Vehicle control device, vehicle control method, and storage medium

Abstract

A vehicle control device includes: an identification unit that identifies the conditions surrounding the vehicle; and a driving control unit that performs automatic driving to control at least one of acceleration, deceleration, and steering of the vehicle based on the conditions identified by the identification unit and map information including multiple coordinate points representing lanes on the path of the vehicle, wherein the driving control unit changes the control level of the automatic driving according to the number of the coordinate points.

Description

Technical Field

[0001] The present invention relates to a vehicle control device, a vehicle control method and a storage medium. Background Art

[0002] Conventionally, there is known a technique for repeatedly determining whether a road through which a vehicle passes exists on a high-precision map and notifying the vehicle of the determination result (for example, see Patent Document 1).

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Laid-Open No. 2018-189594 Summary of the Invention

[0006] Problems to be solved by the invention

[0007] Conventional technology mechanically notifies the driver of the availability of autonomous driving based on information stored in a map. However, conventional technology increases the processing load in locations where the amount of map information increases, sometimes preventing proper autonomous driving.

[0008] The present invention has been made in consideration of such circumstances, and one of its objects is to provide a vehicle control device, a vehicle control method, and a storage medium that enable more appropriate autonomous driving.

[0009] Solutions to Problems

[0010] The vehicle control device, vehicle control method, and storage medium of the present invention employ the following structures.

[0011] (1) A first embodiment of the present invention relates to a vehicle control device comprising: an identification unit for identifying conditions surrounding a vehicle; and a driving control unit for performing automatic driving to control at least one of acceleration, deceleration, and steering of the vehicle based on the conditions identified by the identification unit and map information including a plurality of coordinate points representing lanes on a path of the vehicle, wherein the driving control unit changes the control level of the automatic driving according to the number of the coordinate points.

[0012] (2) According to a second embodiment of the present invention, based on the first embodiment, when the number of coordinate points exceeds an upper limit, the driving control unit lowers the control level of the automatic driving compared to when the number of coordinate points is below the upper limit.

[0013] (3) The third solution of the present invention is based on the second solution. When the number of the coordinate points exceeds the upper limit, the driving control unit eliminates the coordinate points at intervals. When the number of the coordinate points after the elimination is below the upper limit, the driving control unit does not lower the control level of the automatic driving. When the number of the coordinate points after the elimination exceeds the upper limit, the driving control unit lowers the control level of the automatic driving.

[0014] (4) The fourth scheme of the present invention is based on any one of the first to third schemes, and the driving control unit changes the control level of the automatic driving according to the sum of the number of the coordinate points in a first range in front of the vehicle when observed from the position of the vehicle on the path and the number of the coordinate points in a second range behind the vehicle when observed from the position of the vehicle on the path, and the first range is wider than the second range.

[0015] (5) The fifth embodiment of the present invention is a vehicle control method, which causes a computer mounted on a vehicle to perform the following processing: identifying the surrounding conditions of the vehicle; performing automatic driving to control at least one of acceleration, deceleration and steering of the vehicle based on the identified conditions and map information including a plurality of coordinate points representing lanes on the path of the vehicle; and changing the control level of the automatic driving according to the number of the coordinate points.

[0016] (6) The sixth embodiment of the present invention is a storage medium storing a program for causing a computer mounted on a vehicle to perform the following processing: identifying conditions surrounding the vehicle; performing automatic driving to control at least one of acceleration, deceleration, and steering of the vehicle based on the identified conditions and map information including a plurality of coordinate points representing lanes on the path of the vehicle; and changing the control level of the automatic driving according to the number of the coordinate points.

[0017] Effects of the Invention

[0018] According to the above scheme, more appropriate autonomous driving can be performed. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a configuration diagram of a vehicle system using the vehicle control device according to the first embodiment.

[0020] Figure 2 It is a diagram schematically showing an example of the second map information.

[0021] Figure 3 It is a diagram schematically showing another example of the second map information.

[0022] Figure 4 This is a functional structure diagram of the first control unit and the second control unit.

[0023] Figure 5 This is a diagram showing an example of the correspondence between the driving mode and the control state and task of the host vehicle.

[0024] Figure 6 This is a flowchart showing an example of a series of processing procedures performed by the automatic driving control device according to the first embodiment.

[0025] Figure 7 This is a diagram for explaining an example of a method for counting the number of coordinate points.

[0026] Figure 8 This is a diagram for explaining another example of a method for counting the number of coordinate points.

[0027] Figure 9 This is a flowchart showing an example of a series of processing procedures performed by the automatic driving control device according to the second embodiment. DETAILED DESCRIPTION

[0028] Hereinafter, embodiments of a vehicle control device, a vehicle control method, and a storage medium according to the present invention will be described with reference to the accompanying drawings.

[0029] <First embodiment>

[0030] [Overall structure]

[0031] Figure 1 This is a structural diagram of a vehicle system 1 utilizing the vehicle control device of the first embodiment. The vehicle equipped with vehicle system 1 is, for example, a two-wheeled, three-wheeled, or four-wheeled vehicle, and its driving source is an internal combustion engine such as a diesel engine or a gasoline engine, an electric motor, or a combination thereof. The electric motor operates using power generated by a generator connected to the internal combustion engine, or power discharged from a secondary battery or fuel cell.

