Technical Field
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The present invention relates to a vehicle control device and a vehicle control method suitable for driving assistance or automatic driving.
Background Art
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In recent years, in order to realize comfortable and safe driving assistance and automatic driving of vehicles, technology for realizing cooperative traveling in narrow road environments has been desired. In particular, when an oncoming vehicle is encountered on a narrow road, a driving assistance system has been proposed that performs mutual passing traveling cooperatively with the oncoming vehicle while utilizing spaces where withdrawal is possible and the like.
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For example, in the abstract of PTL 1, it is described as a problem to "provide a driving assistance system capable of performing mutual passage safely and smoothly," and as a means for solving the problem, "in an in-vehicle control device 50, driving skill related to passing operation of a driver is evaluated based on a driver's driving history, and based on vehicle body information of the vehicle and road conditions evaluated in a center control device 10, at least one passing position and a degree of easiness of passing at the passing position are calculated on a road where the vehicle performs mutual passage. In the center control device 10, road conditions necessary for mutual passage are evaluated based on road information of the road where the vehicle performs mutual passage, and based on the driving skill of the driver evaluated by the in-vehicle control device 50 and at least one passing position calculated by the passing easiness degree calculation processing and the degree of easiness of passing at the passing position, the easiest passing position and passing method are determined, and the determined passing position and passing method are notified to the driver by notification means 70."
Citation List
Patent Literature
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Summary of Invention
Technical Problem
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However, when passing an oncoming vehicle on a narrow road, there may be cases where oncoming vehicle behavior unexpected for the driving assistance system occurs. For example, even though the easiest passing position and passing method determined by the driving assistance system based on the driving skill of the driver was a scenario in which the host vehicle waits in a retreat space on the left side of the narrow road and the oncoming vehicle passes through the narrow road during that time, the actual oncoming vehicle may wait in a retreat space on the right side of the narrow road and urge prioritized passage of the host vehicle.
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Even in such a case, since the driving assistance system of PTL 1 does not update the information to be notified to the driver (the easiest passing position and passing method), the driver had to judge by himself/herself the easiest passing position and passing method under the current environment while also considering his/her own driving skill.
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Therefore, an object of the present invention is to provide a vehicle control device and a vehicle control method capable of sequentially updating information necessary for coordinated mutual passage on a narrow road based on actual behavior of surrounding moving bodies.
Solution to Problem
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In order to solve the above problem, a vehicle control device of the present embodiment is a vehicle control device including: a passable region candidate determination unit that determines one or more mutually passable regions where the host vehicle and the moving body can mutually pass, on a road where a mutually impassable region exists in which mutual passage between the host vehicle and the moving body is impossible; a moving body movement information detection unit that detects movement information of the moving body; a mutual passage pattern estimation unit that estimates at least one or more mutual passage patterns, which is a combination of action steps of each of the host vehicle and the moving body, for the host vehicle and the moving body to pass through the road; a moving body action matching level evaluation unit that evaluates a matching level of predicted behavior of the moving body predicted based on the movement information and an action step of the moving body when the host vehicle and the moving body mutually pass in the mutually passable region; a mutual passage pattern selection unit that selects at least one mutual passage pattern based on the matching 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 mutually pass in the selected mutual passage pattern.
Advantageous Effects of Invention
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According to the vehicle control device and the vehicle control method of the present invention, it is possible to sequentially update information necessary for coordinated mutual passage on a narrow road based on actual behavior of surrounding moving bodies.
Brief Description of Drawings
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- [FIG. 1] FIG. 1 is a functional block diagram of a vehicle system of a first embodiment.
- [FIG. 2] FIG. 2 is a functional block diagram explaining functions of a processing unit of the vehicle control device of the first embodiment.
- [FIG. 3A] FIG. 3A is a top view showing an example of a mutual passage situation.
- [FIG. 3B] FIG. 3B is a top view showing an example of a mutual passage pattern estimated in the mutual passage situation of FIG. 3A.
- [FIG. 4A] FIG. 4A is a top view showing another example of a mutual passage situation.
- [FIG. 4B] FIG. 4B is a top view showing an example of a mutual passage pattern estimated in the mutual passage situation of FIG. 4A.
- [FIG. 4C] FIG. 4C is a top view showing another example of a mutual passage pattern estimated in the mutual passage situation of FIG. 4A.
- [FIG. 5] FIG. 5 is an example of a mutual passage pattern data group.
- [FIG. 6] FIG. 6 is an example of an action matching level data group.
- [FIG. 7] FIG. 7 is a flowchart of moving body action matching level evaluation by the vehicle control device of the first embodiment.
- [FIG. 8] FIG. 8 is an example of a moving body action matching level calculated by the vehicle control device of the first embodiment.
