Electronic control device and planning method

Abstract

To achieve smooth passing.SOLUTION: An electronic control device mounted on a vehicle includes: an information acquisition section for acquiring travel environment information related to a travel environment in the periphery of the vehicle; a remaining risk area estimation section for estimating, based on the travel environment information, a remaining limit area being the area where the vehicle blocks a behavior of a mobile body other than the vehicle when the vehicle remains and also the area which limits the remaining of the vehicle; and a travel control planning section for planning travel control of the vehicle based on the estimated remaining limit area.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] In recent years, in order to realize comfortable and safe driving assistance and autonomous driving of vehicles, technologies have been proposed that generate the driving trajectory of the vehicle while taking into account the driving of other vehicles. Patent Document 1 discloses a route confirmation device for use in a vehicle, the route confirmation device including a route generation unit that generates a driving plan for driving the vehicle by autonomous driving, and a driving control unit that controls the driving of the vehicle in accordance with the generated driving plan, the route confirmation device including a safety distance setting unit that sets a minimum safety distance that the host vehicle, which is the vehicle for which the route confirmation device is used, should maintain between the host vehicle and the obstacle to avoid the host vehicle coming close to the obstacle, an emergency control unit that determines whether the host vehicle is driving while maintaining the set safety distance, and, if the distance between the host vehicle and the obstacle is shorter than the safety distance, executes emergency control for the host vehicle that is determined separately from the control in accordance with the driving plan, an attention area setting unit that sets an attention area between the moving obstacle and the host vehicle when a moving obstacle is in the direction of travel of the host vehicle, the attention area being an area located farther away from the host vehicle than the safety distance of the host vehicle, and a route selection unit that selects, from the generated driving plans, a driving plan in which the moving obstacle does not enter the set attention area. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2022 / 025087 Summary of the Invention [Problem to be solved by the invention]

[0004] The invention described in Patent Document 1 leaves room for improvement in terms of smooth passing. [Means for solving the problem]

[0005] An electronic control device according to a first aspect of the present invention is an electronic control device mounted on a vehicle, and includes an information acquisition unit that acquires driving environment information related to the driving environment around the vehicle, a congestion risk area estimation unit that estimates a congestion restriction area, which is an area in which the movement of moving bodies other than the vehicle is hindered if the vehicle is delayed based on the driving environment information, and is an area in which the delay of the vehicle is restricted, and a driving control planning unit that plans driving control of the vehicle based on the estimated congestion restriction area. A planning method according to a second aspect of the present invention is a planning method executed by an electronic control unit mounted on a vehicle, and includes acquiring driving environment information regarding the driving environment around the vehicle, estimating a staying restriction area, which is an area in which the movement of moving bodies other than the vehicle is hindered if the vehicle stays there based on the driving environment information, and restricting the staying of the vehicle, and planning driving control of the vehicle based on the estimated staying restriction area. Effect of the Invention

[0006] According to the present invention, smooth passing can be achieved. [Brief description of the drawings]

[0007] [Figure 1] FIG. 1 is a functional block diagram showing a configuration of a vehicle system according to a first embodiment; [Diagram 2] FIG. 1 is a diagram showing an example of a driving scene. [Diagram 3] FIG. 1 shows an example of the structure of data stored in a collaborative behavior data set. [Figure 4] FIG. 3 is a diagram showing an example of a group of predicted moving object path data and a group of predicted moving object trajectory data in the driving scene of FIG. 2; [Diagram 5] FIG. 3 is a diagram showing an example of a collision risk map data group and a retention risk map data group in the driving scene of FIG. 2; [Figure 6] A diagram showing the correlation between the functions realized by the electronic control unit. [Figure 7]Flowchart showing the process of the collaborative action planning unit [Figure 8] Flowchart showing the process of the mobile object behavior prediction unit [Figure 9] Flowchart showing the process of the collision risk map generation unit [Figure 10] Flowchart showing the process of the retention risk map generating unit [Figure 11] Flowchart showing the process of the cruise control planning unit [Figure 12] Figure 2: A diagram showing how the vehicle's trajectory is planned using the collision risk area and congestion risk area in the scene shown above. [Figure 13] FIG. 3 is a diagram illustrating the operation of the vehicle system in a scene different from that shown in FIG. 2. [Figure 14] FIG. 13 is a diagram showing a driving scene for explaining the operation of the second embodiment and a part of the operation of the vehicle system in the driving scene. [Figure 15] FIG. 11 is a diagram showing an example of a driving scene for explaining the operation of the second embodiment; [Figure 16] FIG. 13 is a diagram showing an example of processing by a mobile object behavior prediction unit in the third embodiment; [Figure 17] FIG. 23 is a diagram showing an example of processing by a retention risk map generating unit in the fourth embodiment; [Figure 18] FIG. 13 is a functional block diagram showing a configuration of a vehicle system according to a fifth embodiment. [Figure 19] A functional configuration diagram of a second cruise control planning unit in the fifth embodiment. [Figure 20] Detailed configuration of the passing trajectory generation unit [Figure 21] Flowchart showing the process of the trajectory generation unit [Figure 22] FIG. 23 is a diagram for explaining a method for generating candidates for an evacuation position and orientation in step S3305 of FIG. [Diagram 23] FIG. 23 is a diagram for explaining a method for generating arrival position candidates in step S3306 of FIG. [Figure 24] FIG. 23 is a diagram for explaining a method for generating trajectory candidates in step S3307 of FIG. [Diagram 25]Transition diagram of the crossing state managed by the management department [Figure 26] 1 is a flowchart showing a process executed by a management unit in an initial state. [Figure 27] A diagram showing an example of a passing trajectory and a canceling trajectory. [Figure 28] A flowchart showing a process executed by the management unit in a passing execution state. [Figure 29] A flowchart showing a process executed by the management unit in a passing completion state. [Diagram 30] A flowchart showing a process executed by the management unit in a passing cancellation state. [Diagram 31] FIG. 2 is a schematic diagram showing the movement of a vehicle based on the processing of an electronic control unit; [Diagram 32] FIG. 23 is a diagram showing an example of a scene in which the processing in the sixth embodiment is effective; [Diagram 33] FIG. 23 is a diagram showing an example of trajectory generation in the sixth embodiment; [Diagram 34] FIG. 23 shows an example of a scene in which the processing in the seventh embodiment is effective. [Diagram 35] A functional configuration diagram of a second driving control planning unit in the eighth embodiment. [Diagram 36] FIG. 23 shows an example of a scene for which the processing in the eighth embodiment is effective. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] --First embodiment-- Hereinafter, a first embodiment of an electronic control device will be described with reference to FIGS.

[0009] (System Configuration) 1 is a functional block diagram showing a 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 recognizes the conditions of the road on which the vehicle 2 is traveling and obstacles such as surrounding vehicles around the vehicle 2, and then performs appropriate driving assistance and driving control. This driving assistance also includes the presentation of information to the driver of the vehicle 2.

[0010] As shown in Fig. 1, the vehicle system 1 includes an electronic control unit 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 unit 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 by an in-vehicle network N. The in-vehicle network N may be a wired network, a wireless network, or a mixed network of wired and wireless networks. In the following, the vehicle 2 may be referred to as "own vehicle" 2 to distinguish it from other vehicles.

[0011] 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 an external sensor group 4, a vehicle sensor group 5, a map information management device 6, etc., and outputs the information to an actuator group 7 and an HMI device group 8. The electronic control device 3 has a processing unit 10, a storage unit 30, and a communication unit 40.

[0012] The processing unit 10 is configured to include, for example, a central processing unit (CPU). However, in addition to the CPU, the processing unit 10 may include, or may be configured to include, a graphics processing unit (GPU), a field-programmable gate array (FPGA), an application specific integrated circuit (ASIC), or the like, or may be configured to include any one of them. The processing unit 10 has, as its functions, an information acquisition unit 11, a cooperative action planning unit 12, a mobile object behavior prediction unit 13, a collision risk map generation unit 14, a retention risk map generation unit 15, a driving control planning unit 16, and an information output unit 17. The processing unit 10 may realize these by executing a predetermined operation program stored in the storage unit 30, for example, or a part or all of them may be implemented in hardware by an ASIC or the like.

[0013] The information acquisition unit 11 acquires various pieces of information from other devices connected to the electronic control unit 3 via the in-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 on stationary objects and moving objects around the vehicle 2 detected by the external sensor group 4, a vehicle information data group 32 related to the movement and state of the vehicle 2 detected by the vehicle sensor group 5, etc., a road environment data group 33 related to the road on which the vehicle 2 is traveling from the map information management device 6, and the like, and stores the information in the storage unit 30.

[0014] The cooperative behavior planning unit 12 plans the necessity and procedure of cooperative behavior between the vehicle 2 and the mobile objects around the vehicle 2 based on 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 plan as a cooperative behavior data group 34 in the storage unit 30. The mobile object behavior prediction unit 13 predicts future travel routes and trajectories of the mobile objects around the vehicle 2 included in the sensor detection data group 31. For this prediction, information such as the vehicle information data group 32, the road environment data group 33, and the cooperative behavior data group 34 is used. The mobile object behavior prediction unit 13 then saves the predicted travel routes in the storage unit 30 as a mobile object path prediction data group 35, and stores the predicted trajectories in the storage unit 30 as a mobile object trajectory prediction data group 36.

[0015] The collision risk map generating unit 14 estimates an area where there is a risk of collision between the vehicle 2 and obstacles such as stationary objects and moving objects included in the sensor detection data group 31 and the degree of collision (hereinafter referred to as "collision risk"), and generates a collision risk map that is represented by projecting it onto a two-dimensional map. The collision risk map generating unit 14 uses the sensor detection data group 31, the vehicle information data group 32, and the moving object path prediction data group 35 to generate the risk map. The collision risk map generating unit 14 then stores the generated collision risk map in the storage unit 30 as a collision risk map data group 37. Hereinafter, the collision risk map generating unit 14 will also be referred to as a "collision risk area estimating unit."

[0016] The staying risk map generating unit 15 estimates a staying restriction area, which is an area where the behavior of the moving object designated as a cooperative behavior target in the cooperative behavior data group 34 is hindered if the vehicle 2 stays there, and the degree of the hinderance (hereinafter referred to as "stay risk"). For this estimation, a predicted route of the moving object obtained from the moving object route prediction data group 35 is used. Based on the estimation result, the staying risk map generating unit 15 generates a staying risk map that represents the staying risk by projecting it onto a two-dimensional map, and stores it in the storage unit 30 as a staying risk map data group 38. Note that "staying" means staying in a certain place or area for a predetermined period of time or more, and corresponds to a temporary stop or moving at a low speed. Hereinafter, the staying risk map generating unit 15 is also referred to as a "stay restriction area estimating unit".

[0017] The driving control planning unit 16 plans a trajectory on which the vehicle 2 should travel based on the vehicle information data group 32, the road environment data group 33, the cooperative behavior data group 34, the collision risk map data group 37, the delay risk map data group 38, etc., and determines a control command value to be output to the actuator group 7 for tracking the planned trajectory. When it is necessary to take cooperative action with a moving object around the vehicle 2, the driving control planning unit 16 identifies an appropriate waiting position and posture for the next action of the vehicle 2 based on the cooperative behavior data group 34 and the delay risk map data group 38, and plans a route and trajectory to reach the waiting position and posture. The generated planned route and planned trajectory of the vehicle 2, the control command value to be output to the actuator group 7, etc. are stored in the storage unit 30 as a driving control data group 39.