[0032] The vehicle system 1 includes, for example, a camera 10, a radar device 12, a LIDAR (Light Detection and Ranging) device 14, an object recognition device 16, a communication device 20, an HMI (Human Machine Interface) 30, vehicle sensors 40, a navigation device 50, an MPU (Map Positioning Unit) 60, a driver monitoring camera 70, a driving operating element 80, an automatic driving control device 100, a driving force output device 200, a braking device 210, and a steering device 220. These devices and equipment are interconnected via multiplexed communication lines such as CAN (Controller Area Network) communication lines, serial communication lines, wireless communication networks, and the like. Figure 1 The structure shown is merely an example, and a part of the structure may be omitted or other structures may be added. The automatic driving control device 100 is an example of a "vehicle control device."

[0033] The camera 10 is, for example, a digital camera utilizing a solid-state imaging element such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor). The camera 10 is mounted anywhere on the vehicle (hereinafter, the vehicle M) equipped with the vehicle system 1. To image the front, the camera 10 is mounted on the top of the windshield, behind the rearview mirror, or elsewhere. For example, the camera 10 periodically and repeatedly captures the surroundings of the vehicle M. The camera 10 may also be a stereo camera.

[0034] The radar device 12 radiates radio waves, such as millimeter waves, around the vehicle M and detects the radio waves (reflected waves) reflected by objects to detect at least the object's position (range and direction). The radar device 12 is mounted anywhere on the vehicle M. The radar device 12 can also detect the position and velocity of objects using the FM-CW (Frequency Modulated Continuous Wave) method.

[0035] LIDAR 14 irradiates light (or electromagnetic waves with a wavelength close to light) around the vehicle M and measures the scattered light. LIDAR 14 detects the distance to an object based on the time between light emission and light reception. The irradiated light is, for example, a pulsed laser. LIDAR 14 is mounted anywhere on the vehicle M.

[0036] The object recognition device 16 performs sensor fusion processing on the detection results from some or all of the camera 10, radar device 12, and LIDAR 14 to identify the position, type, speed, etc. of the object. The object recognition device 16 outputs the recognition results to the automatic driving control device 100. The object recognition device 16 can output the detection results from the camera 10, radar device 12, and LIDAR 14 directly to the automatic driving control device 100. The object recognition device 16 can also be omitted from the vehicle system 1.

[0037] The communication device 20 communicates with other vehicles around the host vehicle M using, for example, a cellular network, Wi-Fi network, Bluetooth (registered trademark), DSRC (Dedicated Short Range Communication), or communicates with various server devices via a wireless base station.

[0038] The HMI 30 presents various information to the occupants of the vehicle M and receives input operations from the occupants. The HMI 30 includes various display devices, speakers, buzzers, touch panels, switches, keys, and the like.

[0039] The vehicle sensor 40 includes a vehicle speed sensor for detecting the speed of the host vehicle M, an acceleration sensor for detecting acceleration, a gyro sensor for detecting angular velocity, and an orientation sensor for detecting the orientation of the host vehicle M. The gyro sensor may include, for example, a yaw rate sensor for detecting angular velocity about a vertical axis.

[0040] The navigation device 50 includes, for example, a GNSS (Global Navigation Satellite System) receiver 51, a navigation HMI 52, and a route determination unit 53. The navigation device 50 stores first map information 54 in a storage device such as an HDD (Hard Disk Drive) or a flash memory.

[0041] The GNSS receiver 51 receives radio waves from a plurality of GNSS satellites (artificial satellites) and determines the position of the host vehicle M based on the signals from the received radio waves. The GNSS receiver 51 outputs the determined position of the host vehicle M to the route determination unit 53 or to the automatic driving control device 100 directly or indirectly via the MPU 60. The position of the host vehicle M may also be determined or supplemented by an INS (Inertial Navigation System) using the output of the vehicle sensor 40.

[0042] The navigation HMI 52 includes a display device, a speaker, a touch panel, buttons, etc. The navigation HMI 52 may be partially or entirely shared with the aforementioned HMI 30 .

[0043] The route determination unit 53 refers to the first map information 54 , for example, to determine a route (hereinafter referred to as a route on a map) from the position of the vehicle M determined by the GNSS receiver 51 (or an input arbitrary position) to the destination input by the occupant using the navigation HMI 52 .

[0044] The first map information 54 is information that represents the shape of a road by displaying road links and nodes connected by the links. The first map information 54 may also include road curvature, POI (Point of Interest) information, etc. The route on the map is output to the MPU 60.

[0045] The navigation device 50 can also provide route guidance using the navigation HMI 52 based on the route on the map. The navigation device 50 can also be implemented as a function of a terminal device such as a smartphone or tablet computer held by the passenger. The navigation device 50 can also transmit the current location and destination to a navigation server via the communication device 20, and obtain a route equivalent to the route on the map from the navigation server.

[0046] The MPU 60 includes, for example, a recommended lane determination unit 61, which stores the second map information 62 in a storage device such as an HDD or flash memory. The recommended lane determination unit 61 is implemented by a hardware processor such as a CPU (Central Processing Unit) executing a program (software). The recommended lane determination unit 61 can be implemented by hardware (including circuitry) such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a GPU (Graphics Processing Unit), or can be implemented through the coordinated cooperation of software and hardware. The program can be pre-stored in the storage device of the MPU 60 (a storage device having a non-transitory storage medium), or can be stored in a removable storage medium such as a DVD or CD-ROM and installed in the storage device of the MPU 60 by attaching the storage medium (non-transitory storage medium) to a drive device.

