Vehicle control device and vehicle control method

Abstract

Provided is a vehicle control device capable of sequentially updating information that is necessary for mutual passing on a narrow road in a cooperative manner. This vehicle control device comprises: a passable region candidate determination unit that determines a mutually passable region on a road in which a mutually non-passable region is present; a mobile body movement information detection unit that detects movement information pertaining to a mobile body; a mutual passage pattern estimation unit that estimates at least one or more mutual passage patterns, which are combinations of action steps of each of a host vehicle and a mobile body, for the host vehicle and the mobile body to pass each other on the road; a mobile body action matching level evaluation unit that evaluates the level of matching of the action steps of the mobile body when the host vehicle and the moving body pass each other in the mutually passable region, with respect to a predicted action of the mobile body predicted on the basis of the movement information; a mutual passage pattern selection unit that selects at least one mutual passage pattern on the basis of the matching level; and an autonomous driving / driving assistance information generation unit that generates information to be used in autonomous driving and / or driving assistance of the host vehicle for mutual passage of the host vehicle and the mobile body in the selected mutual passage pattern.

Description

Vehicle control device and vehicle control method

[0001] The present invention relates to a vehicle control device and a vehicle control method suitable for driving assistance or automatic driving.

[0002] In recent years, there has been a demand for technology that enables cooperative driving on narrow roads in order to realize comfortable and safe driving assistance and autonomous driving of vehicles. In particular, a driving assistance system has been proposed that, when encountering an oncoming vehicle on a narrow road, allows the vehicle to cooperatively pass the oncoming vehicle while utilizing available space to pass.

[0003] For example, the abstract of Patent Document 1 states that the problem is to "provide a driving assistance system that enables safe and smooth passing," and that the solution is to "in-vehicle control device 50 evaluates the driver's driving skill regarding passing maneuvers based on the driver's driving history, and calculates at least one passing position and the ease of passing at that passing position on the road where the vehicles will pass, based on vehicle body information and the road conditions evaluated by the center control device 10. The center control device 10 evaluates the road conditions necessary for passing based on road information of the road where the vehicles will pass, and determines the easiest passing position and passing method based on the driver's driving skill evaluated by the in-vehicle control device 50 and at least one passing position and the ease of passing at that passing position calculated by the passing ease calculation process, and notifies the driver of the determined passing position and passing method by the notification means 70."

[0004] Japanese Patent Application Laid-Open No. 2008-217079

[0005] However, when passing an oncoming vehicle on a narrow road, the oncoming vehicle may behave in a way that is unexpected for the driving assistance system. For example, even if the easiest passing location and passing method determined by the driving assistance system based on the driver's driving skill is a scenario in which the host vehicle waits in a pull-out space on the left side of the narrow road while the oncoming vehicle passes through the narrow road, the oncoming vehicle may actually wait in a pull-out space on the right side of the narrow road and prompt the host vehicle to pass through.

[0006] Even in such cases, the driving assistance system of Patent Document 1 does not update the information it notifies the driver (the easiest passing location and passing method), so the driver has to determine for himself or herself the easiest passing location and passing method in the current environment, taking into account his or her own driving skills.

[0007] Therefore, the present invention aims to provide a vehicle control device and a vehicle control method that can sequentially update information necessary for cooperative mutual passage through narrow roads, taking into account the actual behavior of surrounding moving objects.

[0008] In order to solve the above problem, the vehicle control device of this embodiment is a vehicle control device that includes a passable area candidate determination unit that determines one or more mutually passable areas in which the host vehicle and the moving body can pass each other on a road that has a mutually impassable area where the host vehicle and the moving body cannot pass each other; a moving body movement information detection unit that detects movement information of the moving body; a mutually passable pattern estimation unit that estimates at least one mutually passable pattern that is a combination of the behavior steps of the host vehicle and the moving body for the host vehicle and the moving body to pass each other on the road; a moving body behavior agreement level evaluation unit that evaluates the agreement level between the predicted behavior of the moving body predicted based on the movement information and the behavior steps of the moving body when the host vehicle and the moving body pass each other in the mutually passable area; a mutually passable pattern selection unit that selects at least one mutually passable pattern based on the agreement level; and an automatic driving / driving assistance information generation unit that generates information to be used for automatic driving and / or driving assistance of the host vehicle for the host vehicle and the moving body to pass each other in the selected mutually passable pattern.

[0009] According to the vehicle control device and vehicle control method of the present invention, it is possible to successively update information required for cooperative mutual passage through a narrow road, taking into account the actual behavior of surrounding moving bodies.

[0010] 4A . A functional block diagram of a vehicle system according to a first embodiment. A functional block diagram illustrating functions of a processing unit of a vehicle control device according to a first embodiment. A top view showing an example of a mutual passing situation. A top view showing an example of a mutual passing pattern estimated in the mutual passing situation of FIG. 3A. A top view showing another example of the mutual passing situation. A top view showing an example of a mutual passing pattern estimated in the mutual passing situation of FIG. 4A. A top view showing another example of the mutual passing pattern estimated in the mutual passing situation of FIG. 4A. An example of a mutual passing pattern data group. An example of a behavior agreement level data group. A flowchart of mobile object behavior agreement level evaluation by a vehicle control device according to a first embodiment. An example of a mobile object behavior agreement level calculated by a vehicle control device according to a first embodiment. A flowchart of mobile object behavior agreement level evaluation by a vehicle control device according to a second embodiment. An example of a mobile object behavior agreement level calculated by a vehicle control device according to a second embodiment. A flowchart of mobile object behavior agreement level evaluation by a vehicle control device according to a third embodiment. An example of a mobile object behavior agreement level calculated by a vehicle control device according to a third embodiment.