[0018] The information output unit 17 outputs various information to other devices connected to the electronic control unit 3 via the in-vehicle network N. For example, the electronic control unit 3 outputs a control command value determined by the driving control planning unit 16 to the actuator group 7 to control the driving of the vehicle 2. Also, for example, the electronic control unit 3 outputs a collision risk map generated by the collision risk map generating unit 14, a retention risk map generated by the retention risk map generating unit 15, a planned route and a planned trajectory generated by the driving control planning unit 16, and the like to the HMI device group 8. In this way, the electronic control unit 3 presents to the occupant how the vehicle system 1 interprets the surrounding driving environment and what kind of driving it is planning.

[0019] The storage unit 30 includes, 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, a data group required for the processing, and the like. The storage unit 30 is also used as a main memory when the processing unit 10 executes a program, and temporarily stores data required for the program's calculation. In this embodiment, as information for realizing the function of the electronic control unit 3, a sensor detection data group 31, a vehicle information data group 32, a road environment data group 33, a cooperative behavior data group 34, a moving object path prediction data group 35, a moving object trajectory prediction data group 36, a collision risk map data group 37, a retention risk map data group 38, and a driving control data group 39 are stored.

[0020] The sensor detection data group 31 is a collection of data related to detection information by the external sensor group 4. The detection information is, for example, information related to environmental elements such as stationary objects and moving objects identified by the external sensor group 4 based on the sensing information. The vehicle information data group 32 is a collection of data related to the movement, state, etc. 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 running speed, the steering angle, the amount of accelerator operation, the amount of brake operation, etc.

[0021] The road environment data group 33 is a collection of data related to the roads around the vehicle 2, acquired from the map information management device 6 or the like. The data related to the roads includes, for example, information related to the shape and attributes (travel direction, speed limit, driving regulations, etc.) of the roads on which the vehicle 2 is traveling and the lanes that make up the roads. The cooperative behavior data group 34 is a map that expresses the state and procedure of cooperative behavior between the vehicle 2 and moving objects around the vehicle 2.

[0022] The mobile object route prediction data group 35 is a collection of data related to the future predicted route of a mobile object. The mobile object trajectory prediction data group 36 is a collection of data related to the future predicted trajectory of a mobile object. A "route" expresses spatial information, without a time concept, about where on the road surface the object will travel and in what posture. In contrast, a "trajectory" adds a time concept to a route and expresses information about when, where, and in what posture the object will travel. In other words, since a "trajectory" involves time constraints, it is expressed for a specified time range (e.g., 5 seconds in the future).

[0023] The collision risk map data group 37 is a map that represents locations around the vehicle 2 where there is a risk of collision with obstacles such as stationary objects and moving objects, and the extent of the risk. The collision risk map data group 37 is represented, for example, as a grid map. The retention risk map data group 38 is a map that represents areas around the vehicle 2 where the retention of the vehicle 2 hinders the actions of moving objects other than the vehicle 2, and the degree of the hinderance. Like the collision risk map data group 37, the retention risk map data group 38 is represented by a grid map or the like.

[0024] The cruise control data group 39 is a collection of data related to plan information for controlling the cruise of the vehicle 2 generated by the cruise control planning unit 16. For example, the data includes a planned trajectory of the vehicle 2 and control command values ​​to be output to the actuator group 7. The communication unit 40 includes, for example, a network card conforming to a communication standard such as IEEE802.3 or CAN (Controller Area Network). The communication unit 40 transmits and receives data to and from other devices in the vehicle system 1 based on various protocols.

[0025] In this embodiment, the communication unit 40 and the processing unit 10 are described separately, but a part of the processing of the communication unit 40 may be executed in the processing unit 10. For example, a configuration may be adopted in which a hardware device equivalent in the communication processing is located in the communication unit 40, and other device drivers, communication protocol processing, and the like are located in the processing unit 10.

[0026] The external sensor group 4 is a collection of devices that detect the state around the vehicle 2. Examples of the external sensor group 4 include a camera device, a millimeter wave radar, LiDAR, and sonar. The external sensor group 4 detects environmental elements such as stationary objects and moving objects within a predetermined range from the vehicle 2, and outputs the detected elements to the in-vehicle network N. A "stationary object" refers to an obstacle that is unlikely to move from its location, such as a building or a road edge. A "moving object" refers to an obstacle that may move from its location, such as a vehicle other than the vehicle 2, a pedestrian, or an object that has fallen onto the road. Therefore, even if such movable obstacles are stationary, they are called "moving objects."

[0027] The vehicle sensor group 5 is a collection of devices that detect various conditions of the vehicle 2. For example, each vehicle sensor detects the position information, driving speed, steering angle, accelerator operation amount, brake operation amount, etc. of the vehicle 2, and outputs the information to the in-vehicle network N. The map information management device 6 is a device that manages and provides digital map information of the surroundings of the vehicle 2. The map information management device 6 is, for example, a navigation device or the like. The map information management device 6 teethFor example, the vehicle 2 is provided with digital road map data of a predetermined area including the vicinity of the vehicle 2, and is configured to identify the current position of the vehicle 2 on the map, i.e., 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 identified current position of the vehicle 2 and map data of the surrounding area are output to the in-vehicle network N.

[0028] The actuator group 7 is a group of devices that control control elements such as steering, braking, and accelerator that determine the movement of the vehicle. The actuator group 7 controls the movement of the vehicle based on operation information of the steering wheel, brake pedal, accelerator pedal, etc. by the driver and control information output from the electronic control unit 3. The HMI device group 8 is a group of devices that input information from the driver and passengers to the vehicle system 1 and notify information from the vehicle system 1 to the driver and passengers. The HMI device group 8 includes a display, a speaker, a vibrator, a switch, etc.

[0029] FIG. 2 is a diagram showing an example of a driving scene for explaining the operation of this embodiment. FIG. 2 is divided into upper and lower parts, and time has passed from the upper part of FIG. 2 to the lower part of FIG. 2. In the driving scene of FIG. 2, a narrow road 210 where vehicles cannot pass each other includes a retreat area 211 where the road width is partially wide. In this road environment, the host vehicle 2 is about to pass another vehicle 200. In the upper part of FIG. 2, the host vehicle 2 is depicted taking an action 252 of retreating toward an action goal 262 in the retreat area 211. Next to the host vehicle 2, the other vehicle 200 is depicted taking an action 251 of waiting at an action goal 261 so as not to impede the host vehicle 2's action of retreating to the retreat area 211.

[0030] Note that the behavior goal is provisionally set as a guideline for the target position and attitude of the corresponding behavior step in order to express the behavior procedure in the cooperative behavior, and is different from the actual target position and attitude in the cruise control plan and the actual behavior of the other vehicle 200. In addition, "standby" means a state at or below a predetermined speed, and includes not only zero speed but also extremely low speeds such as creep speed.

[0031] The lower diagram in Fig. 2 shows actions that are performed after the actions in the upper diagram are completed. When the host vehicle 2 reaches the action goal 262 in the evacuation area 211, the other vehicle 200 moves toward the action goal 263 (action 253) since it is now possible for the host vehicle 2 to pass the other vehicle 200. Then, the host vehicle 2 moves toward the action goal 264 (action 254) after the other vehicle 200 has left the vicinity, completing the cooperative action regarding passing each other. In this way, the cooperative action is expressed as a combination of dependent action steps between the host vehicle 2 and the other moving body. An action step is characterized by an action goal, which is an indication of the target position and attitude at the end point of the action step.

[0032] In this embodiment as well as in the example of Fig. 2, the vehicle 2 and the other vehicle 200 do not perform any particular mutual communication, but each predicts the other's actions. If the prediction is incorrect, smooth passing as shown in Fig. 2 cannot be achieved, but in this embodiment, the operation is described on the assumption that the other vehicle's actions can be correctly predicted. The vehicle 2 and the other vehicle 200 may communicate with each other and transmit their upcoming actions to each other.

[0033] Fig. 3 is a diagram showing an example of the structure of data stored in the cooperative behavior data group 34. The cooperative behavior data group 34 stores information related to the procedure of cooperative behavior as described in Fig. 2. The cooperative behavior data group 34 is composed of a plurality of records, and each record includes a behavior ID 301, a vehicle ID 302, a behavior goal 303, a dependent behavior ID 304, and the like. The behavior ID 301 is an identifier of the behavior step. In the following, when an expression "behavior XXX" is used, it means that the behavior ID 301 is "XXX".

[0034] The vehicle ID 302 is information on an identifier indicating the subject of the action of the action step. The subject is the vehicle 2 or a moving object that is a partner of the cooperative action of the vehicle 2, and an ID for identifying them is used. The action goal 303 is information on the end point of the action step, and corresponds to the action goal shown in Fig. 2. There are no particular limitations on the form of expression of the action goal, and it may be expressed as position coordinates corresponding to the end point, may be expressed as an area, or may be expressed including a posture.

[0035] The dependent action ID 304 is the action ID of the action step on which the action step depends. When the dependent action ID 304 is specified, it means that the specified action step must be completed before the action step. For example, actions 251 and 252 have no dependent action steps, so they are expressed as "N / A", and actions 253 and 254 depend on actions 252 and 253, respectively, so they are written as "252" and "253".

[0036] FIG. 4 is a diagram showing an example of data stored as a moving object route prediction data group 35 and a moving object trajectory prediction data group 36 for the actions 251 and 253 of the other vehicle 200 in the traveling scene of FIG. 2. The moving object route prediction data group 35 is a collection of data related to the future predicted route of the moving object. The predicted route of the moving object that is the target of the cooperative behavior is generated for each cooperative behavior step. The predicted routes 281 and 283 shown in FIG. 4 correspond to the predicted routes for the actions 251 and 253 of the other vehicle 200, respectively. The moving object trajectory prediction data group 36 is a collection of data related to the future predicted trajectory of the moving object. In FIG. 4, a predicted trajectory 271 of the other vehicle 200 is shown. The predicted trajectory is generated for a predetermined time range in the future, not for each cooperative behavior step, and therefore, in FIG. 4, a trajectory for a predetermined time range in the behavior 251 is shown.

[0037] Fig. 5 is a diagram showing an example of a collision risk map data group 37 and a stagnation risk map data group 38 in the driving scene of Fig. 2. In detail, the upper diagram of Fig. 5 shows an example of the collision risk map data group 37, and the lower diagram of Fig. 5 shows an example of the stagnation risk map data group 38.

[0038] The collision risk map is a map of locations where there is a risk of collision between the vehicle 2 and obstacles such as stationary objects or moving objects in the vicinity, and the extent of the risk. In the example shown in the upper diagram of Fig. 5, the collision risk between a road boundary (road edge), which is a stationary object, and another vehicle 200, which is a moving object, is indicated by hatching with dots indicated by reference numeral 291. One example of a representation form of the collision risk map is a lattice-like map (grid map) of collision risk values ​​at each position of coordinate values ​​(x, y), where x and y are each represented by variables, in a predetermined area defined by an orthogonal coordinate system centered on the current position of the vehicle 2.

[0039] The retention risk map is a map of areas where the vehicle 2 will hinder the behavior of the moving object if it is retained, and the retention risk, which is the degree of the hinderance. In the example shown in Fig. 5, the retention risk area 292 that will hinder the behavior of the other vehicle 200, which is the moving object to be coordinated, is expressed by hatching with diagonal lines. Furthermore, in the retention risk map, retention risks may be placed in areas where travel is not possible. Since the retention risk map is used to determine an appropriate waiting position and posture of the vehicle 2, in order to search for an area where it is possible to retain, it is preferable to place risks not only in areas that will hinder the behavior of the target moving object, but also in areas where travel is not possible.

[0040] However, in the example shown in this embodiment, the presence or absence of collision risk and retention risk is illustrated by the presence or absence of hatching, so the degree of risk is not expressed in the drawing. The degree of risk may be expressed as a binary value of the presence or absence of risk, or as a continuous value such as 0 to 100. In the following, the area where a collision risk exists is also referred to as a "collision risk area," and the area where a retention risk exists is also referred to as a "retention risk area." Furthermore, the collision risk area and retention risk area are collectively referred to as a "risk area."