[0047] The recommended lane determination unit 61 divides the route on the map provided by the navigation device 50 into a plurality of blocks (for example, every 100 meters in the vehicle's travel direction) and determines a recommended lane for each block by referring to the second map information 62. The recommended lane determination unit 61 determines the lane to be driven on from the left. If the route on the map has a branch, the recommended lane determination unit 61 determines a recommended lane so that the host vehicle M can travel on a reasonable route to the branch destination.

[0048] The second map information 62 is map information with higher accuracy than the first map information 54. The second map information 62 includes, for example, information related to lane centers and lane boundaries. The lane center information includes, for example, dotted and dashed lines connecting the coordinate points of the centers of several lanes. The lane boundary information includes, for example, dotted and dashed lines connecting the coordinate points of the boundaries of several lanes.

[0049] Figure 2This figure schematically illustrates an example of second map information 62. For example, assuming a two-lane road, a first lane LN1, one of the two lanes, is divided by dividing lines LM1 and LM2, while a second lane LN2, the other of the two lanes, is divided by dividing lines LM2 and LM3. In this case, the second map information 62 includes, as information related to the center of the first lane LN1, a dotted line and a dashed line (C1 in the figure) connecting the coordinate point exactly halfway between dividing lines LM1 and LM2 (aligned in the direction of the road). Similarly, the second map information 62 includes, as information related to the center of the second lane LN2, a dotted line and a dashed line (C2 in the figure) connecting the coordinate point exactly halfway between dividing lines LM2 and LM3 (aligned in the direction of the road).

[0050] Figure 3 This figure schematically illustrates another example of second map information 62. As shown in the example, second map information 62 may include, as information related to the boundary of first lane LN1, a dotted or dashed line connecting the coordinate points of dividing line LM1 (aligned in the road's extending direction) and a dotted or dashed line connecting the coordinate points of dividing line LM2 (aligned in the road's extending direction). Similarly, second map information 62 may include, as information related to the boundary of second lane LN2, a dotted or dashed line connecting the coordinate points of dividing line LM2 (aligned in the road's extending direction) and a dotted or dashed line connecting the coordinate points of dividing line LM3 (aligned in the road's extending direction).

[0051] The spacing between coordinate points in the center of a lane and / or at the lane boundaries is typically uniform. Specifically, the spacing between coordinate points is approximately 5 meters. The spacing between coordinate points is not limited to uniform and can vary depending on the road shape. For example, on a curving road, the spacing between coordinate points can be narrower than on a straight road.

[0052] The second map information 62 may also include road information, traffic restriction information, address information (address / zip code), facility information, telephone number information, and information on prohibited sections for Mode A or Mode B, described later. The second map information 62 can be updated at any time by communicating with other devices via the communication device 20.

[0053] The driver monitoring camera 70 is, for example, a digital camera utilizing a solid-state imaging element such as a CCD or CMOS. The driver monitoring camera 70 is mounted at any location within the vehicle M in such a manner that it can capture the head of an occupant (hereinafter referred to as the driver) seated in the driver's seat of the vehicle M from the front (in an orientation such that the face is captured). For example, the driver monitoring camera 70 is mounted above a display device located in the center of the instrument panel of the vehicle M.

[0054] The driving operating parts 80 include, for example, an accelerator pedal, a brake pedal, a shift lever, and other operating parts in addition to the steering wheel 82. A sensor that detects the amount of operation or the presence or absence of operation is installed on the driving operating part 80. The detection result of the sensor is output to the automatic driving control device 100, or is output to a part or all of the driving drive force output device 200, the braking device 210, and the steering device 220. The steering wheel 82 is an example of an "operating part that accepts steering operations performed by the driver." The steering wheel 82 does not necessarily have to be annular, and can also be in the form of a special-shaped steering wheel, a joystick, a button, etc. A steering grip sensor 84 is installed on the steering wheel 82. The steering wheel grip sensor 84 is implemented by an electrostatic capacitance sensor, etc., and outputs a signal to the automatic driving control device 100 that can detect whether the driver is gripping the steering wheel 82 (that is, contacting in a state where force can be applied).

[0055] The automatic driving control device 100 includes, for example, a first control unit 120 and a second control unit 160. The first control unit 120 and the second control unit 160 are respectively implemented by executing a program (software) through a hardware processor such as a CPU. Some or all of these components can be implemented by hardware (including a circuit unit; circuitry) such as an LSI, ASIC, FPGA, GPU, etc., or can be implemented by the collaboration of software and hardware. The program can be pre-stored in a storage device such as an HDD or flash memory of the automatic driving control device 100 (a storage device having a non-temporary storage medium), or can be stored in a removable storage medium such as a DVD or CD-ROM, and installed in the HDD or flash memory of the automatic driving control device 100 by assembling the storage medium (non-temporary storage medium) in a drive device.

[0056] Figure 4 This is a functional configuration diagram of first control unit 120 and second control unit 160. First control unit 120 includes, for example, recognition unit 130, action plan generation unit 140, and mode determination unit 150. The combination of action plan generation unit 140 and second control unit 160, or the combination of action plan generation unit 140, mode determination unit 150, and second control unit 160, is an example of a "driving control unit."