- [FIG. 9] FIG. 9 is a flowchart of moving body action matching level evaluation by the vehicle control device of a second embodiment.
- [FIG. 10] FIG. 10 is an example of a moving body action matching level calculated by the vehicle control device of the second embodiment.
- [FIG. 11] FIG. 11 is a flowchart of moving body action matching level evaluation by the vehicle control device of a third embodiment.
- [FIG. 12] FIG. 12 is an example of a moving body action matching level calculated by the vehicle control device of the third embodiment.
Description of Embodiments
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Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings, but 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 in the scope thereof.
First Embodiment
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First, a vehicle control device according to the first embodiment of the present invention will be described using FIGS. 1 to 8.
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FIG. 1 is a functional block diagram showing a configuration of a vehicle system 1 including the vehicle control device 3 of the present embodiment. This vehicle system 1 is mounted on a vehicle 2 (which may be described as "host vehicle VO" to distinguish from other vehicles), and has a function of performing appropriate driving assistance and traveling control after confirming the situation of obstacles such as traveling roads and surrounding vehicles in the periphery of the vehicle 2. In order to realize this function, the vehicle system 1 has a vehicle control device 3, an external world 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, and these are connected by an in-vehicle network N. Below, after sequentially explaining the outlines from the external world sensor group 4 to the external communication device 9, the vehicle control device 3 of the present embodiment will be described in detail.
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The external world sensor group 4 is an aggregate of devices that detect the state around the host vehicle V0. The external world sensor group 4 corresponds to, for example, a camera device, millimeter wave radar, LiDAR, sonar, and the like. The external world sensor group 4 detects environmental elements such as manifest obstacles, road markings, signs, and signals within a predetermined range from the host vehicle V0, and these detection results are output to the vehicle control device 3 via the in-vehicle network N. "Manifest obstacles" are, for example, other vehicles that are vehicles other than the host vehicle V0, pedestrians, fallen objects on the road, road edges, and the like. "Road markings" are, for example, white lines, crosswalks, stop lines, and the like. Further, the external world sensor group 4 also outputs information regarding the detection state to the vehicle control device 3 via the in-vehicle network N based on its own sensing range and the state thereof.
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The vehicle sensor group 5 is an aggregate of devices that detect various states of the host vehicle V0. Each vehicle sensor detects, for example, position information, traveling speed, steering angle, accelerator operation amount, brake operation amount, and the like of the vehicle 2, and outputs them to the vehicle control device 3 via the in-vehicle network N.
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The map information management device 6 is a device that manages and provides digital map information around the host vehicle V0. The map information management device 6 is configured by, for example, a navigation device or the like. The map information management device 6 includes, for example, digital road map data of a predetermined area including the periphery of the host vehicle V0, and is configured to specify the current position of the host vehicle V0 on the map, that is, the road or lane on which the host vehicle V0 is traveling, based on position information and the like of the host vehicle V0 output from the vehicle sensor group 5. Further, it outputs the specified current position of the host vehicle V0 and map data of the periphery thereof to the vehicle control device 3 via the in-vehicle network N.
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The actuator group 7 is a device group that controls control elements such as steering, brake, and accelerator that determine the movement of the host vehicle V0. The actuator group 7 controls the movement of control elements such as steering, brake, and accelerator based on operation information of a handle, brake pedal, accelerator pedal, and the like by the driver and control command values output from the vehicle control device 3, thereby controlling the behavior of the host vehicle V0 and executing automatic driving.
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The HMI device group 8 is a device group for inputting information to the vehicle system 1 from the driver or occupants and for notifying information from the vehicle system 1 to the driver or occupants. The HMI device group 8 includes a display, speaker, vibrator, switch, and the like.
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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.
<Vehicle Control Device 3>
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The vehicle control device 3 is an ECU (Electronic Control Unit) mounted on the vehicle 2. As shown in FIG. 2, this vehicle control device 3 generates traveling control information for driving assistance or automatic driving of the vehicle 2 based on various input information provided from the external world sensor group 4, the vehicle sensor group 5, the map information management device 6, or the external communication device 9 whose illustration is omitted, and outputs it to the actuator group 7, the HMI device group 8, and the external communication device 9. This vehicle control device 3 has a processing unit 10, a storage unit 30, and a communication unit 40. Hereinafter, details of each unit will be explained sequentially.
<<Processing Unit 10>>
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The processing unit 10 is configured to include, for example, a CPU (Central Processing Unit) which is a central processing unit. However, in addition to the CPU, it may be configured to include a GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), ASIC (Application Specific Integrated Circuit), and the like, or may be configured by any one of them.
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The processing unit 10 has, as control functions, an information acquisition unit 11, a passable region candidate determination unit 12, a moving body movement information detection unit 13, a mutual passage pattern estimation unit 14, a moving body action matching level evaluation unit 15, a mutual passage pattern selection unit 16, an automatic driving/driving assistance information generation unit 17, and an information output unit 18. The CPU and the like constituting the processing unit 10 realize these control functions by executing a predetermined control program stored in the storage unit 30.