[0041] In the example shown in the lower diagram of Figure 5, as with the collision risk map, congestion risks are also placed on road edges, which are stationary objects, i.e., areas shown with dotted hatching. However, since impassable areas have a different meaning from the actual congestion risk, it is desirable to configure the congestion risk map so that both can be distinguished. In Figure 5, the congestion risk is distinguished by the degree of congestion risk, with impassable areas shown with dotted hatching and actual congestion risk areas shown with diagonal hatching. The risk degree may be expressed as a discrete level, for example, three levels: high, medium, and low, or as a continuous numerical value.

[0042] The electronic control unit 3 determines and maps the risk of collision with obstacles such as stationary objects and moving objects present around the vehicle 2 and the risk of getting stuck, based on information acquired from the external sensor group 4, the vehicle sensor group 5, the map information management device 6, etc., and generates and outputs driving control information for the vehicle 2. The actuator group 7 controls each actuator of the vehicle 2 according to the driving control information described above. This realizes driving control of the vehicle 2. In addition, the electronic control unit 3 generates HMI information as information to be notified to the driver and passengers when controlling the driving of the vehicle 2, and outputs it to the HMI device group 8. This allows the driver to recognize driving risks, encourages safe driving, supports cooperative behavior with other vehicles, and presents the state of the vehicle system 1 during automatic driving to the driver and passengers.

[0043] Fig. 6 is a diagram showing the correlation between functions realized by the electronic control unit 3. The electronic control unit 3 is configured to execute the processes of the information acquisition unit 11, the cooperative action planning unit 12, the mobile object behavior prediction unit 13, the collision risk map generation unit 14, the retention risk map generation unit 15, the driving control planning unit 16, and the information output unit 17 shown in Fig. 1 in an appropriate order. A series of processes is executed periodically, for example, every 100 ms.

[0044] The information acquisition unit 11 acquires necessary information from other devices via the in-vehicle network N, and stores it in the storage unit 30. The information acquisition unit 11 acquires a sensor detection data group 31 from the external sensor group 4, a vehicle information data group 32 from the vehicle sensor group 5, and a road environment data group 33 from the map information management device 6, and passes them to a downstream processing unit.

[0045] The cooperative behavior planning unit 12 judges whether cooperative behavior with a mobile object around the vehicle 2 is necessary based on the sensor detection data group 31, the vehicle information data group 32, and the road environment data group 33 acquired from the information acquisition unit 11. When the cooperative behavior planning unit 12 judges that cooperative behavior is necessary, it determines and manages a procedure for cooperative behavior with the target mobile object. Then, the cooperative behavior planning unit 12 outputs a cooperative behavior data group 34 relating to the cooperative behavior procedure to the mobile object behavior prediction unit 13 and the driving control planning unit 16, respectively. When it judges that cooperative behavior is unnecessary, the cooperative behavior planning unit 12 may not perform any special process, or may output a message indicating that cooperative behavior is unnecessary to the HMI device group 8 via the information output unit 17.

[0046] The mobile object behavior prediction unit 13 predicts the paths and trajectories of mobile objects around the vehicle 2, and generates a mobile object path prediction data group 35 and a mobile object trajectory prediction data group 36. To generate these, the mobile object behavior prediction unit 13 uses the sensor detection data group 31 and the road environment data group 33 acquired from the information acquisition unit 11, and the cooperative behavior data group 34 output from the cooperative behavior planning unit 12. The mobile object path prediction data group 35 is output together with the cooperative behavior data group 34 to the stay risk map generation unit 15, and the mobile object trajectory prediction data group 36 is output to the collision risk map generation unit 14.

[0047] The collision risk map generating unit 14 estimates areas where a collision risk with the vehicle 2 exists and the degree of collision risk for each area for each obstacle included in the sensor detection data group 31, based on the vehicle information data group 32 and the moving object trajectory prediction data group 36. Then, the collision risk map generating 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 cruise control planning unit 16.

[0048] The stagnation risk map generating unit 15 extracts predicted route information of the mobile object of the cooperative behavior target based on the cooperative behavior data group 34 and the mobile object route prediction data group 35, and identifies an area where the behavior of the mobile object is hindered if the vehicle 2 is stagnated. The stagnation risk map generating unit 15 also identifies an area where travel is not possible based on information such as travel regulations included in the sensor detection data group 31 and the road environment data group 33. The stagnation risk map generating unit 15 combines these pieces of information to estimate areas where a stagnation risk exists and the degree of stagnation risk for each area, and maps the estimation results to generate a stagnation risk map data group 38. The generated stagnation risk map data group 38 is output to the driving control planning unit 16.

[0049] The driving control planning unit 16 plans a trajectory along which the vehicle 2 should travel, based on the cooperative behavior data group 34, the collision risk map data group 37, the delay risk map data group 38, and the like, and generates control command values ​​and the like for following the trajectory. Then, a driving control data group 39 including information such as the control command values ​​and various input information used for presenting information 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 driving control data group 39. Also, based on the cooperative behavior data group 34, the collision risk map data group 37, and the delay risk map data group 38, the HMI device group 8 outputs information for presenting to the occupants.

[0050] The operation of the electronic control unit 3 will be described in detail below using the driving scene shown in FIG.

[0051] (Processing of Collaborative Action Planning Unit 12) 7 is a flowchart showing the processing of the cooperative behavior planning unit 12. First, in step S501, the cooperative behavior planning unit 12 acquires the sensor detection data group 31, the vehicle information data group 32, and the road environment data group 33, which are driving environment information. Next, in step S502, the cooperative behavior planning unit 12 determines whether or not the current driving road environment makes it difficult to pass another vehicle. For example, the cooperative behavior planning unit 12 uses information such as the number of lanes and road width of the current road included in the road environment data group 33 to determine whether or not it is difficult to pass another vehicle.

[0052] When the cooperative behavior planning unit 12 determines that it is not difficult to pass the other vehicle (NO in step S502), it determines that cooperative behavior is not necessary, resets the cooperative behavior data group 34 in the storage unit in step S506, and ends the processing shown in Fig. 7. When the cooperative behavior planning unit 12 determines that it is difficult to pass the other vehicle (YES in step S502), it determines whether or not there is another vehicle (oncoming vehicle) ahead to pass based on the sensor detection data group 31 (step S503).

[0053] When the cooperative behavior planning unit 12 determines that there is no other vehicle ahead to pass (NO in step S503), it proceeds to step S506 and ends the processing shown in Fig. 7. When the cooperative behavior planning unit 12 determines that there is another vehicle ahead to pass (YES in step S503), it determines a cooperative behavior procedure for achieving passing with the other vehicle in step S504, stores the procedure as cooperative behavior data group 34 in the storage unit 30 in step S505, and ends the processing shown in Fig. 7.

[0054] The cooperative action procedure is determined, for example, by the positional relationship of the location of a temporary evacuation area for passing each other. In the case of the scene in Fig. 2, since the evacuation area 211 is located on the left side of the traveling direction of the host vehicle 2, it is natural for the host vehicle 2 to evacuate in a driving environment where vehicles drive on the left side of the road. As a result, the cooperative action procedure as shown in Fig. 2 and Fig. 3 is determined. Note that as the host vehicle 2 and the other vehicle 200 complete action steps according to the cooperative action procedure, the currently targeted action step is updated. In that case, the action step that has been completed is removed from the cooperative action procedure.

[0055] (Processing of mobile object behavior prediction unit 13) 8 is a flowchart showing the processing of the mobile object behavior prediction unit 13. First, in step S601, the mobile object behavior prediction unit 13 acquires the sensor detection data group 31, the road environment data group 33, and the cooperative behavior data group 34, and proceeds to step S602. The mobile object behavior prediction unit 13 sets all the mobile objects included in the sensor detection data group 31 one by one in order as processing target mobile objects, and predicts the travel route and travel trajectory of the processing target mobile object in steps S602 to S607.

[0056] In step S602, the mobile object behavior prediction unit 13 judges whether or not there is an unprocessed mobile object. When the mobile object behavior prediction unit 13 judges that there is no unprocessed mobile object (NO in step S602), the mobile object behavior prediction unit 13 ends the process shown in Fig. 8. When the mobile object behavior prediction unit 13 judges that there is an unprocessed mobile object, the mobile object behavior prediction unit 13 proceeds to step S603.

[0057] In step S603, the mobile object behavior prediction unit 13 judges whether or not the processing target is designated as a cooperative behavior target in the cooperative behavior data group 34. If the mobile object behavior prediction unit 13 judges that the processing target moving object is designated as a cooperative behavior target, the processing proceeds to step S604, and if the processing target moving object is not designated as a cooperative behavior target, the processing proceeds to step S607. In step S607, the mobile object behavior prediction unit 13 predicts the travel route and travel trajectory of the processing target moving object based on information such as lanes and traffic regulations included in the road environment data group 33, and proceeds to step S606.

[0058] In step S604, the mobile object behavior prediction unit 13 predicts a travel route for each cooperative behavior step corresponding to the processing target mobile object in the cooperative behavior data group 34. The cooperative behavior step corresponding to the processing target mobile object is determined based on whether the vehicle ID shown in FIG. 3 matches the ID of the processing target mobile object. In the case of a cooperative behavior step currently targeted by the processing target mobile object, a travel route for the behavior goal 303 is predicted based on the current state (position, posture, speed, etc.) of the processing target mobile object and the state of stationary objects and other mobile objects (including the own vehicle 2). In the case of a cooperative behavior step not currently targeted by the processing target mobile object, a travel route for the behavior goal 303 of the cooperative behavior step is predicted in the same manner from the behavior goal 303 of the cooperative behavior step that the processing target mobile object is scheduled to perform before that. In the example shown in FIG. 4, a predicted route 281 for the behavior 251 which is the currently targeted cooperative behavior step and a predicted route 283 for the behavior 253 which is the next targeted cooperative behavior step are generated.

[0059] Next, in step S605, the mobile object behavior prediction unit 13 predicts the travel trajectory of the processing target mobile object based on the predicted route in each cooperative action step generated in step S604, and proceeds to step S606. The prediction of the travel trajectory is performed within a set time range, unlike the travel route. Therefore, the position, attitude, speed, etc. of the processing target mobile object are estimated from the current state (position, attitude, speed, etc.) of the processing target mobile object based on the currently targeted cooperative action step. If the current cooperative action step is completed within a set time, the prediction is handed over to the next cooperative action step. In the example shown in FIG. 4, it is assumed that the other vehicle 200 is moving at a very low speed, and a predicted trajectory 271 is generated.

[0060] In step S606, the mobile object behavior prediction unit 13 stores the travel route and travel trajectory of the processing target mobile object predicted in step S605 or step S607 in the storage unit 30 as a mobile object route prediction data group 35 and a mobile object trajectory prediction data group 36, respectively. Then, the process returns to step S602, and the unprocessed mobile object but Repeat the process until none remain.

[0061] (Processing of collision risk map generating unit 14) 9 is a flowchart showing the processing of the collision risk map generating unit 14. First, in step S701, the collision risk map generating unit 14 acquires 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 generating unit 14 calculates a collision risk area and its degree for a stationary object included in the sensor detection data group 31. Since a stationary object does not move, the area where the stationary object exists becomes an area having a collision risk regardless of the passage of time.