[0057] The first control unit 120, for example, concurrently implements functions based on AI (artificial intelligence) and pre-defined models. For example, the "intersection recognition" function can be implemented by concurrently executing intersection recognition using deep learning and other methods and recognition based on pre-defined conditions (such as the presence of pattern-matching signals and road signs), and then scoring both for comprehensive evaluation. This ensures the reliability of autonomous driving.

[0058] The recognition unit 130 identifies the surrounding conditions or environment of the host vehicle M. For example, the recognition unit 130 identifies objects around the host vehicle M based on information input from the camera 10, radar device 12, and LIDAR 14 via the object recognition device 16. Examples of objects recognized by the recognition unit 130 include bicycles, motorcycles, four-wheeled vehicles, pedestrians, road signs, road markings, dividing lines, utility poles, guardrails, and fallen objects. Furthermore, the recognition unit 130 identifies the object's state, including its position, velocity, and acceleration. The object's position is identified, for example, as a relative coordinate position (i.e., relative position relative to the host vehicle M) with a representative point (center of gravity, drive shaft center, etc.) of the host vehicle M as the origin, for control purposes. The object's position can be represented by a representative point, such as the object's center of gravity or corner, or by a displayed area. The object's "state" can also include its acceleration, jerk, or "behavior" (e.g., whether it is currently changing lanes or about to change lanes).

[0059] Furthermore, the recognition unit 130 identifies, for example, the lane in which the host vehicle M is traveling (hereinafter referred to as the host lane) and adjacent lanes adjacent to the host lane. For example, the recognition unit 130 obtains the second map information 62 from the MPU 60, compares the pattern of road dividing lines (e.g., the arrangement of solid and dashed lines) included in the obtained second map information 62 with the pattern of road dividing lines around the host vehicle M recognized from the image of the camera 10, and thereby recognizes the space between the dividing lines as the host lane and the adjacent lane.

[0060] The recognition unit 130 is not limited to road dividing lines. It can also recognize lanes such as the vehicle's own lane and adjacent lanes by recognizing road dividing lines and road boundaries (road boundaries) including shoulders, curbs, medians, guardrails, etc. This recognition can also take into account the position of the vehicle M obtained from the navigation device 50 and the processing results of the INS. In addition, the recognition unit 130 can recognize temporary stop signs, obstacles, red lights, toll booths, and other road features.

[0061] Furthermore, when recognizing the host lane, the recognition unit 130 recognizes the relative position and posture of the host vehicle M relative to the host lane. For example, the recognition unit 130 may use the deviation of the host vehicle M's reference point from the lane center and the angle formed by the host vehicle M's travel direction relative to a line connecting the coordinate points at the lane center as the relative position and posture of the host vehicle M relative to the host lane. Alternatively, the recognition unit 130 may recognize the position of the host vehicle M's reference point relative to either end of the host lane (a road dividing line or a road boundary) as the relative position of the host vehicle M relative to the host lane.

[0062] The action plan generation unit 140 generates a future target trajectory for the vehicle M to automatically (without relying on the driver's operation) travel in the driving state specified by the event described later, in principle, in the recommended lane determined by the recommended lane determination unit 61 and in a manner that can respond to the surrounding conditions of the vehicle M.

[0063] The target trajectory includes, for example, a speed element. For example, the target trajectory is represented by a trajectory in which the locations (track points) that the vehicle M should arrive at are arranged in sequence. Track points are locations that the vehicle M should arrive at at predetermined driving distances (e.g., a few meters) along the way. Different from this, target speeds and target accelerations at predetermined sampling times (e.g., a few tenths of a second) are generated as part of the target trajectory. Track points can also be locations that the vehicle M should arrive at at predetermined sampling times. In this case, information on the target speed and target acceleration is represented by the intervals between track points.

[0064] To address the surrounding conditions of the host vehicle M, the action plan generation unit 140 may exceptionally generate a target trajectory for the host vehicle M to travel in a lane other than the recommended lane (e.g., a lane adjacent to the recommended lane). In other words, the action plan generation unit 140 may, in principle, generate a target trajectory for the host vehicle M to travel in the recommended lane, but may, depending on the surrounding conditions of the host vehicle M, exceptionally generate a target trajectory for the host vehicle M to travel in another lane.

[0065] When generating the target trajectory, the action plan generation unit 140 determines an event for autonomous driving (including some driving support) along the route for which the recommended lane is determined. An autonomous driving event is information that specifies the behavior that the vehicle M should take during autonomous driving (partial driving support), that is, the state (or driving plan) during driving.

[0066] Examples of autonomous driving events include constant speed driving events, following driving events, lane change events, diverging events, merging events, and takeover events. A constant speed driving event is a driving strategy that causes the host vehicle M to travel in the same lane at a constant speed. A following driving event is a driving strategy that causes the host vehicle M to follow another vehicle (hereinafter referred to as the preceding vehicle) that is within a specified distance (e.g., within 100 meters) ahead of the host vehicle M in the lane and is closest to the host vehicle M.

[0067] The so-called "following" can be, for example, a driving plan that maintains a constant inter-vehicle distance (relative distance) between the vehicle M and the preceding vehicle, or a driving plan that not only maintains a constant inter-vehicle distance between the vehicle M and the preceding vehicle but also makes the vehicle M drive in the center of the lane.