[0011] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. However, the present invention is not limited to the following embodiments, and various modifications and application examples within the technical concept of the present invention are also included within its scope.

[0012] First, a vehicle control device according to a first embodiment of the present invention will be described with reference to FIGS. 1 to 8. FIG.

[0013] FIG. 1 is a functional block diagram showing the configuration of a vehicle system 1 including a vehicle control device 3 according to the present embodiment. The vehicle system 1 is mounted on a vehicle 2 (sometimes referred to as "host vehicle V0" to distinguish it from other vehicles) and has a function of checking the status of roads and obstacles, such as surrounding vehicles, around the vehicle 2, and then providing appropriate driving assistance and driving control. To achieve this function, the vehicle system 1 includes a vehicle control device 3, an external sensor group 4, a vehicle sensor group 5, a map information management device 6, an actuator group 7, an HMI device group 8, and an external communication device 9, all of which are connected via an in-vehicle network N. Below, the external sensor group 4 through the external communication device 9 will be outlined in order, followed by a detailed description of the vehicle control device 3 according to the present embodiment.

[0014] The external sensor group 4 is a collection of devices that detect the conditions around the host vehicle V0. Examples of the external sensor group 4 include a camera device, millimeter-wave radar, LiDAR, sonar, etc. The external sensor group 4 detects environmental elements such as obvious obstacles, road markings, signs, and traffic lights within a predetermined range from the host vehicle V0, and outputs these detection results to the vehicle control device 3 via the in-vehicle network N. "Obvious obstacles" include, for example, other vehicles other than the host vehicle V0, pedestrians, objects fallen on the road, road edges, etc. "Road markings" include, for example, white lines, crosswalks, stop lines, etc. The external sensor group 4 also outputs information about the detection conditions to the vehicle control device 3 via the in-vehicle network N based on its own sensing range and conditions.

[0015] The vehicle sensor group 5 is a collection of devices that detect various conditions of the host vehicle V0. Each vehicle sensor detects, for example, the position information, traveling speed, steering angle, accelerator operation amount, brake operation amount, etc. of the vehicle 2, and outputs the information to the vehicle control device 3 via the in-vehicle network N.

[0016] The map information management device 6 is a device that manages and provides digital map information about the area around the host vehicle V0. The map information management device 6 is configured, for example, by a navigation device or the like. The map information management device 6 is provided with digital road map data for a predetermined area including the area around the host vehicle V0, and is configured to identify the current position of the host vehicle V0 on the map, i.e., the road and lane on which the host vehicle V0 is traveling, based on the position information of the host vehicle V0 output from the vehicle sensor group 5. Furthermore, the identified current position of the host vehicle V0 and map data about the area around the vehicle V0 are output to the vehicle control device 3 via the in-vehicle network N.

[0017] 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 host vehicle V0. The actuator group 7 controls the movement of the control elements such as steering, braking, and accelerator based on operation information of the steering wheel, brake pedal, accelerator pedal, etc. by the driver and control command values ​​output from the vehicle control device 3, thereby controlling the behavior of the host vehicle V0 and performing autonomous driving.

[0018] The HMI device group 8 is a group of devices for inputting information from the driver and passengers to the vehicle system 1 and notifying the driver and passengers of information from the vehicle system 1. The HMI device group 8 includes a display, a speaker, a vibrator, a switch, etc.

[0019] The external communication device 9 is a communication module that performs wireless communication with the outside of the vehicle system 1. The external communication device 9 is configured to be able to communicate with, for example, a center system (not shown) that provides and distributes services to the vehicle system 1 and the Internet.

[0020] <Vehicle control device 3> The vehicle control device 3 is an ECU (Electronic Control Unit) mounted on the vehicle 2. As shown in Fig. 2 , the vehicle 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, or an external communication device 9 (not shown), and outputs the information to an actuator group 7, an HMI device group 8, and the external communication device 9. The vehicle control device 3 has a processing unit 10, a storage unit 30, and a communication unit 40. Details of each unit will be described below in order.

[0021] <<Processing Unit 10>> The processing unit 10 is configured to include, for example, a central processing unit (CPU), which is a central processing unit. However, in addition to the CPU, the processing unit 10 may also include a graphics processing unit (GPU), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), etc., or may be configured with only one of them.

[0022] The processing unit 10 has, as control functions, an information acquisition unit 11, a passable area candidate determination unit 12, a mobile object movement information detection unit 13, a mutual passing pattern estimation unit 14, a mobile object behavior agreement level evaluation unit 15, a mutual passing pattern selection unit 16, an automatic driving / driving assistance information generation unit 17, and an information output unit 18. The CPU and other components constituting the processing unit 10 execute predetermined control programs stored in the storage unit 30 to realize these control functions.

[0023] <<<Information Acquisition Unit 11>>> The information acquisition unit 11 acquires various pieces of information from other devices connected to the vehicle control device 3 via the in-vehicle network N, and stores the information in the storage unit 30. For example, the information acquisition unit 11 acquires information related to the behavior of the vehicle 2, such as the movement and state, detected by the vehicle sensor group 5, etc., and stores the information in the storage unit 30 as a vehicle information data group 31. The information acquisition unit 11 also acquires information related to the road environment on which the vehicle 2 is traveling from the map information management device 6, the external communication device 9, etc., and stores the information in the storage unit 30 as a road environment data group 32. The information acquisition unit 11 also acquires information related to obstacles around the vehicle 2 detected by the external sensor group 4 and the detection area of ​​the external sensor group 4, and stores the information in the storage unit 30 as a sensor recognition data group 33.