[0062] Then, in step S703, the collision risk map generating unit 14 calculates the collision risk area and its degree for the moving object included in the sensor detection data group 31. Since the moving object may move, it is desirable to determine the collision risk area based on the moving object trajectory prediction data group 36, taking into consideration the influence of the movement over time. For example, the degree of collision risk may be calculated by calculating the probability distribution for each moving direction of the moving object or the probability distribution for each moving speed. In the following step S704, the collision risk map generating unit 14 maps the collision risk around the vehicle 2 calculated in steps S702 and S703 as a collision risk map. As described above, the upper diagram of FIG. 5 shows an example of a collision risk map for the scene in the upper diagram of FIG. 2. The road edge portion, which is a stationary object, and the predicted trajectory area of ​​the other vehicle 200, which is a moving object, are expressed as the collision risk. In the following step S705, the collision risk map generating unit 14 stores the created collision risk map in the storage unit 30 as the collision risk map data group 37, and ends the process shown in FIG. 9.

[0063] (Processing of retention risk map generating unit 15) 10 is a flowchart showing the process of the stay risk map generating unit 15. First, in step S801, the stay risk map generating unit 15 acquires the sensor detection data group 31, the road environment data group 33, the cooperative behavior data group 34, and the moving object route prediction data group 35. In the following step S802, the stay risk map generating unit 15 refers to the cooperative behavior data group 34 and judges whether or not a moving object to behave cooperatively (hereinafter, referred to as a "cooperative moving object") exists. If the stay risk map generating unit 15 judges that a cooperative moving object does not exist, it proceeds to step S809, and if it judges that a cooperative moving object exists, it calculates and maps the stay risk for the cooperative moving object in steps S803 to S808 as described below.

[0064] In step S803, the delay risk map generating unit 15 refers to the cooperative behavior data group 34 to identify the cooperative behavior step of the cooperative moving object to be executed next for the cooperative behavior step currently targeted by the vehicle 2 (hereinafter referred to as the "opponent's next step"). For example, in Fig. 3, if the cooperative behavior step currently targeted by the host vehicle 2 is behavior 252, the opponent's next step is behavior 253. The opponent's next step can be determined by searching for an entry whose dependent behavior ID 304 indicates the cooperative behavior step of the host vehicle 2.

[0065] Next, in step S804, the stay risk map generating unit 15 refers to the moving object route prediction data group 35, extracts a predicted route corresponding to the other side's next step, and estimates a predicted behavior area, which is an area where the cooperative moving object moves in the other side's next step. The predicted behavior area is obtained, for example, by calculating an area through which the cooperative moving object passes according to the predicted route. The shape of the cooperative moving object is obtained, for example, by referring to the recognition results of the external sensor group 4 included in the sensor detection data group 31. Since the recognition results of the external sensor group 4 and the predicted route contain errors, it is desirable to set the predicted behavior area taking these margins into consideration.

[0066] Next, in step S805, the staying risk map generating unit 15 performs the following steps on the mobile object that are scheduled to be performed before the next step on the other side and have not been completed: of The other party's incomplete step is identified. For example, in FIG. 3, when the other party's next step is the action 253, the action corresponds to the action 251. In the following step S806, the stay risk map generating unit 15 estimates a predicted action pre-area, which is an area in which the cooperative moving body moves in the other party's incomplete step, in the same procedure as in step S804.

[0067] In the next step S807, the stay risk map generating unit 15 calculates the area of ​​stay risk and its degree based on the predicted behavior area and the predicted behavior prior area estimated in steps S804 and S806, and maps the result as a stay risk map in step S808. For example, a uniform degree of stay risk is set in the predicted behavior area and the predicted behavior prior area. Also, for example, a relatively low stay risk may be set for a certain distance range in the predicted behavior area and the predicted behavior prior area. An example of setting a degree of stay risk will be described later with reference to FIG. 14 and FIG. 15.

[0068] The reason why the predicted routes of the next step of the other party that the cooperative moving object will perform after the current cooperative action step of the own vehicle 2 and the previous incomplete step of the other party are set as the congestion risk is as follows. That is, the standby position and attitude state at the time when the current cooperative action step of the own vehicle 2 ends have a direct influence. If the standby position and attitude of the own vehicle 2 obstruct the cooperative action step of the cooperative moving object, the cooperative moving object will be unable to move, resulting in a stalemate.

[0069] When mapping of the stay risk for the cooperative moving body is completed by the processing of steps S803 to S808, the stay risk map generating unit 15 maps the non-traveling area onto the stay risk map in step S809. Then, in the following step S810, the stay risk map generating unit 15 stores the stay risk map in the storage unit 30 as a stay risk map data group 38. The non-traveling area corresponds to, for example, an area where a stationary object exists or a no-traveling area indicated by the road environment data group 33 or the like. The risk level when mapping the non-traveling area is recorded so as to be distinguishable from the stay risk for the cooperative moving body.

[0070] Since information on impassable areas can be referenced by using it together with the collision risk map, it is sufficient that the congestion risk is at the very least mapped on the congestion risk map. The lower diagram of Fig. 5 mentioned above shows an example of a congestion risk map for the scene shown in the upper diagram of Fig. 2. In the lower diagram of Fig. 5, the predicted behavior area corresponding to the behavior 251 (predicted route 281) and behavior 253 (predicted route 283) of the other vehicle 200 is shown as a congestion risk area 292.

[0071] (Processing of driving control planning unit 16) 11 is a flowchart showing the processing of the driving control planning unit 16. First, in step S901, the driving control planning unit 16 acquires the sensor detection data group 31, the vehicle information data group 32, the cooperative behavior 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 cooperative behavior data group 34 to determine whether or not a cooperative moving object that is a moving object to be subjected to cooperative behavior exists. If the driving control planning unit 16 determines that no cooperative moving object exists, it proceeds to step S902. 9 If it is determined that a cooperative moving object exists, the process proceeds to step S903.

[0072] In step S903, the driving control planning unit 16 first identifies a target waiting position / posture in the current cooperative action step of the vehicle 2 with reference to the stay risk map included in the stay risk map data group 38. Then, in step S904, the driving control planning unit 16 generates a trajectory for the target waiting position / posture identified in step S903 with reference to the collision risk map included in the collision risk map data group 37, and proceeds to step S905. In step S907, the driving control planning unit 16 generates a trajectory for normal driving, and proceeds to step S905.

[0073] When the trajectory is generated in step S904 or step S907, the cruise control planning unit 16 generates cruise control information based on the trajectory in step S905. In the following step S906, the cruise control planning unit 16 stores the cruise control information generated in step S905 in the storage unit 30 as the cruise control data group 39, and ends the process shown in FIG.

[0074] An example of step S903 and step S904 will be described with reference to Fig. 12. Fig. 12 is a diagram showing how a trajectory 1001 of the host vehicle 2 is planned using the collision risk area 291 and the retention risk area 292 in the scene in the upper diagram of Fig. 2. In step S903, with reference to the retention risk area 292, an area without retention risk is searched for around the action goal 262 of the current cooperative action step of the host vehicle 2 in Fig. 2. In the case of this scene, since there is no retention risk at the position of the action goal 262, the position of the action goal 262 is set as the target waiting position / posture 1011. Then, in step S904, with reference to the collision risk area 291, a trajectory is planned for the target waiting position / posture 1011 such that the passing area of ​​the host vehicle 2 does not overlap with the collision risk.

[0075] As described above, by utilizing the retention risk map, the waiting position and posture at the completion of the current cooperative action step does not overlap with the action area of ​​the next cooperative action step of the other vehicles 200, and therefore does not hinder the cooperative action of the other vehicles 200. Note that in this embodiment, steps S903 and S904 have been described separately, but they may be performed simultaneously. In other words, a condition that satisfies a target waiting position and posture that does not overlap with the retention risk map and a trajectory that does not overlap with the collision risk map may be searched for simultaneously.

[0076] Fig. 13 is a diagram for explaining the operation of the vehicle system 1 in a scene different from that in Fig. 2. In Fig. 13, in addition to the scene configuration in Fig. 2, a stationary object 1110 that becomes an obstacle to traffic is present. Therefore, in the scene in the upper diagram of Fig. 13, the mobile object behavior prediction unit 13 predicts a travel route 1111 that avoids the stationary object 1110 in response to the behavior 251 of the other vehicle 200 in step S604. Therefore, in steps S803 to S808, the retention risk map generation unit 15 estimates a meandering predicted behavior area 1134 as a retention risk based on the travel route 1111 and the like, and generates a retention risk map 1103.

[0077] When the cruise control planning unit 16 calculates the target waiting position and attitude of the action 252 of the vehicle 2 by using the delay risk map 1103 in step S903, the portion indicated by reference numeral 1131 in FIG. 13 overlaps with the delay risk. Therefore, the cruise control planning unit 16 searches for a waiting position and attitude that does not overlap with the delay risk in the vicinity of the action target 262, and determines the target waiting position and attitude 1133. Since this waiting position and attitude does not overlap with the action area of ​​the other vehicle 200, it does not hinder the cooperative action of the other vehicle 200. As described above, in cooperative action with another moving object, by predicting the action area of ​​the cooperative action step of the moving object and setting the waiting position and attitude of the cooperative action step of the vehicle 2 so as to avoid it as a delay restriction area, it becomes possible to perform cooperative action smoothly without getting into a stalemate in various scenes.

[0078] According to the above-described first embodiment, the following advantageous effects can be obtained. (1) The electronic control unit 3 is mounted on a vehicle 2. 2 An information acquisition unit 11 acquires driving environment information related to the surrounding driving environment, i.e., a sensor detection data group 31, a vehicle information data group 32, and a road environment data group 33, a stay risk map generation unit 15 estimates a stay restriction area, which is an area in which the stay of the vehicle 2 is restricted and in which the movement of a moving body other than the vehicle 2 is hindered when the vehicle 2 stays, based on the driving environment information, and Restricted Areaand a cruise control planning unit 16 that plans cruise control of the vehicle 2 based on the above. Therefore, as illustrated in Figs. 12 and 13, smooth passing can be achieved.

[0079] (2) When the vehicle 2 needs to stay in a predetermined area, the driving control planning unit 16 plans driving control so that the vehicle 2 stays in an area that does not overlap with the stay restriction area in the predetermined area in step S903 of Fig. 11. Therefore, the vehicle 2 can wait in a position that does not overlap with the trajectory of the other vehicle 200, thereby realizing smooth passing by the other vehicle 200.

[0080] (3) A moving body other than the vehicle 2 refers to a moving body present around the vehicle that is included in the driving environment information. The electronic control device 3 includes a cooperative action planning unit 12 that determines a cooperative action procedure in cooperation with the moving body. The staying restricted area is an area in which the vehicle 2 staying there inhibits the action of the moving body in the cooperative action procedure. Therefore, the host vehicle 2 prevents a staying area that inhibits the action of the other vehicle 200. Tome Since the vehicle 200 is prevented from staying in the risk area, the vehicle 200 can smoothly pass another vehicle 200.

[0081] (4) The stay risk map generating unit 15 estimates a moving object estimated movement area through which the moving object may pass in the action of the moving object in the cooperative action procedure as shown in Fig. 10, and estimates a stay restriction area based on the moving object estimated movement area. Therefore, it is possible to prevent the passage of other moving objects from being obstructed.

[0082] (5) The cruise control planning unit 16 plans the target waiting position and attitude of the vehicle 2 in the cooperative action procedure as shown in steps S903 and S904 in FIG. 11 so as not to overlap with the stay-limit area.

[0083] (6) The electronic control device 3 includes a collision risk map generating unit 14 that estimates a collision risk area where there is a risk of the vehicle colliding with 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 does not remain in the retention risk area.

[0084] --Second embodiment-- A second embodiment of the electronic control device will be described with reference to Figs. 14 and 15. In the following description, the same components as in the first embodiment are given the same reference numerals, and differences will be mainly described. Points that are not particularly described are the same as in the first embodiment. This embodiment differs from the first embodiment mainly in that an appropriate waiting position and posture is determined by utilizing differences in the degree of congestion risk in a congestion risk map.