[0068] A lane change event is a driving strategy that causes the host vehicle M to change lanes from its own lane to an adjacent lane. A diverging event is a driving strategy that causes the host vehicle M to diverge to the lane on the destination side at a road fork. A merging event is a driving strategy that causes the host vehicle M to merge onto the main road at a merging point. A takeover event is a driving strategy that ends automated driving and switches to manual driving.

[0069] Events may include, for example, overtaking events and avoidance events. An overtaking event is a driving strategy in which the host vehicle M temporarily changes lanes to an adjacent lane, overtaking the preceding vehicle in the adjacent lane, and then changes lanes again to the original lane. An avoidance event is a driving strategy in which the host vehicle M performs at least one of braking and steering to avoid an obstacle in front of the host vehicle M.

[0070] In this way, the action plan generating unit 140 sequentially determines these multiple events on the route to the destination, and generates a target trajectory for causing the vehicle M to travel in the state specified by each event while taking into account the surrounding conditions of the vehicle M.

[0071] The mode determination unit 150 determines the driving mode of the host vehicle M to be one of a plurality of driving modes. The plurality of driving modes assign different tasks to the driver. The mode determination unit 150 includes, for example, a driver state determination unit 152 and a mode change processing unit 154. The individual functions of these will be described later.

[0072] Figure 5 : This is a diagram showing an example of the correspondence between the driving mode and the control state and task of the vehicle M. Among the driving modes of the vehicle M, there are five modes, for example, mode A to mode E. In the control state, that is, the degree of automation (control level) of the driving control of the vehicle M, mode A is the highest, followed by mode B, mode C, and mode D, and mode E is the lowest. On the contrary, in the tasks assigned to the driver, mode A is the lightest, followed by mode B, mode C, and mode D, which become heavy, and mode E is the heaviest. Since the control state is not an automatic driving in modes D and E, the automatic driving control device 100 performs its duties before terminating the control of the automatic driving and transferring to driving assistance or manual driving. The following is an example of the content of each driving mode.

[0073] In Mode A, the vehicle is in automatic driving mode, and the driver is not required to monitor the front or control the steering wheel 82 (in the figure, steering control). However, even in Mode A, the driver is required to maintain a body posture that allows them to quickly switch to manual driving in response to requests from the system centered around the automatic driving control device 100.

[0074] Automatic driving, as used herein, means that steering, acceleration, and deceleration are controlled independently of driver input. The front refers to the space in the direction of travel of the host vehicle M, as visually confirmed through the windshield. Mode A, sometimes referred to as TJP (Traffic Jam Pilot), is a driving mode that can be executed when conditions are met, such as when the host vehicle M is traveling at a specified speed (e.g., approximately 50 km / h) on a motorway, such as a highway, and there is a preceding vehicle to be followed. If these conditions are no longer met, the mode determination unit 150 changes the driving mode of the host vehicle M to Mode B.

[0075] In mode B, it becomes a driving support state, and the driver is assigned the task of monitoring the front of the vehicle M (hereinafter referred to as front monitoring), but is not assigned the task of holding the steering wheel 82. In mode C, it becomes a driving support state, and the driver is assigned the task of monitoring the front and the task of holding the steering wheel 82. Mode D is a driving mode in which at least one of the steering and acceleration and deceleration of the vehicle M requires a certain degree of driver-based driving operation. For example, in mode D, driving support such as ACC (Adaptive Cruise Control) and LKAS (Lane Keeping Assist System) is performed. In mode E, it becomes a manual driving state in which both steering and acceleration and deceleration require the driver's driving operation. In both mode D and mode E, it is natural that the driver is assigned the task of monitoring the front of the vehicle M.

[0076] The automatic driving control device 100 (and the driving support device (not shown)) performs automatic lane changes according to the driving mode. In the automatic lane change, there are automatic lane changes based on system requirements (1) and automatic lane changes based on driver requirements (2). In the automatic lane change (1), there are automatic lane changes for overtaking when the speed of the preceding vehicle is greater than a certain threshold compared to the speed of the vehicle, and automatic lane changes for traveling toward the destination (automatic lane changes based on the recommended lane change). Automatic lane change (2) is to change the lane of the vehicle M in the direction of operation when the conditions such as speed and positional relationship with surrounding vehicles are met and the direction indicator is operated by the driver.

[0077] In mode A, the automatic driving control device 100 does not execute either automatic lane change (1) or (2). In modes B and C, the automatic driving control device 100 executes both automatic lane change (1) and (2). In mode D, the driving support device (not shown) does not execute automatic lane change (1) but executes automatic lane change (2). In mode E, neither automatic lane change (1) nor (2) is executed.

[0078] If the driver is not performing the tasks of the determined driving mode (hereinafter referred to as the current driving mode), the mode determination unit 150 changes the driving mode of the host vehicle M to a driving mode with a heavier task.

