reference to the collision risk map and the detention risk map. For example, the track generation unit 2582 may extract the retreat area from the sensor detection data group 31 and the road environment data group 33, randomly set the retreat position candidates in the retreat area, and may also set the retreat position and posture candidates at the position farthest from the oncoming vehicle in the retreat area. Furthermore, the track generation unit 2582 may also set the candidates for the retreat position and posture based on the speed of the vehicle 2 and the speed of the oncoming vehicle, and the positional relationship between the vehicle, the oncoming vehicle, and the retreat area. For example, the retreat position and posture candidates may also be set in the retreat area closest to the position where the vehicle 2 and the oncoming vehicle collide when the two are traveling at the current speed.

[0207] (Variation 2 of the Fifth Embodiment)

[0208] In the fifth embodiment, the trajectory generation unit 2582 evaluates the calculated multiple trajectory candidates according to five viewpoints and adopts the path with the highest evaluation. However, the trajectory generation unit 2582 may not only calculate and evaluate one trajectory candidate and use the trajectory candidate, but may also randomly use one trajectory candidate from multiple trajectory candidates. In this case, the trajectory candidate may also be appropriately corrected. For example, only one trajectory candidate may be calculated, and if there is an obstacle on the trajectory candidate, the trajectory candidate may be corrected to avoid the obstacle.

[0209] (Variation 3 of the Fifth Embodiment)

[0210] exist Fig.28 In step S2824, the driving mode may be changed to the lane keeping mode, that is, the selection of the track in the track adjustment unit 2505 may be changed to the track generated by the lane keeping track generation unit 2502.

[0211] (Variation 4 of the Fifth Embodiment)

[0212] In the above embodiment, the trajectory generation unit 2582 determines not only the place where the host vehicle 2 retreats but also the posture of the host vehicle 2. However, the trajectory generation unit 2582 may not determine the posture. That is, the "retreat position posture candidate" in the fifth embodiment may be replaced with the "retreat position candidate".

[0213] - Sixth Embodiment -

[0214] Reference Figure 32-33 , a sixth embodiment of the electronic control device is described. In the following description, the same reference numerals are given to the same components as those in the fifth embodiment, and the differences are mainly described. Points not specifically described are the same as those in the fifth embodiment. In this embodiment, the main difference from the fifth embodiment is that the arrival position candidate is changed in consideration of the environmental conditions near the arrival position candidate.

[0215] Fig.32 FIG. 4 is a diagram showing an example of a scene in which the processing in the sixth embodiment is effective. Fig.32 In the example shown, there are obstacles 1801 such as electric poles and fallen objects on the road near the arrival position candidate. In this case, as in the first embodiment, if the arrival position candidate is set at a position that is linearly symmetrical with the avoidance position posture candidate, it is necessary to immediately avoid the object 3801 after the passing vehicle driving mode ends, which may cause uneasiness to the occupants of the vehicle 2.

[0216] Therefore, the passing track generation unit 2508 in this embodiment generates a passing track that takes into account the state near the arrival position candidate. Fig.33As shown in FIG. 1 , several more arrival position candidates are generated around the arrival position candidate. Then, trajectory candidates for all of them are generated, all the generated trajectory candidates are evaluated, and the best trajectory is selected. The generated additional arrival position candidates are, for example, Fig.33 As shown, the arrival position candidates are generated in the vertical direction relative to the lane center line 3501. However, the arrival position candidates can also be generated in the arc direction with the position of the object 3801 as the center. In this way, by generating a passing track that also takes the conditions of the arrival position candidates into consideration, even when the passing driving mode ends and switches to the lane keeping mode or the occupant's driving mode, it is possible to switch safely.

[0217] According to the sixth embodiment described above, the following effects can be obtained.

[0218] (16) The track generation unit 2582 of the passing track generation unit 2508 determines the retreat position candidate based on the output of the external sensor group 4 that senses the surroundings of the vehicle. The track generation unit 2582 generates a position where there is no object within a predetermined distance as a retreat position candidate. In other words, the track generation unit 2582 excludes the position where there is an object within the predetermined distance from the retreat position candidate. Therefore, the action of avoiding the object after the passing driving mode ends can be avoided.

[0219] - Seventh Embodiment -

[0220] Reference Fig.34 , a seventh embodiment of the electronic control device is described. In the following description, the same reference numerals are used for the same components as those in the fifth embodiment, and the differences are mainly described. The points not specifically described are the same as those in the fifth embodiment. In this embodiment, the main difference from the fifth embodiment is that the blind spot is considered in the selection of the candidate for the avoidance position posture.

[0221] Fig.34 1 is a diagram showing an example of a scene in which the processing in the seventh embodiment is effective. The electronic control device 3 in this embodiment avoids the blind spot area and selects the avoidance position posture candidate. Fig.34 In the example, there is a blind spot factor object 4001 such as a high wall near the road boundary 3901. Due to the blind spot factor object 2901, a blind spot area 4002 of the external sensor group 4 is generated near the retreat space. In the blind spot area 4002, there may be a large obstacle 4003 or the like.