[0024] <<<<Passable area candidate determination unit 12>>> After identifying the moving body opposing the host vehicle V0, the passable area candidate determination unit 12 takes into consideration the road width, the host vehicle width, the moving body width, the presence or absence of obstacles, etc., and determines a wide area (hereinafter referred to as a "mutually passable area") in which the host vehicle V0 and the oncoming moving body can pass each other without difficulty, and a narrow area (hereinafter referred to as a "mutually impassable area") in which it is impossible or difficult for the two to pass each other.

[0025] Here, the passable area candidate determination unit 12 identifies a moving object that will pass the host vehicle V0, the moving object's width, the presence or absence of obstacles, etc., based on the outputs of the external sensor group 4. The passable area candidate determination unit 12 also identifies the road width of the road currently being traveled on based on the road map data of the map information management device 6 and the detection state of the road area obtained from the external sensor group 4. Note that, in the following description, the oncoming moving object is another vehicle V1, but the moving object that will pass the host vehicle V0 is not limited to a vehicle and may be a motorcycle, bicycle, pedestrian, etc.

[0026] 3A is a top view showing an example of a mutually passable area and a mutually impassable area determined by the passable area candidate determination unit 12. In this example, the host vehicle V0 is attempting to proceed from left to right, and the other vehicle V1 is attempting to proceed from right to left. As shown in the figure, the road width is narrow on the left and right sides in the figure and wide in the center, so the passable area candidate determination unit 12 determines the road in the center as a mutually passable area A and determines the rest as mutually impassable areas.

[0027] 4A is a top view showing another example of a mutually passable area and a mutually impassable area determined by the passable area candidate determination unit 12. In this example, the host vehicle V0 is also attempting to proceed from left to right, and the other vehicle V1 is attempting to proceed from right to left. As shown in the figure, the road width is constant, but the presence of two utility poles divides the large area through which the host vehicle V0 and the other vehicle V1 can pass simultaneously into three parts. Therefore, the passable area candidate determination unit 12 determines the three divided large areas as mutually passable areas A, B, and C, and determines the remaining area as a mutually impassable area.

[0028] <<<<Mobile object movement information detection unit 13>>> The mobile object movement information detection unit 13 detects movement information of a mobile object (other vehicle V1) to be passed, based on the output of the external sensor group 4. The detected movement information of the other vehicle V1 here includes, for example, the current position, movement speed and direction (information related to current movement), turning steering angle, predicted trajectory, etc. of the other vehicle V1. The predicted trajectory here is a future trajectory point sequence predicted based on past movement information of the mobile object, and includes information such as the position and orientation where the mobile object is likely to travel within several seconds. Possible prediction methods include, for example, a linear trajectory point sequence predicted from past trajectory point sequence information, or a nonlinear trajectory point sequence predicted from a mobile object movement model learned by a machine learning (deep learning, etc.) method using a variety of data on passing scenes.

[0029] <<Mutual Passing Pattern Estimation Unit 14>> The mutual passing pattern estimation unit 14 estimates a pattern (hereinafter referred to as a "mutual passing pattern P") for the host vehicle V0 and the other vehicle V1 to cooperatively pass each other. The mutual passing pattern is defined by a plurality of behavior steps S. Note that "mutual passing cooperatively" means that when the host vehicle V0 and the other vehicle V1 pass through a mutual passable area, the mutual passing is performed in a manner that suppresses the occurrence of unnecessary control by both vehicles, such as turning around or backing up.

[0030] 3B is a top view showing an example of a behavior pattern estimated under the circumstances of FIG. 3A. In the behavior step S1 of this behavior pattern P, the host vehicle V0 moves from a target reference position p Ｖ０，Ｓ１ The other vehicle V1 moves to the target reference position p Ｖ１，Ｓ１ In the next action step S2, the host vehicle V0 moves to the target reference position p Ｖ０，Ｓ２ The other vehicle V1 starts traveling via the target reference position p Ｖ１，Ｓ２ By this behavior pattern P, the host vehicle V0 and the other vehicle V1 in FIG. 3A can pass each other cooperatively.

[0031] Fig. 4B is a top view showing an example of a behavior pattern estimated under the circumstances of Fig. 4A. In Fig. 4A, three mutually passable areas are set, but the behavior pattern P in Fig. 4B is a pattern in which passing is selected in the mutually passable area A. In the behavior step S1 of this behavior pattern P, the host vehicle V0 moves to the target reference position p Ｖ０，Ｓ１ The other vehicle V1 moves to the target reference position p Ｖ１，Ｓ１ In the next action step S2, the host vehicle V0 moves to the target reference position p Ｖ０，Ｓ２ The other vehicle V1 starts traveling via the target reference position p Ｖ１，Ｓ２ With this behavior pattern P, the host vehicle V0 and the other vehicle V1 in FIG. 4A can pass each other cooperatively.

[0032] 4C is a top view showing another example of a behavior pattern in the mutual pass situation of FIG. 4A. The behavior pattern P shown here is a pattern in which two vehicles pass each other in the mutual passable area A, just like FIG. 4B, but it has behavior steps S1 to S3. First, in behavior step S1, the vehicle V0 moves to the target reference position p Ｖ０，Ｓ１ The other vehicle V1 moves to the target reference position p Ｖ１，Ｓ１ In the next action step S2, the host vehicle V0 continues to stop. The other vehicle V1 moves to the target reference position p Ｖ１，Ｓ２ In the action step S3, the host vehicle V0 starts traveling via the target reference position p Ｖ０，Ｓ３ With this behavior pattern P, the host vehicle V0 and the other vehicle V1 in FIG. 4A can pass each other cooperatively.