<<<Information Acquisition Unit 11>>>
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The information acquisition unit 11 acquires various information from other devices connected to the vehicle control device 3 via the in-vehicle network N and stores them in the storage unit 30. For example, it acquires information related to behavior such as movement and state of the vehicle 2 detected by the vehicle sensor group 5 and the like, and stores them in the storage unit 30 as a vehicle information data group 31. Further, it acquires information related to the road environment in which the vehicle 2 travels from the map information management device 6, the external communication device 9, and the like, and stores them in the storage unit 30 as a road environment data group 32. Further, it acquires information regarding obstacles around the vehicle 2 detected by the external world sensor group 4 and a detection region of the external world sensor group 4, and stores them in the storage unit 30 as a sensor recognition data group 33.
<<<Passable Region Candidate Determination Unit 12>>>
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The passable region candidate determination unit 12, after specifying a moving body facing the host vehicle V0, determines a wide region where the host vehicle V0 and the oncoming moving body can mutually pass without difficulty (hereinafter referred to as "mutually passable region") and a narrow region where mutual passage between both is impossible or difficult (hereinafter referred to as "mutually impassable region") by considering road width, host vehicle width, moving body width, presence or absence of obstacles, and the like.
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Here, the passable region candidate determination unit 12 specifies the moving body that passes the host vehicle V0, the moving body width, presence or absence of obstacles, and the like based on the output of the external world sensor group 4. Further, the passable region candidate determination unit 12 specifies the road width of the currently traveling road based on the road map data of the map information management device 6, the detection state of the road region obtained from the external world sensor group 4, and the like. Note that, in the following, description will be made assuming that the oncoming moving body is another vehicle V1, but the moving body that passes the host vehicle V0 is not limited to a vehicle, and may be a motorcycle, bicycle, pedestrian, or the like.
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FIG. 3A is a top view showing an example of the mutually passable region and the mutually impassable region determined by the passable region candidate determination unit 12. In this example, the host vehicle V0 is trying to proceed from the left side to the right side, and the other vehicle V1 is trying to proceed from the right side to the left side. As illustrated, since the road width is narrow on the left side and the right side in the figure and wide at the center, the passable region candidate determination unit 12 determines the central part of the road as the mutually passable region A and determines the others as mutually impassable regions.
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Further, FIG. 4A is a top view showing another example of the mutually passable region and the mutually impassable region determined by the passable region candidate determination unit 12. Also in this example, the host vehicle V0 is trying to proceed from the left side to the right side, and the other vehicle V1 is trying to proceed from the right side to the left side. As illustrated, the road width is constant, but the wide region where the host vehicle V0 and the other vehicle V1 can pass simultaneously is divided into three parts due to the existence of two utility poles. Therefore, the passable region candidate determination unit 12 determines the three divided wide regions as mutually passable regions A, B, and C, and determines the remaining regions as mutually impassable regions.
<<<Moving Body Movement Information Detection Unit 13>>>
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The moving body movement information detection unit 13 detects movement information of the moving body (other vehicle V1) that is a passing target based on the output of the external world sensor group 4. The movement information of the other vehicle V1 detected here is, for example, the current position of the other vehicle V1, movement speed and direction (information related to current movement), turning steering angle, predicted trajectory, and the like. The predicted trajectory here is a future trajectory point sequence predicted based on past movement information of the moving body, and includes information such as positions and orientations where the moving body is likely to travel within several seconds. As for the prediction method, for example, a linear trajectory point sequence predicted from past trajectory point sequence information, a non-linear trajectory point sequence predicted from a movement model of a moving body learned using diverse data of passing scenes by machine learning (deep learning, etc.) methods, and the like can be considered.
<<Mutual Passage Pattern Estimation Unit 14>>
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The mutual passage pattern estimation unit 14 estimates a pattern for the host vehicle V0 and the other vehicle V1 to perform mutual passage cooperatively (hereinafter referred to as "mutual passage pattern P"). The mutual passage pattern is defined by a plurality of action steps S. Note that "performing mutual passage cooperatively" means that, when the host vehicle V0 and the other vehicle V1 pass through the mutually passable region, both vehicles perform mutual passage so as to suppress occurrence of extra controls such as switchback maneuver and backward traveling.
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FIG. 3B is a top view showing an example of an action pattern estimated under the situation of FIG. 3A. In action step S1 of this action pattern P, the host vehicle V0 moves to a target reference position pV0,S1 in front of the mutually passable region A and stops. Further, the other vehicle V1 moves to a target reference position pV1,S1 within the mutually passable region A and stops. In the next action step S2, the host vehicle V0 starts traveling via a target reference position pV0,S2 beyond the mutually passable region A. Further, the other vehicle V1 starts traveling via a target reference position pV1,S2 beyond the mutually passable region A. By such an action pattern P, the host vehicle V0 and the other vehicle V1 of FIG. 3A can mutually pass cooperatively.