[0085] FIG. 14 is a diagram showing a driving scene for explaining the operation of the second embodiment and a part of the operation of the vehicle system 1 in the driving scene. Driving scenes 1200 and 1201 show the flow of cooperative behavior with another vehicle 1202. In the scene of FIG. 14, the host vehicle 2 is driving from the right side to the left side, and the cooperative behavior planning unit 12 predicts that the other vehicle 1202, which is driving on the side where the evacuation area exists, will evacuate to the evacuation area. In the driving scene 1200, the host vehicle 2 is too close to the other vehicle 1202, so that the other vehicle 1202 is hindered from taking an action 1212 to move to the evacuation area. Therefore, the host vehicle 2 takes an action 1211 to retreat. The driving scene 1201, which is the subsequent cooperative behavior procedure, is the same as the driving scene in the lower diagram of FIG. 2.

[0086] 14 indicate a collision risk map and a retention risk map, respectively, for the action 1211 of the traveling scene 1200. When mapping the retention risk of the other vehicle 1202 onto the retention risk map in steps S803 to S808, the retention risk map generating unit 15 in this embodiment arranges not only a main retention risk area 292-1 corresponding to a predicted behavior area related to the action 1212 of the other vehicle 1202, but also a low retention risk area 292-2 having a relatively low risk level around it.

[0087] The main delay risk area 292-1 means an area that certainly obstructs the action 1212 of the other vehicle 1202. The low delay risk area 292-2 means an area that may make it difficult for the other vehicle 1202 to perform the action 1212. The low delay risk area 292-2 exists on the outer periphery of the main delay risk area 292-1, and the low delay risk area 292-2 is set wide especially in the direction parallel to the traveling direction of the host vehicle.

[0088] If the vehicle 2 is close to the action area of ​​the other vehicle 1202, the driver of the other vehicle 1202 feels pressured by the need for higher precision than necessary. Therefore, the driver should move back so that there is enough space for the action 1212. 292-2 is In this way, the driving control planning unit 16 sets the delay risk, which is a relatively low risk, in step S903. 292-2 By determining the target waiting position and attitude 1230 so as to avoid the collision as much as possible, a sufficient space is secured for the action 1212 of the other vehicle 1202. This makes it possible to prevent pressure on the driver of the other vehicle 1202.

[0089] FIG. 15 is a diagram showing an example of a traveling scene for explaining the operation of the second embodiment. This is the same traveling scene as FIG. 14, but is different in that another vehicle 1253 exists behind the host vehicle 2. In this traveling scene, a collision risk area 1284 where there is a risk of collision with the other vehicle 1253 is set behind the host vehicle 2, so the host vehicle 2 cannot move backward as shown by the reference symbol 1280. Therefore, there is no space to completely avoid the low retention risk area 292-2, which has a relatively low risk level. In such a case, the electronic control device 3 allows the target waiting position and attitude of the host vehicle 2 to overlap the low retention risk area 292-2, which has a relatively low risk level.

[0090] Detention risk 292-2 isThis is set to allow for the ease of driving of other vehicles 1252, and does not necessarily hinder the actions 1262 of other vehicles 1252. It reflects the fact that passing each other in close proximity is unavoidable in a situation where there is not enough space between the vehicles. 292-1O Call 292-2 If the risk level is set uniformly, it becomes difficult to respond according to the situation, as in the scenes in Figures 14 and 15.

[0091] As described above, by considering not only the predicted action area of ​​the moving body of the cooperative action target but also the influence on the ease of the action of the moving body, and setting the stay risk wider than the predicted action area, it is possible to realize smooth cooperative action that takes into account the ease of the action of the moving body. Also, by setting the stay risk so that the risk level can be distinguished between an area that completely inhibits the action of the moving body of the cooperative action target and an area that affects the ease of the action of the moving body, it becomes possible to determine an appropriate target waiting position and attitude according to the situation, and smooth cooperative action can be realized.

[0092] According to the above-described second embodiment, the following advantageous effects can be obtained. (7) The retention risk area includes information on the degree of difficulty in taking action that is given to the moving object. That is, there is a main retention risk area 292-1 with a relatively high risk level and a low retention risk area 292-2 with a relatively low risk level. When there is no target waiting position and posture that does not overlap with the main retention risk area 292-1 and the low retention risk area 292-2, the cruise control planning unit 16 allows the planning of a target waiting position and posture that overlaps with the low retention risk area 292-2.

[0093] --Third embodiment-- A third embodiment of the electronic control device will be described with reference to Fig. 16. In the following description, the same components as those in the first embodiment are given the same reference numerals, and differences will be mainly described. Points that are not particularly described are the same as those in the first embodiment. This embodiment differs from the first embodiment mainly in that the mobile object behavior prediction unit 13 takes into account the possibility that a mobile object is present in a blind spot.

[0094] The mobile object behavior prediction unit 13 in this embodiment performs the following process in addition to the process in the first embodiment. That is, the mobile object behavior prediction unit 13 refers to the sensor detection data group 31 and the road environment data group 33, and predicts that a mobile object is present in the blind spot and will move so as to obstruct the movement of the host vehicle 2. A specific example will be described with reference to FIG.

[0095] FIG. 16 is a diagram showing an example of processing by the mobile object behavior prediction unit 13 in the third embodiment. FIG. 16 includes a driving scene 1301, a driving scene 1302, a collision risk map 1303, and a stay risk map 1304. In the driving scene 1301, the host vehicle 2 is stopped on a road in a traffic jam. There is a side road immediately ahead of the host vehicle 2 on the left side, which is in a blind spot of the sensor of the host vehicle 2, but there is a possibility that another vehicle may enter the road on which the host vehicle 2 is traveling. Under such circumstances, it is desirable not to stay in an area near the side road so as not to hinder the actions of other vehicles in preparation for the case in which another vehicle appears on the side road in the future.

[0096] In such a case, the stagnation risk map can be applied. In the first and second embodiments of the present invention, the mobile object behavior prediction unit 13 predicted the travel route and travel trajectory of the mobile object MO detected by the external sensor group 4 according to the processing flow of Fig. 8, but in this embodiment, the mobile object MO is further considered to include a virtual mobile object VMO. The virtual mobile object VMO is an embodiment of a mobile object that may not be detected in the blind spot of the external sensor group 4, or a mobile object that does not exist now but may appear in the future.

[0097] In the travel scene of FIG. 16, it is assumed that another vehicle will appear on a side road in the future, and a virtual other vehicle 1311 is placed as shown in a travel scene 1302. The mobile object behavior prediction unit 13 predicts a possible travel route for this virtual other vehicle 1311. Since the concept of time is not fixed for a virtual moving object, a travel trajectory is not predicted. Also, since the state of a virtual moving object is not fixed, there may be multiple candidates for its behavior (behavior 1312 and behavior 1313), but the mobile object behavior prediction unit 13 predicts travel routes for all candidates. Then, the stay risk map generation unit 15 places a stay risk as shown in a stay risk map 1304 according to the predicted route of the virtual moving object generated by the mobile object behavior prediction unit 13.

[0098] In the processing flow of FIG. 11, since the virtual other vehicle 1311 is not a target of the cooperative action, a negative determination is made in step S902, and the driving control planning unit 16 generates a normal driving trajectory in step S907. At this time, the driving control planning unit 16 uses the retention risk map to determine a waiting place in the case of a traffic jam. That is, the driving control planning unit 16 generates a trajectory so as not to stop in an area corresponding to the retention risk map 1304. When the preceding vehicle 1320 of the host vehicle 2 is stopped just ahead of a side road as in the driving scene of FIG. 16, there is a collision risk of the preceding vehicle 1320 ahead as shown in the collision risk map 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 and waits at the current position.

[0099] When 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, the host vehicle 2 determines that it can pass through the retention risk 1323 without staying there, and generates a trajectory for moving forward. Since staying means staying at a specific location or area for a certain period of time or more, even if it is impossible to pass through the retention risk at a certain point in time, the host vehicle 2 may enter the retention risk in the following cases. That is, if it is predicted that the host vehicle will be able to pass in the near future, such as when a vehicle in front of the preceding vehicle has started moving forward, and it is determined that the time spent in the retention risk area will be within a predetermined value, the host vehicle 2 may enter the retention risk.

[0100] According to the above-described third embodiment, the following advantageous effects can be obtained. (8) A moving body other than vehicle 2 refers to a moving body that may appear in the future around vehicle 2 estimated from driving environment information, such as virtual other vehicle 1311 in Fig. 16. Therefore, in this embodiment, a congestion risk map is generated on the assumption that another vehicle is present in the blind spot of host vehicle 2, so that the progress of the vehicle present in the blind spot is not impeded.

[0101] (9) The cruise control planning unit 16 plans cruise control so that the residence time in the residence limit area falls within a predetermined value.

[0102] --Fourth embodiment-- A fourth embodiment of the electronic control device will be described with reference to FIG. 17. In the following description, the same components as those in the first embodiment are given the same reference numerals, and differences will be mainly described. Points that are not particularly described are the same as those in the first embodiment. This embodiment is mainly different from the first embodiment in that the stay risk map generating unit 15 also maps areas where stopping is not possible on the stay risk map. The stay risk map generating unit 15 in this embodiment performs the following process in addition to the process in the first embodiment. That is, the stay risk map generating unit 15 reflects traffic regulations regarding stopping obtained from the road environment data group 33 on the stay risk map.

[0103] FIG. 17 is a diagram showing an example of processing of the stay risk map generating unit 15 in the fourth embodiment. FIG. 17 shows a driving scene 1401 and a corresponding stay risk map 1402. The driving scene 1401 shows a road marking of a no-stop area 1412 and a road sign 1414 indicating a no-parking / no-stop section 1413 on the road on which the vehicle 2 is traveling. The stay risk map generating unit 15 generates a stay risk map according to the processing flow of FIG. 10. At this time, the stay risk map generating unit 15 maps not only the no-drive area but also the no-stop area on the stay risk map in step S809. Information on the road markings and road signs can be obtained by referring to the road environment data group 33 acquired from the map information management device 6.

[0104] The retention risk map generating unit 15 identifies a no-stop area from information on road markings and road signs, and places a retention risk at the corresponding location. In Fig. 17, the no-stop area 1412 corresponds to a retention risk 1422, and the no-parking / stopping section 1413 corresponds to a retention risk 1423. Then, the driving control planning unit 16 generates a trajectory that does not stop on a retention risk, as in the third embodiment.

[0105] The information on traffic regulations such as road markings and road signs can be determined individually by the cruise control planning unit 16 by directly referring to the road environment data group 33. However, in automated driving on roads, various traffic regulations must be taken into consideration, and a place where the vehicle can stop or stay must be specified in consideration of the cooperative behavior with the moving object as described in the first to third embodiments, and it is cumbersome to construct a process for making individual determinations. In this embodiment, the factors that regulate the stay of the vehicle 2 are integrated and managed in a centralized manner as a stay risk map, making it possible to make a determination, thereby facilitating the cruise control planning unit 16 to specify an appropriate position and attitude where the vehicle can stay.

[0106] According to the above-described fourth embodiment, the following advantageous effects can be obtained. (10) The delay risk map generating unit 15 further estimates the delay risk area based on the traffic regulation information around the vehicle included in the driving environment information. Therefore, the electronic control unit 3 can achieve smooth passing with other vehicles while observing the traffic regulations.

[0107] (11) The traffic regulation information is a no-parking / no-stopping area or a no-stopping area as shown in Fig. 17. Therefore, the electronic control device 3 can realize smooth passing with other vehicles while observing traffic regulations such as no-parking / no-stopping areas and no-stopping areas.

[0108] --Fifth embodiment-- Hereinafter, a fifth embodiment of the electronic control device will be described with reference to Fig. 18 to Fig. 31. This embodiment differs from the previous embodiments in that it also takes into consideration what happens after the two vehicles pass each other. The same components as those in the first embodiment are given the same reference numerals and will not be described.