[0033] 3B, 4B, and 4C are examples of simplified representations of the behavior pattern P, and the actual behavior pattern P may be divided into smaller behavior steps.

[0034] <<<<Mobile object behavior agreement level evaluation unit 15>>> The mobile object behavior agreement level evaluation unit 15 compares the movement information of the mobile object (other vehicle V1) with the most recent target reference position, and calculates the agreement level between the behavior of the mobile object (other vehicle V1) and the mutual passing pattern. The method for calculating the agreement level will be described in detail later, but in this embodiment, the agreement level value is assumed to be a value between 0 and 1, and the closer to 1, the higher the agreement level between the two.

[0035] <<<<Mutual Passing Pattern Selection Unit 16>>> When there are multiple mutual passing patterns estimated by the mutual passing pattern estimation unit 14 (see Figures 4B and 4C), the mutual passing pattern selection unit 16 selects the mutual passing pattern with the highest matching level calculated by the mobile object behavior matching level evaluation unit 15 as the highest priority mutual passing pattern (hereinafter referred to as the "passing pattern").

[0036] <<<Autonomous driving / driving assistance information generation unit 17>>> The autonomous driving / driving assistance information generation unit 17 converts information corresponding to the passing pattern selected by the mutual passing pattern selection unit 16 into control information for the actuator group 7 and the HMI device group 8 and transmits it. For example, when autonomous driving is being performed, the autonomous driving / driving assistance information generation unit 17 generates a traveling trajectory corresponding to the next action step of the host vehicle V0 included in the passing pattern, and determines actuator control command values, etc. that control the host vehicle V0 to follow that traveling trajectory. Furthermore, when driving assistance is being performed, the autonomous driving / driving assistance information generation unit 17 notifies the driver of a recommended target position, etc. of the host vehicle V0 via the display of the HMI device group 8.

[0037] <<<<Information Output Unit 18>>> The information output unit 18 outputs various information to other devices connected to the vehicle control device 3 via the in-vehicle network N. For example, the information output unit 18 outputs a control command value included in the autonomous driving travel data group 38 to the actuator group 7 to control the travel of the host vehicle V0.

[0038] Furthermore, for example, the planned trajectory and the like included in the sensor recognition data group 33, the mutual passing pattern data group 35, and the driving assistance data group 37, which will be described later, are output to the HMI device group 8 and presented to the occupant of the host vehicle V0. This allows the occupant of the host vehicle V0, during autonomous driving, to be presented with how the vehicle system 1 interprets the surrounding driving environment (display of the sensor recognition data group 33) and what kind of driving is planned (display of the mutual passing pattern data group 35 and the driving assistance data group 37).

[0039] <<Storage Unit 30>> The storage unit 30 is configured to include, for example, storage devices such as a hard disk drive (HDD), flash memory, or read-only memory (ROM), and memories such as a random access memory (RAM). The storage unit 30 stores programs processed by the processing unit 10, data sets 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, temporarily storing data required for the program's calculations.

[0040] In this embodiment, the information for realizing the functions of the vehicle control device 3 includes a vehicle information data group 31, a road environment data group 32, a sensor recognition data group 33, a region candidate data group 34, a mutual passing pattern data group 35, a behavior agreement level data group 36, a driving assistance data group 37, and an autonomous driving travel data group 38, which are stored in the storage unit 30. Each data group will be described in detail below.

[0041] <<<Vehicle Information Data Group 31>>> The vehicle information data group 31 is a collection of data relating to the behavior of the host vehicle V0 detected by the vehicle sensor group 5, etc. The data relating to the behavior of the host vehicle V0 is information that represents the movement, state, etc. of the host vehicle V0, and includes, for example, information such as the position of the host vehicle V0, the traveling speed, the steering angle, the amount of accelerator operation, the amount of brake operation, and the traveling route.

[0042] <<<Road Environment Data Group 32>>> The road environment data group 32 is a collection of data related to the road environment around the host vehicle V0. Data related to the road environment is information related to the roads around the host vehicle V0, including the road on which the host vehicle V0 is traveling. This includes, for example, information related to the shape and attributes (direction of travel, speed limit, driving regulations, etc.) of the lanes that make up the roads around the host vehicle V0, traffic light information, traffic information related to the traffic conditions (average speed, etc.) of each road and lane, statistical knowledge information based on past cases, etc. Static information such as the shape and attributes of roads and lanes is included in map information acquired from, for example, the map information management device 6.

[0043] <<<<Sensor Recognition Data Group 33>>> The sensor recognition data group 33 is a collection of data related to detection information or detection states by the external sensor group 4. The detection information is, for example, information related to environmental elements such as obstacles, road markings, signs, and traffic lights around the host vehicle V0 that are identified by the external sensor group 4 based on the sensing information, or the sensing information itself around the host vehicle V0 by the external sensor group 4 (point cloud information from LiDAR or RADAR, camera images, parallax images from stereo cameras, etc.). The detection state is information indicating the area detected by the sensor and its accuracy, and includes, for example, a grid map such as an OGM.

[0044] <<<Area candidate data group 34>>> The area candidate data group 34 is a collection of mutually passable areas determined by the passable area candidate determination unit 12. In the example of Fig. 3A , only the mutually passable area A is in the area candidate data group 34, and in the example of Fig. 4A , the mutually passable areas A, B, and C are in the area candidate data group 34.