[0079] For example, in mode A, if the driver is in a physical posture that cannot be switched to manual driving in response to a request from the system (for example, if the driver continues to look around outside the permitted area or if a sign of driving difficulty is detected), the mode decision unit 150 uses the HMI30 to urge the driver to switch to manual driving. If the driver does not respond, the vehicle M is gradually stopped by the shoulder of the road and the automatic driving is stopped. After the automatic driving is stopped, the vehicle enters the state of mode D or E, and the vehicle M can be started by manual operation of the driver. The same applies to "stopping automatic driving" below. In mode B, if the driver is not monitoring the front, the mode decision unit 150 uses the HMI30 to urge the driver to monitor the front. If the driver does not respond, the vehicle M is gradually stopped by the shoulder of the road and the automatic driving is stopped. In mode C, when the driver is not monitoring the front or is not holding the steering wheel 82, the mode determination unit 150 uses the HMI 30 to urge the driver to monitor the front and / or hold the steering wheel 82. If the driver does not respond, the vehicle M is gradually stopped by the shoulder of the road and the automatic driving is stopped.

[0080] To perform the aforementioned mode change, the driver state determination unit 152 monitors the driver's state and determines whether the driver's state is appropriate for the task. For example, the driver state determination unit 152 analyzes images captured by the driver monitoring camera 70 and performs posture estimation processing to determine whether the driver is in a body posture that prevents the system from requesting a transition to manual driving. The driver state determination unit 152 also analyzes images captured by the driver monitoring camera 70 and performs line of sight estimation processing to determine whether the driver is monitoring the road ahead.

[0081] The mode change processing unit 154 performs various processes for mode change. For example, the mode change processing unit 154 instructs the action plan generation unit 140 to generate a target trajectory for roadside stopping, instructs a driving support device (not shown) to operate, or controls the HMI 30 to prompt the driver to take action.

[0082] The second control unit 160 controls the driving force output device 200 , the braking device 210 , and the steering device 220 so that the host vehicle M passes through the target trajectory generated by the action plan generation unit 140 at a predetermined timing.

[0083] The second control unit 160 includes, for example, an acquisition unit 162, a speed control unit 164, and a steering control unit 166. The acquisition unit 162 acquires the information of the target track (track point) generated by the action plan generation unit 140 and stores it in a memory (not shown). The speed control unit 164 controls the driving force output device 200 or the braking device 210 based on the speed element associated with the target track stored in the memory. The steering control unit 166 controls the steering device 220 according to the degree of curvature of the target track stored in the memory. The processing of the speed control unit 164 and the steering control unit 166 is implemented, for example, by a combination of feedforward control and feedback control. As an example, the steering control unit 166 performs a combination of feedforward control corresponding to the curvature of the road ahead of the vehicle M and feedback control based on the deviation from the target track.

[0084] The driving force output device 200 outputs the driving force (torque) used to propel the vehicle to the drive wheels. The driving force output device 200 comprises, for example, a combination of an internal combustion engine, an electric motor, and a transmission, and an ECU (Electronic Control Unit) that controls them. The ECU controls the aforementioned components based on information input from the second control unit 160 or from the driving control element 80.

[0085] The brake device 210 includes, for example, a brake caliper, a hydraulic cylinder that transmits hydraulic pressure to the brake caliper, an electric motor that generates hydraulic pressure in the hydraulic cylinder, and a brake ECU. The brake ECU controls the electric motor based on information input from the second control unit 160 or information input from the driver operating element 80, outputting brake torque corresponding to the braking operation to each wheel. The brake device 210 may include a mechanism that transmits the hydraulic pressure generated by operating the brake pedal included in the driver operating element 80 to the hydraulic cylinder via a master hydraulic cylinder as a backup. The brake device 210 is not limited to the structure described above, and may also be an electronically controlled hydraulic brake device that controls the actuator based on information input from the second control unit 160 and transmits the hydraulic pressure of the master hydraulic cylinder to the hydraulic cylinder.

[0086] The steering system 220 includes, for example, a steering ECU and an electric motor. The electric motor, for example, applies force to a rack-and-pinion mechanism to change the direction of the steering wheel. The steering ECU drives the electric motor to change the direction of the steering wheel based on information input from the second control unit 160 or information input from the driving operating element 80.

[0087] [Processing Flow]

[0088] Hereinafter, the flow of a series of processes performed by the automatic driving control device 100 according to the first embodiment will be described using a flowchart. Figure 6This is a flowchart showing an example of a series of processing flows performed by the automatic driving control device 100 according to the first embodiment. The processing in this flowchart can be repeatedly executed at a predetermined cycle when, for example, the following execution conditions are satisfied.

[0089] Condition (i): The automatic driving control device 100 can obtain the second map information 62 from the MPU 60 .

[0090] Condition (ii): The host vehicle M is not traveling in the prohibited section of mode A or mode B.

[0091] Condition (iii): No abnormality occurs in the second map information 62 .

[0092] First, the recognition unit 130 refers to the second map information 62 output from the MPU 60 to the automatic driving control device 100, identifies the own lane and the adjacent lane based on the second map information 62 and the image of the camera 10, and then identifies the relative position and posture of the own vehicle M relative to the identified own lane (step S100).

[0093] Next, the mode change processing unit 154 refers to the second map information 62 output from the MPU 60 to the automatic driving control device 100 and counts the number of coordinate points on the second map information 62 (high-precision map) that are located around the current position of the host vehicle M (the relative position identified by the recognition unit 130) (step S102). Specifically, the mode change processing unit 154 counts the number Nc of coordinate points in the center of the lane and / or the number Nb of coordinate points at the boundary of the lane.