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FIG. 4B is a top view showing an example of an action pattern estimated under the situation of FIG. 4A. In FIG. 4A, three mutually passable regions were set, but the action pattern P of FIG. 4B is a pattern that selected mutual passage in the mutually passable region A. In action step S1 of this action pattern P, the host vehicle V0 moves to a target reference position pV0,S1 in front of the mutually passable region A and stops. Further, the other vehicle V1 moves to a target reference position pV1,S1 within the mutually passable region A and stops. In the next action step S2, the host vehicle V0 starts traveling via a target reference position pV0,S2 beyond the mutually passable region A. Further, the other vehicle V1 starts traveling via a target reference position pV1,S2 beyond the mutually passable region A. By such an action pattern P, the host vehicle V0 and the other vehicle V1 of FIG. 4A can mutually pass cooperatively.
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FIG. 4C is a top view showing another example of an action pattern in the mutual passage situation of FIG. 4A. The action pattern P shown here is a pattern that executes mutual passage in the mutually passable region A similarly to FIG. 4B, but has action steps S1 to S3. First, in action step S1, the host vehicle V0 moves to a target reference position pV0,S1 within the mutually passable region A and stops. Further, the other vehicle V1 moves to a target reference position pV1,S1 in front of the mutually passable region A and stops. In the next action step S2, the host vehicle V0 continues stopping. Further, the other vehicle V1 starts traveling via a target reference position pV1,S2 beyond the mutually passable region A. In action step S3, the host vehicle V0 starts traveling via a target reference position pV0,S3 beyond the mutually passable region A. Also by such an action pattern P, the host vehicle V0 and the other vehicle V1 of FIG. 4A can mutually pass cooperatively.
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Note that FIGS. 3B, 4B, and 4C are examples in which the action pattern P is simply expressed, and the actual action pattern P may be divided into finer action steps.
<<<Moving Body Action Matching Level Evaluation Unit 15>>>
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The moving body action matching level evaluation unit 15 compares movement information of the moving body (other vehicle V1) with the most recent target reference position, and calculates a matching level between the behavior of the moving body (other vehicle V1) and the mutual passage pattern. Details of the calculation method of the matching level here will be described later, but the value of the matching level in the present embodiment is assumed to be a value from 0 to 1, and the closer to 1, the higher the matching level between both.
<<<Mutual Passage Pattern Selection Unit 16>>>
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When there are a plurality of mutual passage patterns estimated by the mutual passage pattern estimation unit 14 (see FIGS. 4B and 4C), the mutual passage pattern selection unit 16 selects the mutual passage pattern with the highest matching level calculated by the moving body action matching level evaluation unit 15 as the highestpriority mutual passage pattern (hereinafter referred to as "passing pattern").
<<<Automatic Driving/Driving Assistance Information Generation Unit 17>>>
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The automatic driving/driving assistance information generation unit 17 converts information corresponding to the passing pattern selected by the mutual passage pattern selection unit 16 into control information for the actuator group 7 and the HMI device group 8 and transmits it. For example, if automatic driving is being implemented, it 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 and the like for controlling the host vehicle V0 so as to follow the traveling trajectory. Further, if driving assistance is being implemented, it notifies the driver of a recommended target position of the host vehicle V0 and the like via the display of the HMI device group 8.
<<<Information Output Unit 18>>>
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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, it outputs control command values included in an automatic driving traveling data group 38 to the actuator group 7 to control traveling of the host vehicle V0.
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Further, for example, it outputs planned trajectories and the like included in a sensor recognition data group 33, a mutual passage pattern data group 35, and a driving assistance data group 37, which will be described later, to the HMI device group 8, and presents them to occupants of the host vehicle V0. Thereby, in the host vehicle V0 during automatic driving, it is possible to present to the occupants how the vehicle system 1 interprets the surrounding traveling environment (display of the sensor recognition data group 33) and what kind of traveling is being planned (display of the mutual passage pattern data group 35 and the driving assistance data group 37).
<<Storage Unit 30>>
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The storage unit 30 is configured to include, for example, a storage device such as an HDD (Hard Disk Drive), flash memory, ROM (Read Only Memory), and a memory such as RAM (Random Access Memory). The storage unit 30 stores programs to be processed by the processing unit 10, data groups necessary for the processing, and the like. Further, it is also used for the purpose of temporarily storing data necessary for calculation of the program as a main memory when the processing unit 10 executes the program.