[0045] <<<Mutual Passing Pattern Data Group 35>>> The mutual passing pattern data group 35 is a data group that aggregates the mutual passing patterns estimated by the mutual passing pattern estimation unit 14. Fig. 5 shows an example of the mutual passing pattern data group 35. The mutual passing pattern data group 35 illustrated here has a data sequence 35a indicating an overall action sequence (serial number), a data sequence 35b indicating a vehicle ID, a data sequence 35c indicating an action step corresponding to the vehicle ID, a data sequence 35d indicating a target reference position for each action step, a data sequence 35e indicating an action step end condition, and a data sequence 35f indicating a target passable area A.

[0046] <<<<Behavior Consistency Level Data Group 36>>> The behavior consistency level data group 36 is a data group that compiles the behavior consistency levels for each mutual passage pattern candidate calculated by the mobile object behavior consistency level evaluation unit 15, and has a data structure as shown in the example of Figure 6.

[0047] <<<<Driving assistance data group 37>>> The driving assistance data group 37 is a data group determined by the automatic driving / driving assistance information generation unit 17 and used to follow the driving trajectory for the action step currently being executed in the driving behavior plan of the vehicle V0, and includes control command values, etc. to be output to the HMI device group 8 of the vehicle V0.

[0048] <<<Autonomous driving driving data group 38>>> The autonomous driving driving data group 38 is a data group determined by the autonomous driving / driving assistance information generation unit 17 and used to follow the driving trajectory for the action step currently being executed in the driving behavior plan of the host vehicle V0, and includes control command values ​​to be output to the actuator group 7 of the host vehicle V0, etc.

[0049] <<Communication Unit 40>> The communication unit 40 has a function of communicating with other devices connected via the in-vehicle network N. The communication function of the communication unit 40 is used when the information acquisition unit 11 acquires various pieces of information from other devices via the in-vehicle network N or when the information output unit 18 outputs various pieces of information to other devices via the in-vehicle network N.

[0050] The communication unit 40 includes a network card conforming to a communication standard such as IEEE 802.3 or CAN (Controller Area Network), etc. The communication unit 40 transmits and receives data between the vehicle control device 3 and other devices in the vehicle system 1 based on various protocols.

[0051] 1, the communication unit 40 and the processing unit 10 are shown separately, but part of the processing of the communication unit 40 may be executed within the processing unit 10. For example, a configuration may be adopted in which the equivalent of a hardware device in the communication processing exists in the communication unit 40, and other device drivers, communication protocol processing, etc. exist within the processing unit 10.

[0052] <Flowchart> Next, a method for calculating the behavior agreement level performed by the mobile object behavior agreement level evaluation unit 15 of the vehicle control device 3 will be described with reference to FIGS.

[0053] First, in step St1 of the flowchart in Fig. 7, the mobile object behavior agreement level evaluation unit 15 acquires mutual passing pattern candidates estimated by the mutual passing pattern estimation unit 14. In the following, it is assumed that the mutual passing patterns in Fig. 4B and Fig. 4C are acquired as mutual passing pattern candidates.

[0054] Next, in step St2, the mobile object behavior agreement level evaluation unit 15 determines the target reference position p Ｖ１，Ｓ１ Get.

[0055] In step St3, the mobile object behavior agreement level evaluation unit 15 acquires movement information (current position, movement speed, movement direction, turning steering angle, predicted trajectory, etc.) of the oncoming vehicle (other vehicle V1) from the mobile object movement information detection unit 13.

[0056] In step St11, the mobile object behavior agreement level evaluation unit 15 calculates the distance between the current position of the oncoming vehicle (other vehicle V1) acquired in step St3 and each of the target reference positions p Ｖ１，Ｓ１ Calculate the distance to

[0057] In step St12, the mobile object behavior agreement level evaluation unit 15 calculates whether the oncoming vehicle (other vehicle V1) is moving from the current position to each of the target reference positions p Ｖ１，Ｓ１ The estimated speed at which the vehicle will travel to the destination is calculated. The estimated speed calculated here is roughly proportional to the distance calculated in step St11.

[0058] In step St13, the mobile object behavior agreement level evaluation unit 15 determines whether the estimated speed calculated in step St12 is 0. If the requirement is met, the process proceeds to step St14, and if the requirement is not met, the process proceeds to step St15.

[0059] In step St14, the mobile object behavior matching level evaluation unit 15 calculates the matching level using the calculation formula shown in the figure. In this calculation formula, "distance" is the distance calculated in step St11, "maximum distance" is a parameter set in advance in accordance with the system, and "direction factor" is the distance between the target reference position p Ｖ１，Ｓ１ is a coefficient that is determined depending on whether the vehicle is in front of or behind the other vehicle V1. Therefore, the match level calculated in this step decreases as the distance approaches the maximum distance. Although not shown in Figure 7, if the distance is greater than the maximum distance, the match level is set to 0.

[0060] The direction factor is the target reference position p Ｖ１，Ｓ１ is, for example, 1 when the target reference position p is in front of the other vehicle V1, and is, for example, 0.8 when the target reference position p is behind the other vehicle V1. Ｖ１，Ｓ１ If the vehicle V1 is in front of the other vehicle V1, the matching level will be higher than if the vehicle V1 is behind the other vehicle V1.

[0061] In step St15, the mobile object behavior agreement level evaluation unit 15 calculates the target reference position p Ｖ１，Ｓ１is ahead of the oncoming vehicle (other vehicle V1) and the velocity vector of the oncoming vehicle (other vehicle V1) is directed forward. If the requirements are met, the process proceeds to step St16, and if the requirements are not met, the process proceeds to step St17.