[0094] Figure 7 This figure illustrates an example method for counting coordinate points. In the figure, P0 represents the current position of the host vehicle M on the route to the destination. For example, the mode change processing unit 154 counts the number of coordinate points Nc located in the center of a first range of lanes "ahead" of the host vehicle M, as viewed from the current position P0 of the host vehicle M. Furthermore, the mode change processing unit 154 counts the number of coordinate points Nc located in the center of a second range of lanes "behind" the host vehicle M, as viewed from the current position P0 of the host vehicle M.

[0095] The first range and / or the second range may be absolute fixed values, or relative values that vary depending on the speed of the host vehicle M. For example, if the first range and the second range are fixed values, the first range may be set to approximately 300 m, and the second range may be set to approximately 200 m. In other words, the first range may be set to a larger range than the second range.

[0096] The mode change processing unit 154 may count the number of coordinate points in the first and second ranges based on the current position of the vehicle M, or in addition thereto, count the number of coordinate points in a third range ahead of the first range.

[0097] Figure 8 This figure illustrates another example of a method for counting coordinate points. For example, the mode change processing unit 154 counts the number Nc of coordinate points in the center of the lane within a third range, located further "ahead" of the first range. Similar to the first and second ranges, the third range can be an absolute fixed value or a relative value that varies depending on factors such as the speed of the vehicle M. For example, the third range can be set to approximately 300 m.

[0098] exist Figure 7 and Figure 8 , the mode change processing unit 154 is described as counting the number Nc of coordinate points located in the center of the lanes of the first, second, and third ranges, but the present invention is not limited to this. For example, the mode change processing unit 154 may count the number Nb of coordinate points located at the boundaries of the lanes of the first, second, and third ranges instead of counting the number Nc of coordinate points located in the center of the lanes.

[0099] return Figure 6 Next, the mode change processing unit 154 determines whether the number of counted coordinate points exceeds the upper limit number N. MAX (Step S104).

[0100] For example, Figure 7 In this way, the mode change processing unit 154 counts the number of coordinate points in the first range and the second range, calculates the sum of the number of coordinate points in the first range and the number of coordinate points in the second range, and determines whether the calculated sum exceeds the first upper limit. MAX1 . The first upper limit MAX1 For example, it may be around 500.

[0101] As described above, in the second map information 62, the intervals between lane center coordinate points and lane boundary coordinate points are typically about 5 meters. Therefore, if the first range is 300 meters and the second range is 200 meters, there are typically about 100 coordinate points within the combined driving range of 500 meters.

[0102] On the other hand, there are more than the first upper limit in the first range and the second range. MAX1In the case where there are 500 coordinate points, which is five times the normal number, it can be inferred that there is some abnormality in the second map information 62 itself, or some abnormality due to the complex road structure or traffic conditions. That is, the mode change processing unit 154 compares the number of coordinate points existing in the first range and the second range with the first upper limit number. MAX1 , to determine whether some abnormality has occurred in the second map information 62 itself, or some abnormality has occurred due to the complex road structure and traffic conditions.

[0103] Furthermore, if Figure 8 In this manner, the mode change processing unit 154 counts the number of coordinate points in the third range and determines whether the number of coordinate points in the third range exceeds the second upper limit. MAX2 The second upper limit MAX2 For example, it may be around 300.

[0104] When the third range is 300 [m], there are usually about 60 coordinate points within the driving range of 300 [m].

[0105] On the other hand, in the third range, there are more than the second upper limit MAX2 In the case where there are 300 coordinate points, which is five times the normal number, it can be inferred that there is some abnormality in the second map information 62 itself, or some abnormality due to the complex road structure or traffic conditions. That is, the mode change processing unit 154 compares the number of coordinate points existing in the third range with the second upper limit number. MAX2 , to determine whether some abnormality has occurred in the second map information 62 itself, or some abnormality has occurred due to the complex road structure and traffic conditions.

[0106] The mode change processing unit 154 is configured to process the coordinate points when the number of coordinate points exceeds the upper limit N. MAX In other words, the mode change processing unit 154 changes the driving mode of the host vehicle M to a driving mode with a lower control level when it can be inferred that some abnormality has occurred in the second map information 62 itself or some abnormality has occurred due to the complex road structure or traffic conditions.

[0107] For example, when the driving mode of the host vehicle M is mode A or mode B, the mode change processing unit 154 changes the driving mode to mode C or mode D, which has a lower control level than mode B. In other words, the mode change processing unit 154 changes the driving mode to mode C or mode D, which places a heavier responsibility (task) on the occupants than mode B.

[0108] As described above, Modes A and B are modes in which the occupant is not required to grip the steering wheel 82. In contrast, Modes C and D are modes in which the occupant is required to grip the steering wheel 82. Therefore, the mode change processing unit 154 determines that the number of coordinate points in the automatic driving or driving support exceeds the upper limit N. MAX In the case of , the driving mode of the host vehicle M is changed to a mode in which the grip of the steering wheel 82 is arranged as a responsibility for the occupants.

[0109] Mode E, which is a manual driving mode, is of course arranged so that the occupant is responsible for gripping the steering wheel 82. Therefore, the mode change processing unit 154 determines that the number of coordinate points in the automatic driving or driving support exceeds the upper limit N. MAX In the case of , you can also change from any automatic driving or driving support mode to Mode E.