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In the present embodiment, as information for realizing the functions of the vehicle control device 3, 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 passage pattern data group 35, an action matching level data group 36, a driving assistance data group 37, an automatic driving traveling data group 38, and the like are stored in the storage unit 30. Hereinafter, details of each data group will be explained sequentially.
<<<Vehicle Information Data Group 31>>>
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The vehicle information data group 31 is a set of data regarding behavior of the host vehicle V0 detected by the vehicle sensor group 5 and the like. Data regarding behavior of the host vehicle V0 is information representing movement, state, and the like of the host vehicle V0, and includes, for example, information such as position, traveling speed, steering angle, accelerator operation amount, brake operation amount, and traveling route of the host vehicle V0.
<<<Road Environment Data Group 32>>>
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The road environment data group 32 is a set of data regarding the road environment around the host vehicle V0. Data regarding the road environment is information regarding roads around the host vehicle V0 including the road on which the host vehicle V0 is traveling. This includes, for example, information regarding shapes and attributes (traveling direction, speed limit, traveling regulations, etc.) of lanes constituting roads around the host vehicle V0, signal information, traffic information regarding traffic conditions (average speed, etc.) of each road or lane, statistical knowledge information based on past cases, and the like. Static information such as shapes and attributes of roads and lanes is included in, for example, map information acquired from the map information management device 6 and the like.
<<<Sensor Recognition Data Group 33>>>
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The sensor recognition data group 33 is a set of data regarding detection information or detection state by the external world sensor group 4. Detection information is, for example, information regarding environmental elements such as obstacles, road markings, signs, and signals around the host vehicle V0 specified by the external world sensor group 4 based on its sensing information, and sensing information itself around the host vehicle V0 by the external world sensor group 4 (point cloud information of LiDAR or RADAR, camera images, disparity images of stereo cameras, etc.). Detection state is information indicating a region detected by the sensor and its accuracy, and includes, for example, a lattice-like map such as OGM.
<<<Region Candidate Data Group 34>>>
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The region candidate data group 34 is a set of mutually passable regions determined by the passable region candidate determination unit 12. In the example of FIG. 3A, only the mutually passable region A is the region candidate data group 34, and in the example of FIG. 4A, the mutually passable regions A, B, and C are the region candidate data group 34.
<<<Mutual Passage Pattern Data Group 35>>>
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The mutual passage pattern data group 35 is a data group that aggregates mutual passage patterns estimated by the mutual passage pattern estimation unit 14. FIG. 5 is an example of the mutual passage pattern data group 35. The mutual passage pattern data group 35 exemplified here has a data column 35a indicating an overall action sequence (serial number), a data column 35b indicating a vehicle ID, a data column 35c indicating an action step for the vehicle ID, a data column 35d indicating a target reference position of each action step, a data column 35e indicating an action step end condition, and a data column 35f indicating a target passable region A.
<<<Action Matching Level Data Group 36>>>
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The action matching level data group 36 is a data group that summarizes the action matching level for each mutual passage pattern candidate calculated by the moving body action matching level evaluation unit 15, and has a data structure as exemplified in FIG. 6.
<<<Driving Assistance Data Group 37>>>
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The driving assistance data group 37 is a data group for following a traveling trajectory for an action step currently being executed in a traveling action plan of the host vehicle V0, determined by the automatic driving/driving assistance information generation unit 17, and includes control command values and the like to be output to the HMI device group 8 of the host vehicle V0.
<<<Automatic Driving Traveling Data Group 38>>>
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The automatic driving traveling data group 38 is a data group for following a traveling trajectory for an action step currently being executed in a traveling action plan of the host vehicle V0, determined by the automatic driving/driving assistance information generation unit 17, and includes control command values and the like to be output to the actuator group 7 of the host vehicle V0.
<<Communication Unit 40>>
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The communication unit 40 has a communication function with other devices connected via the in-vehicle network N. When the information acquisition unit 11 acquires various information from other devices via the in-vehicle network N and when the information output unit 18 outputs various information to other devices via the in-vehicle network N, the communication function of this communication unit 40 is used.
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The communication unit 40 is configured to include, for example, a network card compliant with communication standards such as IEEE802.3 or CAN (Controller Area Network). The communication unit 40 transmits and receives data based on various protocols between the vehicle control device 3 and other devices in the vehicle system 1.
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Note that, in FIG. 1, 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, it may be configured such that the equivalent of a hardware device in communication processing exists in the communication unit 40, and other device driver groups, communication protocol processing, and the like exist in the processing unit 10.
<Flowchart>
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Next, using FIGS. 7 and 8, a calculation method of the action matching level implemented by the moving body action matching level evaluation unit 15 of the vehicle control device 3 will be described.