[0062] In step St16, the mobile object behavior agreement level evaluation unit 15 calculates the agreement level using the calculation formula shown in the figure. In this calculation formula, the "oncoming vehicle speed" is the moving speed of the oncoming vehicle (other vehicle V1) acquired in step St3, and the "estimated speed" is the estimated speed of the oncoming vehicle (other vehicle V1) calculated in step St12. Therefore, the closer the actual measured value of the moving speed of the oncoming vehicle (other vehicle V1) is to the estimated speed, the higher the agreement level.

[0063] In step St17, the mobile object behavior agreement level evaluation unit 15 calculates the target reference position p Ｖ１，Ｓ１ is behind the oncoming vehicle (other vehicle V1) and the velocity vector of the oncoming vehicle (other vehicle V1) is pointing backward. If the requirements are met, the process proceeds to step St16, and if the requirements are not met, the process ends.

[0064] In step St18, the mobile object behavior matching level evaluation unit 15 evaluates the matching level as 0. Note that the reason for reaching this step is that the oncoming vehicle (other vehicle V1) is approaching the target reference position p Ｖ１，Ｓ１ is when it is moving in the opposite direction.

[0065] Through the above processing, the vehicle control device 3 can calculate the behavior matching level with each of the multiple mutual passing pattern candidates based on the estimated speed of the oncoming vehicle (other vehicle V1).

[0066] 8 shows an example of the match level calculated according to the flowchart of FIG. 7. In this figure, the target reference position p1 is the target reference position p Ｖ１，Ｓ１ The target reference position p2 corresponds to the target reference position p Ｖ１，Ｓ１As is clear from the figure, the distance from the current position of the other vehicle V1 to the target reference position p1 is relatively long, and the distance to the target reference position p2 is relatively short. Therefore, in step St12, the estimated speed when the other vehicle V1 moves to the target reference position p1 and stops is calculated to be higher than the estimated speed when the other vehicle V1 moves to the target reference position p2 and stops. Therefore, if the current velocity vector of the other vehicle V1 is large, a relatively large match level (e.g., 0.8) is calculated for a mutual pass pattern including the distant target reference position p1, and a relatively small match level (e.g., 0.2) is calculated for a mutual pass pattern including the nearby target reference position p2.

[0067] Therefore, when the mobile object behavior matching level evaluation unit 15 calculates a matching level such as that shown in Figure 8 based on the observed speed of the other vehicle V1, it can be predicted that the other vehicle V1 will take the behavioral steps of Figure 4B, so the mutual passing pattern selection unit 16 selects the mutual passing pattern of Figure 4B, and the automatic driving / driving assistance information generation unit 17 generates various information to realize the mutual passing pattern of Figure 4B.

[0068] According to the vehicle control device of the present embodiment described above, it is possible to sequentially update information required for cooperative mutual passage through a narrow road, taking into account the actual speed of an oncoming vehicle. By enabling the host vehicle V0 and the other vehicle V1 to cooperatively pass each other, it is possible to shorten the time required for the host vehicle V0 and the other vehicle V1 to pass each other in a mutual passable area, thereby realizing smooth traffic. When the vehicle control device 3 is used for automatic driving of the host vehicle V0, it is possible to improve the ride comfort of the occupants of the host vehicle V0. Furthermore, when the vehicle control device 3 is used for driving assistance of the host vehicle V0, it is possible to improve the ride comfort of the occupants of the host vehicle V0 and also improve the operability of the driver of the host vehicle V0.

[0069] Next, a second embodiment of the present invention will be described with reference to Figures 9 and 10. In the first embodiment, the behavior matching level with each mutual passing pattern is evaluated based on the speed of the moving object, but in this embodiment, the behavior matching level with each mutual passing pattern is evaluated based on the trajectory of the moving object. Note that, below, a duplicated description of points common to the first embodiment will be omitted.

[0070] 9 is a flowchart of the mobile object behavior agreement level evaluation in this embodiment. Steps S1 to S3 in the figure are the same as those in FIG. 7 in the first embodiment, so a description thereof will be omitted.

[0071] In step St21, the mobile object behavior agreement level evaluation unit 15 calculates the distance between the current position of the oncoming vehicle (other vehicle V1) acquired in step St3 and each of the target reference positions p Ｖ１，Ｓ１ A smooth route to the target reference position p is estimated. Various methods can be used for route estimation in this step. For example, Ｖ１，Ｓ１ Alternatively, if an obstacle exists on the route estimated in this way, the route may be modified to avoid the obstacle.

[0072] In step St22, the mobile object behavior matching level evaluation unit 15 calculates the root mean square error (hereinafter referred to as "RMSE") between the predicted trajectory obtained in step St3 and the estimated route obtained in step St21 for each target reference position.

[0073] In step St23, the mobile object behavior agreement level evaluation unit 15 determines whether the RMSE calculated in step St22 is equal to or greater than a predetermined RMSE threshold. If the requirement is met, the process proceeds to step St24. If the requirement is not met, the process proceeds to step St25. The RMSE threshold is a parameter (e.g., 0.5) that is preset in accordance with the system.

[0074] In step St24, the mobile object behavior matching level evaluation unit 15 evaluates the matching level as 0.

[0075] In step St25, the mobile object behavior agreement level evaluation unit 15 calculates the agreement level using the calculation formula shown in the figure.

[0076] Through the above processing, the vehicle control device 3 can calculate the behavior matching level with each of the multiple mutual passing pattern candidates based on the estimated trajectory of the oncoming vehicle (other vehicle V1).