[0109] FIG. 18 is a block diagram showing an electronic control device according to a fifth embodiment. 3 2 is a functional block diagram showing the configuration of a vehicle system 2001 including: car Both 2 To The vehicle system 2001 recognizes the conditions of obstacles such as roads and surrounding vehicles around the other vehicle 2002, and then performs appropriate driving assistance and driving control. This driving assistance also includes the presentation of information to the driver of the vehicle 2.

[0110] 19 is a functional configuration diagram of the second driving control planning unit 2016. The second driving control planning unit 2016 calculates a target trajectory based on a risk map, environmental information, lane information, and map information. The second driving control planning unit 2016 includes a driving plan unit 2501 and a trajectory planning unit 2506. The driving plan unit 2501 calculates a driving mode candidate weight 3001 based on route information, environmental information, previous selection information 3005, and the like.

[0111] The candidate driving mode weight 3001 is a weight, or in other words a probability, of the host vehicle 2 executing each of a plurality of predetermined driving modes. The driving modes in this embodiment are four, namely, lane keeping, lane changing, obstacle avoidance, and passing, and the weights of each are indicated by values ​​V1 to V4, the total value of which is "100." In other words, the candidate target behavior weight 3001 is the value of V1 to V4. For example, when the host vehicle 2 is traveling on a straight road, there is no vehicle or object ahead that needs to be avoided, and the route information indicates that there is no need to change lanes to an adjacent lane, V1 corresponding to lane keeping is "100," and V2 to V4 are set to "0."

[0112] The trajectory planning unit 2506 includes a lane keeping trajectory generating unit 2502, a lane changing trajectory generating unit 2503, an obstacle avoidance trajectory generating unit 2504, a passing trajectory generating unit 2508, and a trajectory arbitration unit 2505. The lane keeping trajectory generating unit 2502 generates a trajectory for keeping the host vehicle 2 in the center of the lane in which the host vehicle 2 is currently traveling. The lane changing trajectory generating unit 2503 generates a trajectory for changing lanes to an adjacent lane of the lane in which the host vehicle 2 is currently traveling. The obstacle avoidance trajectory generating unit 2504 generates a trajectory for avoiding obstacles existing in the lane in which the host vehicle 2 is currently traveling. The passing trajectory generating unit 2508 generates a trajectory for passing other vehicles as described later.

[0113] The trajectory arbitration unit 2505 evaluates each trajectory generated by the lane keeping trajectory generation unit 2502, the lane change trajectory generation unit 2503, the obstacle avoidance trajectory generation unit 2504, and the passing trajectory generation unit 2508 based on the degree of safety with respect to objects present in the vicinity 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 trajectory and the object and the value of the driving mode candidate weight 3001. The trajectory arbitration unit 2505 specifies the driving mode with the best evaluation as the best mode, and generates driving control information so that the vehicle 2 drives along the trajectory of the best mode. Furthermore, the trajectory arbitration unit 2505 outputs the best mode to the operation plan unit 2501 as the previous selection information 3005.

[0114] 20 is a detailed configuration diagram of the passing trajectory generating unit 2508. The passing trajectory generating unit 2508 includes a management unit 2581, a trajectory generating unit 2582, and a cancel trajectory generating unit 2583. The management unit 2581 manages the passing state described below. The trajectory generating unit 2582 generates a passing trajectory. The cancel trajectory generating unit 2583 generates a cancel trajectory. The passing trajectory and the cancel trajectory will be described in detail later.

[0115] Fig. 21 is a flowchart showing the processing of the trajectory generating unit 2582 of the passing trajectory generating unit 2508. First, in step S3301, the trajectory generating unit 2582 acquires the sensor detection data group 31, the road environment data group 33, the cooperative behavior data group 34, the moving object trajectory prediction data group 36, the collision risk map data group 37, and the stay risk map data group 38. In the following step S3302, the trajectory generating unit 2582 refers to the cooperative behavior data group 34 to determine whether or not a cooperative moving object that is a moving object to behave cooperatively exists. If the trajectory generating unit 2582 determines that a cooperative moving object does not exist, it ends the processing shown in Fig. 21, and if it determines that a cooperative moving object exists, it proceeds to step S3305.

[0116] In step S3305, the trajectory generating unit 2582 generates a plurality of candidate evacuation positions and postures based on the collision risk map and the retention risk map. Details of the processing of this step will be described later with reference to the drawings. In the following step S3306, the trajectory generating unit 2582 generates candidate arrival positions that are candidates for arrival positions at which the passing mode is changed to another mode after passing the evacuation position. Details of the processing of this step will be described later with reference to the drawings.

[0117] In the next step S3307, the trajectory generating unit 2582 generates a trajectory candidate that passes through the evacuation position and posture candidates and the arrival position candidates. As described above, since there are a plurality of evacuation position and posture candidates, a plurality of trajectory candidates are also generated in this step. In the next step S3308, the trajectory generating unit 2582 evaluates each of the trajectory candidates generated in step S3307 and selects the trajectory with the highest evaluation. For example, the evaluation value used in this evaluation can be calculated so that the evaluation value is higher when the trajectory overlaps less with the retention risk area and the evaluation value is higher when the length of the trajectory is shorter. In the next step S3309, the trajectory generating unit 2582 stores information on the trajectory selected in step S3308 in the storage unit 30 as a trajectory generated by the trajectory generating unit 2582.

[0118] FIG. 22 is a diagram for explaining a method for generating candidates for an evacuation position and posture in step S3305 in FIG. 21. However, the generation method described here is merely an example, and candidates for an evacuation position and posture may be generated by other methods. As shown in FIG. 22, an oncoming vehicle 2200 that should act cooperatively is present ahead of the host vehicle 2. And, an evacuation space is present ahead of the host vehicle 2 on the left side. Since the retention risk area 2292 generated by the retention risk map generating unit 15 is present ahead of the host vehicle and on the host vehicle 2, in order to realize cooperative behavior, here passing driving, it is necessary to move the host vehicle 2 to a place where this retention risk area does not exist, that is, to evacuate.

[0119] Therefore, in the area where the retention risk area 2292 does not exist and does not contact the collision risk area 2291, Retirement Candidate avoidance posture positions (N1, θ1) to (N5, θ5) are generated. N represents the planar position, and θ represents the yaw angle of the vehicle 2. The number of candidate avoidance posture positions to be generated is arbitrary. The trajectory generating unit 2582 selects a location close to the retention risk area within a range in which the host vehicle 2 does not overlap with the retention risk area, taking into consideration the size of the host vehicle 2.

[0120] FIG. 23 is a diagram for explaining a method for generating the arrival position candidate in step S3306 in FIG. 21. However, the generation method described here is merely an example, and the arrival position candidate may be generated by other methods. First, the trajectory generating unit 2582 refers to the road environment data group 33 and identifies the center line 3501 of the driving lane in which the host vehicle 2 is traveling. Next, the trajectory generating unit 2582 calculates the distance L between the positions of the passing mode start point 3502 and the escape position and attitude candidate 3504 projected onto the center line 3501. Then, the trajectory generating unit 2582 sets a point on the center line 3501, which is a point that has progressed a distance L in the opposite direction from the passing mode start point 3502 from the position where the escape position and attitude candidate 3504 is projected, as the arrival position candidate 3503.

[0121] FIG. 24 is a diagram for explaining a method for generating trajectory candidates in step S3307 in FIG. 21. However, the generation method described here is merely an example, and trajectory candidates may be generated by other methods. The trajectory generating unit 2582 generates route candidates by combining straight lines and multiple arc curves as shown in FIG. 24. The trajectory generating unit 2582 can generate multiple route candidates by changing the length of the straight line portion, the radius of the arc curve, etc. The trajectory generating unit 2582 may use a clothoid curve instead of the arc curve. The trajectory generating unit 2582 may further set a speed for each trajectory.

[0122] The trajectory generating unit 2582 calculates a speed profile when the vehicle travels along the generated trajectory candidate. For example, the speed profile is set at each virtual time series point set every time the vehicle travels a predetermined distance or a predetermined time on the trajectory candidate. The speed set at each time series point may be a random value or a constant value. The trajectory generating unit 2582 creates multiple speed profiles and evaluates each speed profile using the following formula. In the following formula, the sum calculated for all time series points on the trajectory candidate is the evaluation value EVV of the speed profile. The trajectory generating unit 2582 sets the speed profile having the smallest evaluation value EV1 as the speed profile of the trajectory candidate.

[0123] EVV = Σ{w11 (longitudinal acceleration of the vehicle)^2 + w12 (lateral acceleration of the vehicle)^2 + w13 (speed limit - vehicle speed)^2 + w14 (value of collision risk map)^1} ··· Equation 1

[0124] In formula 1, w11 to w14 are each a predetermined coefficient. The collision risk map value 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 may 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.

[0125] Step S in Figure 21 3308 The trajectory generation unit 2582 evaluates each trajectory candidate from the following five viewpoints, and selects the trajectory with the best trajectory evaluation value EVR, which is the sum of the evaluation value and the weighting coefficient. low The trajectory candidate is adopted. The five viewpoints are safety, convenience, ride comfort, discomfort, and pressure on oncoming vehicles. The trajectory evaluation value EVR is expressed by the following Equation 2.

[0126] EVR=w1E1+w2E2+w3E3+w4E4+w5E5...Formula 2

[0127] In the formula 2, w1 to w5 are each a predetermined coefficient, and E1 to E5 are each an evaluation value for each of the five viewpoints mentioned above.

[0128] Safety is evaluated using the distance to surrounding objects and the apparent risk value. For example, the inverse of the minimum distance between the road and the route candidate or the collision risk map value can be used as the evaluation value. Convenience can be evaluated using the length of the entire trajectory or the length of the trajectory from the passing mode start point to the evacuation position and attitude candidate. The shorter the trajectory, the higher the convenience. The evaluation value is small. The reason for this is that if it takes a long time to perform an action to pass each other, the oncoming vehicle will have to wait for a long time, which may cause the occupants of the other vehicle and the vehicle itself to feel distrustful.

[0129] The evaluation of ride comfort uses the acceleration that occurs in a vehicle traveling along the calculated route and the jerk, which is the change in acceleration over time. For example, the value of (the inverse of the turning radius) x (the total turning angle) can be used as the evaluation index. This is based on the idea that a route with a large lateral acceleration or a long period of time during which lateral acceleration occurs is a poor ride. In other words, when the turning radius is small, Turn The larger the turning angle, the higher the evaluation value of the ride comfort. Small do.

[0130] The number of turns is used to evaluate the sense of discomfort. This is based on the idea that the more turns there are, the more uncomfortable the occupants of the vehicle 2 feel. The closest distance between the calculated route and another vehicle is used to evaluate the sense of oppression. For example, the reciprocal of the smallest distance between the center position coordinate of the other vehicle and the route candidate can be used as the evaluation index. The reason for this is that a route that comes too close to an oncoming vehicle makes the occupants of the vehicle and the other vehicle feel a sense of oppression.

[0131] 25 is a transition diagram of the passing state managed by the management unit 2581. The management unit 2581 manages the passing state that indicates the state of passing with an oncoming vehicle. There are four passing states: an initial state 2701, a passing execution state 2702, a passing completion state 2703, and a passing cancellation state 2704. The passing state at the start of operation is the initial state 2701, and transitions from the initial state 2701 are made as described below.

[0132] In the initial state 2701, if it is determined that passing is possible, the state transitions to a passing execution state 2702. In the initial state 2701 or the passing execution state 2702, if it is determined that passing is impossible, the state transitions to a passing cancellation state 2704. In the passing execution state 2702, if passing is completed, the state transitions to a passing completion state 2703, and if the state of an oncoming vehicle or environmental conditions change during passing and it is determined that passing is impossible, the state transitions to a passing cancellation state 2704. After transitioning to the passing completion state 2703 and the passing cancellation state 2704, the state returns to the initial state 2701. Each state will be described below.