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First, in step St1 of the flowchart of FIG. 7, the moving body action matching level evaluation unit 15 acquires mutual passage pattern candidates estimated by the mutual passage pattern estimation unit 14. In the following, it is assumed that the mutual passage patterns of FIGS. 4B and 4C are acquired as mutual passage pattern candidates.
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Next, in step St2, the moving body action matching level evaluation unit 15 acquires a target reference position pV1,S1 in action step S1 of the oncoming vehicle (other vehicle V1) from each mutual passage pattern candidate.
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In step St3, the moving body action matching 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 moving body movement information detection unit 13.
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In step St11, the moving body action matching level evaluation unit 15 calculates a distance from the current position of the oncoming vehicle (other vehicle V1) acquired in step St3 to each target reference position pV1,S1 acquired in step St2.
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In step St12, the moving body action matching level evaluation unit 15 calculates an estimated speed at which the oncoming vehicle (other vehicle V1) travels from the current position to each target reference position pV1,S1. Note that the estimated speed calculated here is generally proportional to the length of the distance calculated in step St11.
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In step St13, the moving body action matching level evaluation unit 15 determines whether the estimated speed calculated in step St12 is 0. Then, if the requirement is satisfied, the process proceeds to step St14, and if the requirement is not satisfied, the process proceeds to step St15.
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In step St14, the moving body action matching level evaluation unit 15 calculates the matching level by the calculation formula shown in the figure. Note that, in this calculation formula, "distance" is the distance calculated in step St11, "maximum distance" is a parameter preset according to the system, and "direction factor" is a coefficient determined depending on whether the target reference position pV1,S1 is in front of or behind the other vehicle V1. Therefore, the matching level calculated by this step becomes smaller as the distance approaches the maximum distance. Note that, although not shown in FIG. 7, it is assumed that when the distance is larger than the maximum distance, the matching level is set to 0.
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Note that the direction factor is, for example, 1 when the target reference position pV1,S1 is in front of the other vehicle V1, and is, for example, 0.8 when it is behind. Therefore, if the target reference position pV1,S1 is in front of the other vehicle V1, the matching level becomes higher compared to when it is behind.
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In step St15, the moving body action matching level evaluation unit 15 determines whether the target reference position pV1,S1 is in front of the oncoming vehicle (other vehicle V1) and the velocity vector of the oncoming vehicle (other vehicle V1) is directed forward. Then, if the requirement is satisfied, the process proceeds to step St16, and if the requirement is not satisfied, the process proceeds to step St17.
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In step St16, the moving body action matching level evaluation unit 15 calculates the matching level by the calculation formula shown in the figure. Note that, in this calculation formula, "oncoming vehicle speed" is the movement speed of the oncoming vehicle (other vehicle V1) acquired in step St3, and "estimated speed" is the estimated speed of the oncoming vehicle (other vehicle V1) calculated in step St12. Therefore, the closer the measured value of the movement speed of the oncoming vehicle (other vehicle V1) is to the estimated speed, the higher the matching level becomes.
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In step St17, the moving body action matching level evaluation unit 15 determines whether the target reference position pV1,S1 is behind the oncoming vehicle (other vehicle V1) and the velocity vector of the oncoming vehicle (other vehicle V1) is directed backward. Then, if the requirement is satisfied, the process proceeds to step St16, and if the requirement is not satisfied, the process ends.
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In step St18, the moving body action matching level evaluation unit 15 evaluates the matching level as 0. Note that this step is reached when the oncoming vehicle (other vehicle V1) is proceeding in a direction opposite to the target reference position pV1,S1.
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Through the above processing, the vehicle control device 3 can calculate the action matching level with each of a plurality of mutual passage pattern candidates based on the estimated speed of the oncoming vehicle (other vehicle V1).
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FIG. 8 is an example of the matching level calculated according to the flowchart of FIG. 7. In this figure, target reference position p1 corresponds to target reference position pV1,S1 of FIG. 4B, and target reference position p2 corresponds to target reference position pV1,S1 of FIG. 4C. As is obvious 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 larger 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 matching level (for example, 0.8) is calculated for the mutual passage pattern including the distant target reference position p1, and a relatively small matching level (for example, 0.2) is calculated for the mutual passage pattern including the nearby target reference position p2.
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Therefore, when a matching level as shown in FIG. 8 is calculated by the moving body action matching level evaluation unit 15 based on the observed speed of the other vehicle V1, it can be predicted that the other vehicle V1 will adopt the action step of FIG. 4B, so the mutual passage pattern selection unit 16 selects the mutual passage pattern of FIG. 4B, and the automatic driving/driving assistance information generation unit 17 generates various information so as to realize the mutual passage pattern of FIG. 4B.