[0077] 10 shows an example of the match level calculated according to the flowchart of FIG. 9. The target reference position p1 in the upper diagram is the same as the target reference position p in FIG. 4B. Ｖ１，Ｓ１ The target reference position p2 corresponds to the target reference position p Ｖ１，Ｓ１ When the other vehicle V1 moves from its current position to the target reference position p1, a route that goes straight and then turns left is estimated, whereas when the other vehicle V1 moves to the target reference position p2, a route that makes a quick right turn is estimated. In contrast, the predicted trajectory of the other vehicle V1 acquired in step St3 goes straight and then turns left, so as shown in the diagram below, a relatively large matching level (e.g., 0.8) is calculated for mutual passing patterns that include the distant target reference position p1, and a relatively small matching level (e.g., 0.1) is calculated for mutual passing patterns that include the nearby target reference position p2.

[0078] Therefore, when the mobile object behavior matching level evaluation unit 15 calculates a matching level such as that shown in Figure 10, it can be predicted that the other vehicle V1 will take the behavioral steps of Figure 4B, so the mutual passing pattern selection unit 16 selects the mutual passing pattern of Figure 4B, and the automatic driving / driving assistance information generation unit 17 generates various information to realize the mutual passing pattern of Figure 4B.

[0079] According to the vehicle control device of the present embodiment described above, it is possible to successively update information required for cooperative mutual passage through a narrow road, taking into account the actual trajectory of an oncoming vehicle.

[0080] Next, a third embodiment of the present invention will be described with reference to Figures 11 and 12. In the first embodiment, the behavioral matching level with each mutual passing pattern is evaluated based on the speed of the moving object, and in the second embodiment, the behavioral matching level with each mutual passing pattern is evaluated based on the trajectory of the moving object. In the present embodiment, however, the behavioral matching level with each mutual passing pattern is evaluated based on the steering angle of the moving object. Note that, in the following, a duplicated description of points common to the first and second embodiments will be omitted.

[0081] 11 is a flowchart of the mobile object behavior agreement level evaluation in this embodiment. Steps S1 to S3 in the figure are the same as those in FIG. 7 in the first embodiment, so a description thereof will be omitted.

[0082] Step St31 is to determine the target reference position p Ｖ１，Ｓ１ This is a process of estimating a smooth path to the target point, and is equivalent to step St21 in the second embodiment.

[0083] In step St32, the mobile object behavior agreement level evaluation unit 15 calculates the target reference position p Ｖ１，Ｓ１ Based on the route to each target reference position p Ｖ１，Ｓ１ The steering angle α required for turning when traveling in the direction indicated by the arrow is calculated.

[0084] In step St33, the mobile object behavior agreement level evaluation unit 15 determines whether the steering angle α calculated in step St32 is greater than the maximum steering angle of the oncoming vehicle (the steering angle at which the vehicle can make the sharpest turn within the specifications). If the requirement is met, the process proceeds to step St34, and if the requirement is not met, the process proceeds to step St35. Note that satisfying the requirement in this step means that the oncoming vehicle (other vehicle V1) is located at the target reference position p Ｖ１，Ｓ１ This means that you must make at least one turn when driving towards the other side.

[0085] In step St34, the mobile object behavior matching level evaluation unit 15 evaluates the matching level as 0.

[0086] In step St35, the mobile object behavior agreement level evaluation unit 15 calculates the agreement level using the calculation formula shown in the figure.

[0087] Through the above processing, the vehicle control device 3 can calculate the behavior matching level with each of the multiple mutual passing pattern candidates based on the estimated steering angle of the oncoming vehicle (other vehicle V1).

[0088] 12 shows an example of the matching level calculated according to the flowchart of FIG. 11. When the other vehicle V1 moves from its current position to the target reference position p3, a route that travels substantially straight is estimated, whereas when the other vehicle V1 moves from its current position to the target reference position p4, a route that makes a large left turn is estimated. Therefore, the matching level with a mutual passing pattern in which the other vehicle V1 travels substantially straight to the target reference position p3 is calculated to be a relatively large 0.9, and the matching level with a mutual passing pattern in which the other vehicle V1 travels to the target reference position p4 by making a large left turn is calculated to be a relatively small 0.1.

[0089] Therefore, when the mobile object behavior matching level evaluation unit 15 calculates a matching level such as that shown in Figure 12, it can be predicted that the other vehicle V1 will take behavior steps toward the target reference position p3, so the mutual passing pattern selection unit 16 selects a mutual passing pattern that includes behavior steps toward the target reference position p3, and the automatic driving / driving assistance information generation unit 17 generates various information to realize the selected mutual passing pattern.

[0090] According to the vehicle control device of the present embodiment described above, it is possible to successively update information required for cooperative mutual passage through a narrow road, taking into account the steering angle of an oncoming vehicle.

[0091] In the above embodiments, the matching level was calculated using a different method for each embodiment, but the matching level calculation methods of each embodiment may be combined, and the mutual passing pattern to be selected may be determined based on the sum or average value of the matching levels calculated using different methods.

[0092] Next, a vehicle control device 3 according to a fourth embodiment of the present invention will be described. Note that overlapping explanations of points common to the above-described embodiments will be omitted. In the above-described embodiment, it was assumed that the driver would follow the reciprocal passing pattern proposed by the vehicle control device 3 via the HMI device group 8 during driving assistance. However, in reality, the driver may not follow the proposed reciprocal passing pattern. Therefore, the vehicle control device 3 of this embodiment is configured to propose an alternative reciprocal passing pattern if the driver does not or cannot follow the initially proposed reciprocal passing pattern.