[0222] When the trajectory generation unit 2582 generates three reference numerals 3961 to 3963 as candidates for avoidance positions and postures, if reference numeral 3961 is used, it may be difficult to park the vehicle due to obstacle 4003, so it is not preferred. Therefore, when there is a blind spot area, the trajectory generation unit 2582 excludes the avoidance position and posture candidates that are within a specified distance from the blind spot area 4002 for selection. However, the trajectory generation unit 2582 may also add the distance between the candidate trajectory and the blind spot area to the evaluation items of the candidate trajectory instead of excluding all of them.

[0223] According to the seventh embodiment described above, the following effects can be obtained.

[0224] (17) The track generation unit 2582 of the passing track generation unit 2508 determines the candidate of the retreat position based on the output of the external sensor group 4 that senses the surroundings of the vehicle. The track generation unit 2582 generates a position that is not a blind spot of the external sensor group 4 as a candidate of the retreat position. In other words, the track generation unit 2582 excludes the blind spot of the external sensor group 4 from the candidate of the retreat position. In the passing driving in the state where such a blind spot area exists, by generating the passing track taking the blind spot area into consideration, the target waiting position posture and the target track will not be changed in the middle of the passing driving, and the riding comfort of the passengers will not be disturbed.

[0225] - Eighth Embodiment -

[0226] Reference Figure 35-36 , an eighth embodiment of the electronic control device is described. In the following description, the same reference numerals are used for the same components as those in the fifth embodiment, and the differences are mainly described. The points not specifically described are the same as those in the fifth embodiment. In this embodiment, the main difference from the fifth embodiment is that notification is performed when a path cannot be generated.

[0227] Fig.35 : This is a functional structure diagram of the second driving control planning unit 2016 in the eighth embodiment. In addition to the structure of the second driving control planning unit 2016 in the fifth embodiment, the second driving control planning unit 2016 in this embodiment is further provided with a notification unit 2509. The notification unit 2509 notifies the output of the track mediation unit 2505 to the outside. The notification destination is not limited to the interior of the vehicle 2, but may also be the surroundings or a distance of the vehicle 2. The notification method may be any one of sound, image, and vibration, and may also be not directly notified via communication. That is, the notification unit 2509 may be implemented by a voice output device, an image output device, a vibrator, a communication module, and the like.

[0228] In the present embodiment, the second travel control planning unit 2016 notifies the passengers of the vehicle 2 through the notification unit 2509 that a path cannot be generated when there is no track on which the vehicle 2 can travel. As described above, the track adjustment unit 2505 evaluates the tracks generated by the lane keeping track generation unit 2502, the lane change track generation unit 2503, the obstacle avoidance track generation unit 2504, the passing track generation unit 2508, and the track adjustment unit 2505. For example, when the track adjustment unit 2505 determines that any track collides with an obstacle, it notifies that a path cannot be generated.

[0229] Fig.36 FIG. 4 is a diagram showing an example of a scene in which the processing in the eighth embodiment is effective. Fig.36 In the example, there is a following vehicle 1901 behind the vehicle 2 and another vehicle 200 in front. Although the vehicle 2 has generated a passing track, the other vehicle 200 is approaching the vehicle 2, so the outer side of the road, the collision risk area 291 of the following vehicle 1901 and the other vehicle 200 surround the vehicle 2. In this state, the vehicle 2 is in contact with the collision risk area 291 regardless of which direction it moves, so it cannot move. Therefore, the second driving control planning unit 2016 notifies the occupants of the vehicle 2 that the path cannot be generated. As a result, for example, it can be expected that the situation can be improved by the occupants of the vehicle 2 driving themselves.

[0230] According to the eighth embodiment described above, the following effects can be obtained.

[0231] (18) The track adjustment unit 2505 determines the track on which the vehicle 2 is to travel from a plurality of tracks including the track generated by the passing track generation unit 2508 and the lane keeping track generation unit 2502. If there is no track on which the vehicle 2 can travel, the notification unit 2509 notifies that the track cannot be calculated. Therefore, the passengers of the vehicle 2 are notified that a path cannot be generated, and it is expected that the situation can be improved by the passengers of the vehicle 2 driving themselves, for example.

[0232] In each of the above-mentioned embodiments and variations, the configuration of the functional modules is only an example. Several functional configurations shown as different functional modules may be integrated, or a configuration represented by a functional block diagram may be divided into two or more functions. In addition, other functional modules may be configured to have a part of the functions possessed by each functional module.

[0233] In each of the above-mentioned embodiments and variations, the program is stored in a ROM not shown in the figure, but the program may also be stored in the storage unit 30. In addition, the electronic control device is provided with an input / output interface not shown in the figure, and the program may be read from other devices via the input / output interface and a medium available to the electronic control device when necessary. Here, the medium refers to, for example, a storage medium or a communication medium that can be loaded and unloaded from the input / output interface, that is, a wired, wireless, optical network, or a carrier or digital signal transmitted in the network. In addition, part or all of the functions implemented by the program may also be implemented by a hardware circuit or FPGA.