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According to the vehicle control device of the present embodiment described above, it is possible to sequentially update information necessary for coordinated mutual passage on a narrow road based on the actual speed of the oncoming vehicle. By enabling the host vehicle V0 and the other vehicle V1 to perform mutual passage cooperatively, it is possible to shorten the time required for mutual passage in the mutually passable region by the host vehicle V0 and the other vehicle V1 and realize smooth traffic. When the vehicle control device 3 is used for automatic driving of the host vehicle V0, it is possible to improve riding comfort of occupants of the host vehicle V0. Further, when the vehicle control device 3 is used for driving assistance of the host vehicle V0, it is possible to improve riding comfort of occupants of the host vehicle V0 and improve operability of the driver of the host vehicle V0.
Second Embodiment
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Next, the second embodiment of the present invention will be described using FIGS. 9 and 10. In the first embodiment, the action matching level with each mutual passage pattern was evaluated based on the speed of the moving body, but in the present embodiment, the action matching level with each mutual passage pattern is evaluated based on the trajectory of the moving body. Note that, in the following, duplicate explanation of common points with the first embodiment will be omitted.
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FIG. 9 is a flowchart of moving body action matching level evaluation of the present embodiment. Steps S1 to S3 in the figure are equivalent to those of FIG. 7 of the first embodiment, so explanation thereof will be omitted.
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In step St21, the moving body action matching level evaluation unit 15 estimates a smooth route from the current position of the oncoming vehicle (other vehicle V1) acquired in step St3 to each target reference position pV1,S1 acquired in step St2. Various methods can be used for the route estimation method in this step, but for example, it may be estimated by connecting the current position of the other vehicle V1 and the target reference position pV1,S1 with a simple spline. Further, when an obstacle exists on the route estimated in such a manner, it may be corrected to a route that avoids the obstacle.
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In step St22, the moving body action matching level evaluation unit 15 calculates a root mean square error (hereinafter referred to as "RMSE") between the predicted trajectory acquired in step St3 and the estimated route acquired in step St21 for each target reference position.
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In step St23, the moving body action matching level evaluation unit 15 determines whether the RMSE calculated in step St22 is equal to or greater than a predetermined RMSE threshold value. Then, if the requirement is satisfied, the process proceeds to step St24, and if the requirement is not satisfied, the process proceeds to step St25. Note that the RMSE threshold value is a parameter preset according to the system (for example, 0.5).
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In step St24, the moving body action matching level evaluation unit 15 evaluates the matching level as 0.
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In step St25, the moving body action matching level evaluation unit 15 calculates the matching level by the calculation formula shown in the figure.
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Through the above processing, the vehicle control device 3 can calculate the action matching level with each of a plurality of mutual passage pattern candidates based on the estimated trajectory of the oncoming vehicle (other vehicle V1).
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FIG. 10 is an example of the matching level calculated according to the flowchart of FIG. 9. Target reference position p1 in the upper diagram corresponds to target reference position pV1,S1 of FIG. 4B, and target reference position p2 corresponds to target reference position pV1,S1 of FIG. 4C. When the other vehicle V1 moves from the current position to the target reference position p1, a route that goes straight and then turns left is estimated, whereas when moving to the target reference position p2, a route that promptly turns right is estimated. On the other hand, since the predicted trajectory of the other vehicle V1 acquired in step St3 is one that goes straight and then turns left, as shown in the lower diagram, a relatively large matching level (for example, 0.8) is calculated for the mutual passage pattern including the distant target reference position p1, and a relatively small matching level (for example, 0.1) is calculated for the mutual passage pattern including the nearby target reference position p2.
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Therefore, when a matching level as shown in FIG. 10 is calculated by the moving body action matching level evaluation unit 15, it can be predicted that the other vehicle V1 will adopt the action step of FIG. 4B, so the mutual passage pattern selection unit 16 selects the mutual passage pattern of FIG. 4B, and the automatic driving/driving assistance information generation unit 17 generates various information so as to realize the mutual passage pattern of FIG. 4B.
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According to the vehicle control device of the present embodiment described above, it is possible to sequentially update information necessary for coordinated mutual passage on a narrow road based on the actual trajectory of the oncoming vehicle.
Third Embodiment
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Next, the third embodiment of the present invention will be described using FIGS. 11 and 12. In the first embodiment, the action matching level with each mutual passage pattern was evaluated based on the speed of the moving body, and in the second embodiment, the action matching level with each mutual passage pattern was evaluated based on the trajectory of the moving body, but in the present embodiment, the action matching level with each mutual passage pattern is evaluated based on the steering angle of the moving body. Note that, in the following, duplicate explanation of common points with the first and second embodiments will be omitted.
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FIG. 11 is a flowchart of moving body action matching level evaluation of the present embodiment. Steps S1 to S3 in the figure are equivalent to those of FIG. 7 of the first embodiment, so explanation thereof will be omitted.
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Step St31 is a process for estimating a smooth route to the target reference position pV1,S1, and is equivalent to step St21 of the second embodiment.