[0133] 26 is a flowchart showing the process executed by the management unit 2581 in the initial state 2701. First, in step S2801, the management unit 2581 checks the passing request. 2 If the value of "V4", which is the weight of the driving mode corresponding to "passing" generated by 501, is equal to or greater than a predetermined value, a positive judgment is made and proceeds to step S2802, and if the value of "V4" is less than the predetermined value, a negative judgment is made and return is made to step S2801.

[0134] In step S2802, the management unit 2581 executes the passing trajectory generation unit 2508 The trajectory required for passing each other is generated using the above. Detailed processing of this step is as shown in FIG. 21. In the following step S2803, the management unit 2581 generates a cancel trajectory. The cancel trajectory is a trajectory from the current position of the vehicle 2 to the arrival position candidate, and is different from the passing trajectory. The cancel trajectory is, for example, a trajectory that connects the current position of the vehicle 2 to the arrival position candidate with a straight line.

[0135] Fig. 27 is a diagram showing an example of a passing trajectory and a cancel trajectory. In Fig. 27, a path leading to a possible arrival position 3503 via a possible evacuation position and attitude 3504 is a passing trajectory. On the other hand, a path leading to a possible arrival position 3503 from a current position of the vehicle 2 without passing through the possible evacuation position and attitude 3504 is a cancel trajectory. Returning to Fig. 26, the explanation will be continued.

[0136] In the next step S2804, the management unit 2581 judges whether or not passing is necessary. Specifically, the management unit 2581 refers to the collision risk map data group 37 and the retention risk map data group 38, and judges that passing is necessary if the cancel trajectory overlaps the risk area, and judges that passing is unnecessary if the cancel trajectory does not overlap the risk area. If the management unit 2581 judges that passing is necessary, it proceeds to step S2805, and if it judges that passing is unnecessary, it proceeds to step S2806. In step S2805, the management unit 2581 transitions the passing state to the passing execution state 2702 and ends the processing shown in FIG. 26. In step S2806, the management unit 2581 transitions the passing state to the passing cancellation state 2704 and ends the processing shown in FIG. 26.

[0137] Fig. 28 is a flowchart showing the processing executed by management unit 2581 in passing execution state 2702. First, in step S2811, management unit 2581 generates a trajectory required for passing running. Detailed processing of this step is as shown in Fig. 21. In the following step S2812, management unit 2581 generates a cancellation trajectory. The method of generating the cancellation trajectory is as explained in step S2803 of Fig. 26.

[0138] In the next step S2813, the management unit 2581 compares the generated passing trajectory and the cancellation trajectory, and performs an evaluation based on the indexes of safety and ride comfort. For example, if the management unit 2581 determines that there is a risk of the vehicle coming into close contact with another vehicle or a surrounding object if the vehicle is driven based on the passing trajectory, the management unit 2581 determines that the passing driving cannot be continued. If the management unit 2581 determines that the passing can be continued, the process proceeds to step S2814, and if the management unit 2581 determines that the passing cannot be continued, the process proceeds to step S2817.

[0139] Step S 2814 Then, the management unit 2581 sends the generated passing trajectory to the trajectory arbitration unit 2582. 2 The trajectory output is sent to the trajectory arbitration unit 505. 2 28. When the vehicle 2 is selected by 505, the vehicle 2 is controlled to travel along this trajectory. In the following step S2815, the management unit 2581 judges whether or not the position of the vehicle 2 has reached the end area of ​​the passing mode, that is, the arrival position candidate, based on the self-position information, lane information, and the like. If the management unit 2581 judges that the arrival position candidate has been reached, the process proceeds to step S2816, and if the management unit 2581 judges that the arrival position candidate has not been reached, the process returns to step S2811. In step S2816, the management unit 2581 transitions to the passing completion state 2703 and ends the process shown in FIG. 28. In step S2817, the management unit 2581 transitions the passing state to the passing cancellation state 2704 and ends the process shown in FIG. 28.

[0140] 29 is a flowchart showing the processing executed by the management unit 2581 in the passing completed state 2703. First, in step S2821, the management unit 2581 generates a lane-maintaining trajectory. Specifically, the management unit 2581 uses the lane-maintaining trajectory generation unit 2502, or by processing similar to that of the lane-maintaining trajectory generation unit 2502, to generate a trajectory for maintaining the driving lane in which the host vehicle 2 is currently traveling. In the following step S2822, the management unit 2581 uses the trajectory generated in step S2821 in the trajectory arbitration unit 2502. 2 The trajectory output is sent to the trajectory arbitration unit 505. 2When selected by 505, the host vehicle 2 is controlled to travel along this trajectory.

[0141] In the next step S2823, the management unit 2581 judges whether the same lane has been maintained for a predetermined time. If the management unit 2581 judges that the lane has been maintained for the predetermined time or more, the process proceeds to step S2824, and if the management unit 2581 judges that the time during which the lane has been maintained is less than the predetermined value, the process returns to step S2821. In step S2824, the management unit 2581 transitions the passing state to the initial state 2701, and ends the process shown in FIG.

[0142] 30 is a flowchart showing the process executed by the management unit 2581 in the passing cancellation state 2704. First, in step S2831, the management unit 2581 transfers the already calculated cancellation trajectory to the trajectory arbitration unit 2582. 2 The trajectory output is sent to the trajectory arbitration unit 505. 2 30. If the selected trajectory is selected by 505, the vehicle 2 is controlled to travel along this trajectory. In the following step S2832, the management unit 2581 judges whether or not the cancel trajectory has been maintained for a predetermined time, in other words, whether or not the vehicle 2 has traveled along the cancel trajectory. If the management unit 2581 judges that the cancel trajectory has been maintained for more than the predetermined time, the process proceeds to step S2833, and if the management unit 2581 judges that the time during which the cancel trajectory has been maintained is less than the predetermined value, the process returns to step S2831. In step S2833, the management unit 2581 transitions the passing state to the initial state 2701, and ends the process shown in FIG.

[0143] Figure 31 shows the electronic control device. 3 31 is a schematic diagram showing the movement of the vehicle 2 based on the processing of FIG. 31. In the scene shown in FIG. 31, the road is narrow, the vehicle 2 is automatically driven from the left side to the right side in the figure, and an oncoming vehicle is ahead of the vehicle 2. 2 The vehicle 2 detects that there is an escape area 211 in the left front direction based on at least one of the sensor detection data group 31 and the road environment data group 33. teethBased on the data, a passing trajectory 3003 is generated from the viewpoints of ride comfort, safety, etc. By generating the passing trajectory 3003, the vehicle can pass an oncoming vehicle without colliding with the oncoming vehicle. Bad for the crew Ride comfort and No This can prevent the user from feeling at ease.

[0144] According to the above-mentioned fifth embodiment, the following advantageous effects can be obtained. (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 generates an evacuation position candidate that is a candidate for an evacuation position where the vehicle is to escape from the moving body during a passing action (S3305 in FIG. 21), generates a destination position candidate that is a candidate for a destination position to be reached after passing the evacuation position candidate (S3306 in FIG. 21), generates a trajectory that passes through the current position of the vehicle, the position of the evacuation position candidate, and the position of the destination position candidate (S3307 in FIG. 21), and includes a passing trajectory generating unit 2508. Therefore, the electronic control device 3 can generate a trajectory that takes into account even after passing another moving body.

[0145] (13) The trajectory generating unit 2582 of the passing trajectory generating unit 2508 generates escape position candidates based on at least one of the size of the moving object and the speed of the moving object.

[0146] (14) The trajectory generation unit 2582 of the passing trajectory generation unit 2508 generates a plurality of trajectories, evaluates each of the plurality of trajectories, and selects the optimal trajectory (S3308 in FIG. 21).

[0147] (15) The trajectory generation unit 2582 of the passing trajectory generation unit 2508 evaluates each of the multiple trajectories based on at least one of safety, convenience, ride comfort, discomfort, and a feeling of pressure from an oncoming vehicle (S3308 in FIG. 21).

[0148] (Modification 1 of the fifth embodiment) In the above-described fifth embodiment, the trajectory generating unit 2582 determines the evacuation position and posture candidates by referring to the collision risk map and the stagnation risk map. However, the trajectory generating unit 2582 may determine the evacuation position and posture candidates without referring to the collision risk map and the stagnation risk map. For example, the trajectory generating unit 2582 may extract an evacuation area from the sensor detection data group 31 or the road environment data group 33, and set the evacuation position candidates randomly in the evacuation area, or may set the evacuation position and posture candidates in the evacuation area at a position farthest from the oncoming vehicle. Furthermore, the trajectory generating unit 2582 may set the evacuation position and posture candidates based on the speed of the host vehicle 2 and the speed of the oncoming vehicle, and the positional relationship between the host vehicle, the oncoming vehicle, and the evacuation area. For example, the evacuation position and posture candidates may be set in the evacuation area closest to the position where the host vehicle 2 and the oncoming vehicle collide when they run at the current speed.

[0149] (Modification 2 of the fifth embodiment) In the above-mentioned fifth embodiment, the trajectory generating unit 2582 evaluates the calculated multiple trajectory candidates from five viewpoints and adopts the route with the highest evaluation. However, the trajectory generating unit 2582 may calculate only one trajectory candidate and use that trajectory candidate without evaluating it, or may randomly use one trajectory candidate from the multiple trajectory candidates. In this case, however, the trajectory candidate may be appropriately corrected. For example, only one trajectory candidate may be calculated, and if an obstacle exists on that trajectory candidate, the trajectory candidate may be corrected to avoid the obstacle.

[0150] (Modification 3 of the fifth embodiment) Figure 2 9 In step S2824, the driving mode may be changed to the lane keeping mode, that is, the selection of the trajectory in the trajectory arbitration unit 2505 may be changed to the trajectory generated by the lane keeping trajectory generation unit 2502.

[0151] (Variation 4 of the fifth embodiment) In the embodiment described above, the trajectory generating unit 2582 determines not only the location to which the host vehicle 2 retreats but also the attitude of the host vehicle 2. However, the trajectory generating unit 2582 does not have to determine the attitude. That is, the "retreat position and attitude candidate" in the fifth embodiment may be replaced with an "retreat position candidate."

[0152] -Sixth embodiment- A sixth embodiment of the electronic control device will be described with reference to Figs. 32 and 33. In the following description, the same components as those in the fifth embodiment are given the same reference numerals, and differences will be mainly described. Points that are not particularly described are the same as those in the fifth embodiment. This embodiment differs from the fifth embodiment mainly in that the arrival position candidates are changed in consideration of the environmental conditions in the vicinity of the arrival position candidates.

[0153] Fig. 32 is a diagram showing an example of a scene in which the processing in the sixth embodiment is effective. In the example shown in Fig. 32, an obstacle 1801 such as a utility pole or a fallen object on the road is present near the arrival position candidate. In such a case, 5 Similarly to the embodiment of the present invention, if the arrival position candidate is set at a position symmetrical to the waiting position and posture candidate, the object will be detected immediately after the passing driving mode ends. 1 It will be necessary to avoid vehicle 801, which may cause anxiety to the occupants of vehicle 2.

[0154] Therefore, the passing trajectory generating unit 2508 in this embodiment generates a passing trajectory that takes into account the state near the arrival position candidate. That is, as shown in FIG. 33, several more arrival position candidates are generated around the arrival position candidate. Then, trajectory candidates are generated for all of them, all of the generated trajectory candidates are evaluated, and the optimal trajectory is selected. The additional arrival position candidates to be generated may be, for example, a candidate near the lane center line as shown in FIG. 1 501, a candidate arrival position is generated in the vertical direction. 1Candidates for the arrival position may be generated in the direction of an arc centered on the position 801. In this way, by generating a passing trajectory that takes into account the situation at the candidate arrival position, it becomes possible to switch safely even when the passing driving mode ends and switches to a lane keeping mode or a driving mode by an occupant.