[0093] One example of a situation in which the driver does not follow the proposed reciprocal passing pattern is when the driver has low driving skill and finds it difficult to execute the initially proposed reciprocal passing pattern. Therefore, the vehicle control device 3 of this embodiment is configured to propose a simpler alternative reciprocal passing pattern if the proposed reciprocal passing pattern is not executed for a predetermined time (e.g., 10 seconds).

[0094] Another example of a situation in which the driver does not follow the proposed mutual passing pattern is when the driver has low driving skills and is therefore unable to implement a mutual passing pattern that includes backing up the host vehicle V0. Therefore, the vehicle control device 3 of this embodiment is configured to propose from the beginning a second-best mutual passing pattern that does not include backing up if the initially selected mutual passing pattern includes backing up.

[0095] According to the present embodiment described above, it is possible to propose a mutual passing pattern that can be implemented even by a driver with low driving skills.

[0096] REFERENCE SIGNS LIST 1 Vehicle system 2 Vehicle 3 Vehicle control device 10 Processing unit 11 Information acquisition unit 12 Passable area candidate determination unit 13 Mobile object movement information detection unit 14 Mutual passage pattern estimation unit 15 Mobile object behavior agreement level evaluation unit 16 Mutual passage pattern selection unit 17 Autonomous driving / driving assistance information generation unit 18 Information output unit 30 Memory unit 31 Vehicle information data group 32 Road environment data group 33 Sensor recognition data group 34 Area candidate data group 35 Mutual passage pattern data group 36 Behavior agreement level data group 37 Driving assistance data group 38 Autonomous driving travel data group 40 Communication unit 4 External sensor group 5 Vehicle sensor group 6 Map information management device 7 Actuator group 8 HMI device group 9 External communication device N In-vehicle network V0 Host vehicle V1 Other vehicle

Claims

1. A vehicle control device comprising: a passable area candidate determination unit that determines one or more mutual passable areas in which the host vehicle and a moving body can pass each other on a road that has a mutual impassable area in which the host vehicle and a moving body cannot pass each other; a moving body movement information detection unit that detects movement information of the moving body; a mutual pass pattern estimation unit that estimates at least one mutual pass pattern which is a combination of action steps of the host vehicle and the moving body for the host vehicle and the moving body to pass each other on the road; a moving body behavior agreement level evaluation unit that evaluates a level of agreement between a predicted behavior of the moving body based on the movement information and the action steps of the moving body when the host vehicle and the moving body pass each other in the mutual passable area; a mutual pass pattern selection unit that selects at least one mutual pass pattern based on the agreement level; and an automatic driving / driving assistance information generation unit that generates information to be used for automatic driving and / or driving assistance of the host vehicle for the host vehicle and the moving body to pass each other in the selected mutual pass pattern.

2. A vehicle control device as described in claim 1, wherein the movement information includes information regarding the speed of the moving body, the action step includes information regarding a target position of the moving body, and the moving body action matching level evaluation unit evaluates the matching level between the predicted action of the moving body and the action step based on the distance and approach speed to the target position of the action step of the moving body in the mutual passing pattern.

3. A vehicle control device as described in claim 1, wherein the movement information includes information regarding the past trajectory point sequence of the moving body, the action step includes information regarding a target position of the moving body, the moving body movement information detection unit predicts a future trajectory point sequence of the moving body based on the past trajectory point sequence of the moving body, and the moving body behavior matching level evaluation unit estimates a route that the moving body will take when traveling toward a target position of the action step of the moving body in the mutual passing pattern, and evaluates the matching level based on the magnitude of position error between the estimated route and the future trajectory point sequence.

4. A vehicle control device as described in claim 1, wherein the action step includes information regarding a target position of the moving body, and the moving body action matching level evaluation unit estimates a route that the moving body will take when traveling toward the target position of the action step of the moving body in the mutual passing pattern, and evaluates the matching level based on the magnitude of the steering angle required to travel the estimated route.

5. A vehicle control device as described in claim 1, characterized in that the automatic driving / driving assistance information generation unit presents the mutual passing pattern selected by the mutual passing pattern selection unit to the driver via an HMI device.

6. A vehicle control device as claimed in claim 5, characterized in that the mutual passing pattern selection unit selects another mutual passing pattern when the driver does not follow the mutual passing pattern presented via the HMI device.

7. A vehicle control device according to claim 5, characterized in that the mutual passing pattern selection section selects another mutual passing pattern when the initially selected mutual passing pattern includes a backward action step.

8. A vehicle control method executed by a vehicle control device, comprising: a passable area candidate determination step for determining one or more mutual passable areas in which the host vehicle and a moving body can pass each other on a road that has a mutually impassable area in which the host vehicle and a moving body cannot pass each other; a moving body movement information detection step for detecting movement information of the moving body; a mutual pass pattern estimation step for estimating at least one mutual pass pattern which is a combination of the movement steps of the host vehicle and the moving body for passing the road between the host vehicle and the moving body; a moving body behavior agreement level evaluation step for evaluating a level of agreement between a predicted behavior of the moving body predicted based on the movement information and the movement steps of the moving body when the host vehicle and the moving body pass each other in the mutual passable area; a mutual pass pattern selection step for selecting at least one mutual pass pattern based on the agreement level; and an automatic driving / driving assistance information generation step for generating information to be used for automatic driving and / or driving assistance of the host vehicle for the host vehicle and the moving body to pass each other in the selected mutual pass pattern.

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