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In step St32, the moving body action matching level evaluation unit 15 calculates a steering angle α necessary for turning when traveling to each target reference position pV1,S1 based on the route to each target reference position pV1,S1 estimated in step St31.
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In step St33, the moving body action matching level evaluation unit 15 determines whether the steering angle α calculated in step St32 is larger than the maximum steering angle of the oncoming vehicle (the steering angle capable of turning most sharply within specifications). Then, if the requirement is satisfied, the process proceeds to step St34, and if the requirement is not satisfied, the process proceeds to step St35. Note that satisfying the requirement of this step means that the oncoming vehicle (other vehicle V1) must perform at least one switchback maneuver when traveling to the target reference position pV1,S1.
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In step St34, the moving body action matching level evaluation unit 15 evaluates the matching level as 0.
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In step St35, the moving body action matching level evaluation unit 15 calculates the matching level by the calculation formula shown in the figure.
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Through the above processing, the vehicle control device 3 can calculate the action matching level with each of a plurality of mutual passage pattern candidates based on the estimated steering angle of the oncoming vehicle (other vehicle V1).
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FIG. 12 is an example of the matching level calculated according to the flowchart of FIG. 11. When the other vehicle V1 moves from the current position to the target reference position p3, a route that goes almost straight is estimated, whereas when the other vehicle V1 moves from the current position to the target reference position p4, a route that turns largely to the left is estimated. Therefore, the matching level with the mutual passage pattern that goes almost straight and moves to the target reference position p3 is calculated as a relatively large 0.9, and the matching level with the mutual passage pattern that turns largely to the left and moves to the target reference position p4 is calculated as a relatively small 0.1.
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Therefore, when a matching level as shown in FIG. 12 is calculated by the moving body action matching level evaluation unit 15, it can be predicted that the other vehicle V1 will adopt an action step heading toward the target reference position p3, so the mutual passage pattern selection unit 16 selects a mutual passage pattern including an action step heading toward the target reference position p3, and the automatic driving/driving assistance information generation unit 17 generates various information so as to realize the selected mutual passage pattern.
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According to the vehicle control device of the present embodiment described above, it is possible to sequentially update information necessary for coordinated mutual passage on a narrow road based on the steering angle of the oncoming vehicle.
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Note that, in the above embodiments, the matching level was calculated by a different method for each embodiment, but the matching level calculation methods of each embodiment may be combined, and the mutual passage pattern to be selected may be determined based on the sum or average value of matching levels calculated by different methods.
Fourth Embodiment
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Next, a vehicle control device 3 according to the fourth embodiment of the present invention will be described. Note that, duplicate explanation of common points with the above-described embodiments will be omitted. In the above embodiments, it was assumed that the driver follows the mutual passage pattern proposed by the vehicle control device 3 via the HMI device group 8 during driving assistance. However, an actual driver may not follow the proposed mutual passage pattern. Therefore, in the vehicle control device 3 of the present embodiment, when the driver has not followed or cannot follow the initially proposed mutual passage pattern, an alternative mutual passage pattern can be proposed.
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As an example of a situation where the driver does not follow the proposed mutual passage pattern, a situation can be considered where the driver feels difficulty in executing the initially proposed mutual passage pattern because the driving skill of the driver is low. Therefore, the vehicle control device 3 of the present embodiment proposes a simpler alternative mutual passage pattern when the proposed mutual passage pattern has not been executed for a predetermined time (for example, 10 seconds).
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Further, as another example of a situation where the driver does not follow the proposed mutual passage pattern, a situation can be considered where the driver cannot implement a mutual passage pattern including backward movement of the host vehicle V0 because the driving skill of the driver is low. Therefore, when the initially selected mutual passage pattern includes backward driving, the vehicle control device 3 of the present embodiment proposes from the beginning a second-best mutual passage pattern that does not include backward driving.
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According to the present embodiment described above, it is possible to propose a mutual passage pattern that can be implemented even by a driver with low driving skill.
Reference Signs List
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- 1
- vehicle system
- 2
- vehicle
- 3
- vehicle control device
- 10
- processing unit
- 11
- information acquisition unit
- 12
- passable region candidate determination unit
- 13
- moving body movement information detection unit
- 14
- mutual passage pattern estimation unit
- 15
- moving body action matching level evaluation unit
- 16
- mutual passage pattern selection unit
- 17
- automatic driving/driving assistance information generation unit
- 18
- information output unit
- 30
- storage unit
- 31
- vehicle information data group
- 32
- road environment data group
- 33
- sensor recognition data group
- 34
- region candidate data group
- 35
- mutual passage pattern data group
- 36
- action matching level data group
- 37
- driving assistance data group
- 38
- automatic driving traveling data group
- 40
- communication unit
- 4
- external world 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