[0155] According to the above-described sixth embodiment, the following advantageous effects can be obtained. (16) The trajectory generating unit 2582 of the passing trajectory generating unit 2508 determines the escape position candidate based on the output of the external sensor group 4 that senses the surroundings of the vehicle. The trajectory generating unit 2582 generates a position where no object exists within a predetermined distance as the escape position candidate. In other words, the trajectory generating unit 2582 excludes a position where an object exists within a predetermined distance from the escape position candidate. Therefore, an operation to avoid an object immediately after the passing driving mode ends is avoided.

[0156] --Seventh embodiment-- A seventh embodiment of an electronic control device will be described with reference to Fig. 34. In the following description, the same components as those in the fifth embodiment are denoted by the same reference numerals, and differences will be mainly described. Points that are not particularly described are the same as those in the fifth embodiment. This embodiment differs from the fifth embodiment mainly in that blind spots are taken into consideration when selecting candidates for an evacuation position and attitude.

[0157] 34 is a diagram showing an example of a scene in which the processing in the seventh embodiment is effective. The electronic control unit 3 in this embodiment selects a candidate evacuation position and posture while avoiding a blind spot area. In FIG. 34, a blind spot generating object such as a high wall is present near a road boundary 3901. 2901 Due to this blind spot generating object 2901, a blind spot area 4002 for the external sensor group 4 is generated near the evacuation space. In the blind spot area 4002, there is a possibility that a large obstacle 4003 or the like is present.

[0158] When the trajectory generating unit 2582 generates three candidates of symbols 3961 to 3963 as the turning-off position and posture candidates, it is not preferable to adopt the symbol 3961 since it may become difficult to stop the vehicle due to an obstacle 4003. Therefore, when a blind spot area exists, the trajectory generating unit 2582 selects the turning-off position and posture candidates by excluding those existing within a predetermined distance from the blind spot area 4002. However, instead of uniformly excluding them, the trajectory generating unit 2582 may add the distance between the candidate trajectory and the blind spot area to the evaluation items of the candidate trajectory.

[0159] According to the above-described seventh embodiment, the following advantageous effects can be obtained. (17) The trajectory generation unit 2582 of the passing trajectory generation unit 2508 determines the candidate evacuation position based on the output of the group of external sensors 4 that senses the surroundings of the vehicle. The trajectory generation unit 2582 generates positions that are not in the blind spots of the group of external sensors 4 as the candidate evacuation positions. In other words, the trajectory generation unit 2582 excludes the blind spots of the group of external sensors 4 from the candidate evacuation positions. In passing driving in a state where such blind spots exist, by generating a passing trajectory that takes the blind spots into consideration, the target evacuation position and posture or the target trajectory will not change during passing driving, and the occupants can be assured of the safety of the vehicle. Bad ride This will no longer cause discomfort or anxiety.

[0160] --Eighth embodiment-- An eighth embodiment of an electronic control device will be described with reference to Figs. 35 and 36. In the following description, the same components as those in the fifth embodiment are given the same reference numerals, and differences will be mainly described. Points that are not particularly described are the same as those in the fifth embodiment. This embodiment differs from the fifth embodiment mainly in that a notification is given when it is impossible to generate a route.

[0161] FIG. 35 is a functional configuration diagram of the second driving control planning unit 2016 in the eighth embodiment. The second driving control planning unit 2016 in this embodiment further includes a notification unit 2509 in addition to the configuration of the second driving control planning unit 2016 in the fifth embodiment. The notification unit 2509 notifies the outside of the output of the trajectory arbitration unit 2505. The notification destination is not limited to the inside of the vehicle 2, but may be the surroundings of the vehicle 2 or a remote location. The notification method may be any of sound, video, and vibration, and may be notified via communication rather than directly. That is, the notification unit 2509 can be realized by an audio output device, a video output device, a vibrator, a communication module, and the like.

[0162] In the present embodiment, when there is no trajectory on which the vehicle 2 can travel, the second driving control planning unit 2016 notifies the occupants of the vehicle 2, etc., via the notification unit 2509 that it is impossible to generate a route. As described above, the trajectory arbitration unit 2505 controls the lane keeping trajectory generation unit 2502, the lane change trajectory generation unit 2503, the obstacle avoidance trajectory generation unit 2504, the passing trajectory generation unit 2508, of The trajectory arbitration unit 2505 evaluates the trajectories generated by each of them. For example, if the trajectory arbitration unit 2505 determines that both trajectories will collide with an obstacle, it notifies the user that generation of a route is impossible.

[0163] FIG. 36 is a diagram showing an example of a scene where the process in the eighth embodiment is effective. In FIG. 36, a following vehicle 1901 exists behind the host vehicle 2, and another vehicle 200 exists in front of the host vehicle 2. The host vehicle 2 generates a passing trajectory, but since the other vehicle 200 approaches the host vehicle 2, the outside of the road, the following vehicle 1901, and a collision risk area 291 caused by the other vehicle 200 surround the host vehicle 2. In this state, the host vehicle 2 cannot move in any direction because it will come into contact with the collision risk area 291. Therefore, the second driving control planning unit 2016 notifies the occupant of the host vehicle 2 or the like that it is impossible to generate a route. As a result, it is expected that the situation will improve if, for example, the occupant of the host vehicle 2 drives the vehicle himself.

[0164] According to the above-described eighth embodiment, the following advantageous effects can be obtained. (18) The trajectory arbitration unit 2505 determines a trajectory for the vehicle 2 to travel from a plurality of trajectories including the trajectories generated by the passing trajectory generation unit 2508 and the lane keeping trajectory generation unit 2502, and notifies the fact that the trajectory cannot be calculated via the notification unit 2509 if there is no trajectory on which the vehicle 2 can travel. Therefore, it is expected that the situation will improve by notifying the occupant of the vehicle 2 or the like that a route cannot be generated and, for example, by the occupant of the vehicle 2 driving the vehicle himself / herself.

[0165] In each of the above-mentioned embodiments and modifications, the configuration of the functional blocks is merely an example. Some functional configurations shown as separate functional blocks may be integrated, or a configuration shown in one functional block diagram may be divided into two or more functions. In addition, some of the functions of each functional block may be provided by other functional blocks.

[0166] In the above-described embodiments and modifications, the program is stored in a ROM (not shown), but the program may be stored in the storage unit 30. The electronic control device may have an input / output interface (not shown), and the program may be read from another device via a medium available to the electronic control device and the input / output interface when necessary. The medium here refers to, for example, a storage medium that is detachable from the input / output interface, or a communication medium, i.e., a wired, wireless, optical, or other network, or a carrier wave or digital signal that propagates through the network. Some or all of the functions realized by the program may be realized by a hardware circuit or an FPGA.

[0167] The above-mentioned embodiments and modifications may be combined with each other. Although various embodiments and modifications have been described above, the present invention is not limited to these. Other aspects that are conceivable within the scope of the technical idea of ​​the present invention are also included in the scope of the present invention. [Explanation of symbols]

[0168] 2: Vehicle, own vehicle 3: Electronic control device 11: Information acquisition department 12: Cooperative Action Planning Division 13: Mobile behavior prediction unit 14: Collision risk map generation unit 15: Delay risk map generation unit 16: Driving control planning section 17: Information output section 37: Collision risk map data set 38: Detention risk map data set 291: Collision risk area 292: Retention risk area 292-1: Main retention risk area 292-2: Low retention risk area 2 501: Operation Planning Department 2 016: 2nd Driving Control Planning Division 2505:Trajectory Mediation Department 2508 : Passing each other Trajectory generation part

Claims

1. An electronic control device mounted on a vehicle, An information acquisition unit that acquires driving environment information related to a driving environment around the vehicle; a retention risk area estimation unit that estimates a retention restriction area, which is an area in which the retention of the vehicle will hinder the movement of other moving bodies that are moving bodies other than the vehicle, based on the driving environment information, and is an area in which the retention of the vehicle is restricted; A driving control planning unit that plans driving control of the vehicle based on the estimated stay limit area, The other moving object is a moving object present around the vehicle and included in the driving environment information, A cooperative action planning unit that determines a procedure for cooperative action with the other moving object, The stay restriction area is an area in which the vehicle, if stayed in, inhibits the action of the other moving object in the cooperative action procedure.

2. 2. The electronic control device according to claim 1, The driving control planning unit, when it is necessary for the vehicle to stay in a predetermined area, plans driving control so that the vehicle stays in an area in the predetermined area that does not overlap with the stay restriction area.

3. 2. The electronic control device according to claim 1, The stay risk area estimation unit is an electronic control device that estimates a moving object estimated movement area through which the other moving object may pass during the action of the other moving object in the cooperative action procedure, and estimates the stay restriction area based on the moving object estimated movement area.

4. 2. The electronic control device according to claim 1, The driving control planning unit plans a target waiting position and attitude of the vehicle in the cooperative action procedure so as not to overlap with the stay-limit area.

5. 5. The electronic control device according to claim 4, the stay restriction area includes information regarding a degree of difficulty in moving the other moving bodies; The electronic control device, wherein the driving control planning unit allows planning of a target waiting position and attitude that overlaps with the area with a low degree of difficulty in moving when there is no target waiting position and attitude that does not overlap with the stay-restricted area.

6. 2. The electronic control device according to claim 1, The driving control planning unit plans driving control so that a residence time in the residence limit area falls within a predetermined value.

7. 2. The electronic control device according to claim 1, The other moving object is a moving object that may appear in the future around the vehicle, which is estimated from the driving environment information.

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

9. 9. The electronic control device according to claim 8, The traffic regulation information is a no parking or no stopping area or an area where stopping is not permitted.

10. 2. The electronic control device according to claim 1, A collision risk area estimation unit that estimates a collision risk area in which there is a risk that the vehicle will collide with an obstacle based on the driving environment information, The driving control planning unit plans driving control such that the vehicle does not enter the collision risk area and does not remain in the stay restriction area.

11. A planning method executed by an electronic control unit mounted on a vehicle, comprising: Obtaining driving environment information relating to a driving environment around the vehicle; Based on the driving environment information, estimating a stay restriction area, which is an area in which the stay of the vehicle will hinder the movement of other moving bodies that are moving bodies other than the vehicle and is an area in which the stay of the vehicle is restricted; and planning a travel control of the vehicle based on the estimated stay limit area; The other moving object is a moving object present around the vehicle and included in the driving environment information, determining a cooperative action procedure in cooperation with the other moving object; The staying restricted area is an area in which the vehicle's staying is likely to inhibit the behavior of the other moving objects in the cooperative action procedure.

12. An electronic control device mounted on a vehicle, An information acquisition unit that acquires driving environment information related to a driving environment around the vehicle; a retention risk area estimation unit that estimates a retention restriction area, which is an area in which the retention of the vehicle will hinder the movement of other moving bodies that are moving bodies other than the vehicle, based on the driving environment information, and is an area in which the retention of the vehicle is restricted; A driving control planning unit that plans driving control of the vehicle based on the estimated stay limit area, generating a candidate evacuation position for causing the vehicle to evacuate from the other moving body when passing the other moving body, at a position not overlapping with the stay limit area; generating a candidate arrival position which is a candidate arrival position to be reached after passing the candidate evacuation position; The electronic control device further includes a passing trajectory generating unit that generates a trajectory that passes through a current position of the vehicle, the positions of the candidate evacuation positions, and the positions of the candidate arrival positions.

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