[0234] The above-mentioned embodiments and modifications may also be combined. Various embodiments and modifications are described above, but the present invention is not limited to these contents. Other modes considered within the scope of the technical concept of the present invention are also included in the scope of the present invention.

[0235] Description of Reference Numerals

[0236] 2: Vehicle, own vehicle

[0237] 3: Electronic control device

[0238] 11: Information Acquisition Department

[0239] 12: Coordinated Action Planning Department

[0240] 13: Mobile behavior prediction department

[0241] 14: Collision risk map generation unit

[0242] 15: Detention risk map generation department

[0243] 16: Driving Control Planning Department

[0244] 17: Information output unit

[0245] 37: Collision Risk Map Data Set

[0246] 38: Detention Risk Map Data Set

[0247] 291: Collision risk area

[0248] 292: Detention risk area

[0249] 292-1: Main stranding risk area

[0250] 292-2: Low risk of detention area

[0251] 501: Driving Planning Department

[0252] 505: Track Adjustment Department

[0253] 602: Track Generation Unit

[0254] 2016: Second Driving Control Planning Department

[0255] 2505: Track Adjustment Department

[0256] 2508: Track Generation Department

Claims

1. An electronic control device mounted on a vehicle, wherein: have: an information acquisition unit, which acquires driving environment information related to the driving environment around the vehicle; a detention risk area estimating unit that estimates a detention restriction area based on the driving environment information, the detention restriction area being an area that hinders the movement of mobile bodies other than the vehicle, i.e., other mobile bodies, when the vehicle is detained and is an area that restricts the detention of the vehicle; as well as A travel control planning unit plans travel control of the vehicle based on the estimated stay restriction area.

2. The electronic control device according to claim 1, wherein: The travel control planning unit plans travel control so that the vehicle stays in an area of ​​the predetermined area that does not overlap with the stay restriction area when the vehicle needs to stay in the predetermined area.

3. The electronic control device according to claim 1, wherein: The other moving objects are moving objects present around the vehicle and included in the driving environment information. The electronic control device further includes a coordinated action planning unit that determines a coordinated action process to be performed with the other mobile bodies. The retention restriction area is an area that hinders the actions of the other moving bodies in the coordinated action process when the vehicle is retained.

4. The electronic control device according to claim 3, wherein: The stay risk area estimating unit estimates an estimated moving body behavior area through which the moving body may pass during the behavior of the moving body in the coordinated behavior process, and estimates the stay restriction area based on the estimated moving body behavior area.

5. The electronic control device according to claim 3, wherein: The travel control planning unit plans a target waiting position and posture of the vehicle during the coordinated action so as not to overlap with the stay restriction area.

6. The electronic control device according to claim 5, wherein: The stay restriction area includes information related to the degree of difficulty of movement given to the mobile body. The travel control planning unit allows planning of a target waiting position posture overlapping the region with a low degree of behavioral difficulty when there is no target waiting position posture that does not overlap the stay restriction region.

7. The electronic control device according to claim 1, wherein: The travel control planning unit plans travel control so that the time spent in the stay restriction area falls within a predetermined value.

8. The electronic control device according to claim 1, wherein: The other moving objects are moving objects that are estimated to appear around the vehicle in the future based on the running environment information.

9. The electronic control device according to claim 1, wherein: The stay risk area estimating unit further estimates the stay restriction area based on traffic regulation information around the vehicle included in the driving environment information.

10. The electronic control device according to claim 9, wherein: The traffic regulation information refers to a prohibited parking area or a non-stopping area.

11. The electronic control device according to claim 1, wherein: The electronic control device further includes a collision risk region estimating unit that estimates a collision risk region where there is a risk of the vehicle colliding with an obstacle based on the driving environment information. The travel control planning section plans travel control such that the vehicle does not intrude into the collision risk area and the vehicle does not stay in the stay restriction area.

12. A planning method, which is a planning method executed by an electronic control device mounted on a vehicle, wherein: include: Acquiring driving environment information related to the driving environment around the vehicle; estimating a retention restriction area based on the running environment information, the retention restriction area being an area that hinders movement of mobile bodies other than the vehicle when the vehicle is retained and is an area that restricts retention of the vehicle; as well as Based on the estimated stay restriction area, travel control of the vehicle is planned.

13. The electronic control device according to claim 1, wherein: The electronic control device further includes a passing track generating unit, which performs: generating a retreat position candidate at a position that does not overlap with the stay restriction area, the retreat position candidate being a candidate for a retreat position for the vehicle to retreat from the other moving body when the vehicle is in a passing maneuver with the other moving body, generating an arrival position candidate, the arrival position candidate being a candidate of an arrival position reached after passing through the retreat position candidate, A trajectory passing through the current position of the vehicle, the position of the evacuation position candidate, and the position of the arrival position candidate is generated.

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