[0110] On the other hand, the mode change processing unit 154 sets the number of coordinate points to the upper limit N. MAX In the following cases, the driving mode of the host vehicle M is not changed, and the current driving mode is continued (maintained) (step S108). That is, if it cannot be inferred that an abnormality has occurred in the second map information 62 itself, or if an abnormality has occurred due to complex road structure or traffic conditions, the mode change processing unit 154 does not change the driving mode of the host vehicle M, and the current driving mode is continued.

[0111] Next, the action plan generating unit 140 switches whether or not to output the target trajectory to the second control unit 160 according to the driving mode changed or maintained by the mode changing processing unit 154 (step S110 ).

[0112] For example, when the current driving mode is mode A, B, or C and the number of coordinate points is the upper limit N MAX In the following cases, the current driving mode is maintained. In this case, the action plan generation unit 140 outputs the target trajectory to the second control unit 160. Based on this, the second control unit 160 controls the acceleration, deceleration, and steering of the host vehicle M based on the target trajectory. As a result, in Mode A, autonomous driving based on the target trajectory is performed, while in Mode B or Mode C, driving support based on the target trajectory is performed.

[0113] On the other hand, when the current driving mode is mode A or B and the number of coordinate points exceeds the upper limit N MAX In the case of the above, change the current driving mode to mode C, D, or E with a lower control level.

[0114] For example, when changing to Mode C, the action plan generation unit 140 outputs the target trajectory to the second control unit 160, similar to when maintaining Mode C. Based on this, the second control unit 160 controls the acceleration, deceleration, and steering of the host vehicle M based on the target trajectory. As a result, driving support based on the target trajectory is performed in Mode C.

[0115] When the mode is changed to Mode D, the action plan generation unit 140 outputs the target trajectory to the second control unit 160. In this case, the second control unit 160 controls the driving force output device 200, the braking device 210, and the steering device 220, which are controlled based on the target trajectory. In other words, the second control unit 160 controls the acceleration, deceleration, and steering of the vehicle M.

[0116] When changing to Mode E, the action plan generation unit 140 does not output the target trajectory to the second control unit 160. In this case, the ECUs for the driving force output device 200, the braking device 210, and the steering device 220, which are controlled by the second control unit 160, control their own devices based on the driver's operation of the driving operating elements 80. In other words, the acceleration, deceleration, and steering of the vehicle M are controlled by manual driving. This concludes the process in this flowchart.

[0117] According to the first embodiment described above, the recognition unit 130 uses the second map information 62 to recognize the lane, and then recognizes the relative position and posture of the vehicle M relative to the recognized lane. The mode change processing unit 154 counts the number of coordinate points that exist around the current position of the vehicle M (the relative position recognized by the recognition unit 130) on the second map information 62. The mode change processing unit 154 changes the control level of the automatic driving according to the number of counted coordinate points. Specifically, the mode change processing unit 154 changes the control level of the automatic driving when the number of coordinate points exceeds the upper limit number N. MAX In the case where the number of coordinate points is the upper limit number N MAX The control level of the autonomous driving is lowered compared to the following situations.

[0118] This control allows the driver to continue some or all of the driving while traveling in locations where the amount of map information increases and the processing load increases. For example, when transitioning from mode A or B to mode C, D, or E, the driver of the vehicle M monitors the road ahead while maintaining control of the steering wheel 82, enabling them to respond to changes in the surrounding environment. In this way, the automatic driving control device 100 can perform more appropriate automatic driving by monitoring the coordinate points of the second map information 62.

[0119] <Second embodiment>

[0120] The second embodiment is described below. The second embodiment differs from the first embodiment in that the number of coordinate points exceeds the upper limit N. MAX In the case of exceeding the upper limit N MAX The following description will focus on the differences from the first embodiment, and the description of the points common to the first embodiment will be omitted. It should be noted that in the description of the second embodiment, the same reference numerals are used to indicate the same parts as those in the first embodiment.

[0121] Figure 9 This is a flowchart showing an example of a series of processing flows performed by the automatic driving control device 100 according to the second embodiment. The processing in this flowchart can be repeatedly executed at a predetermined cycle when, for example, some of the execution conditions described in the first embodiment are satisfied.

[0122] First, the recognition unit 130 refers to the second map information 62 output from the MPU 60 to the automatic driving control device 100, identifies the own lane and the adjacent lane based on the second map information 62 and the image of the camera 10, and then identifies the relative position and posture of the own vehicle M relative to the identified own lane (step S200).

[0123] Next, the mode change processing unit 154 refers to the second map information 62 output from the MPU 60 to the automatic driving control device 100, and counts the number of coordinate points on the second map information 62 (high-precision map) that exist around the current position of the vehicle M (the relative position identified by the identification unit 130) (step S202).

[0124] Next, the mode change processing unit 154 determines whether the number of counted coordinate points exceeds the upper limit N. MAX (Step S204).

[0125] The mode change processing unit 154 is configured to process the coordinate points when the number of coordinate points exceeds the upper limit N. MAX In the case of , the coordinate points are thinned out (reduced) (step S206).

[0126] For example, when the number of coordinate points in the first range and the second range exceeds the first upper limit, the mode change processing unit 154 MAX1 When the number of coordinate points is 500 (for example), the coordinate points in the first range and the second range are thinned out so that the interval between the coordinate points in the first range and the second range becomes 1 [m] or more.

[0127] Similarly, the mode change processing unit 154, for example, when the number of coordinate points in the third range exceeds the second upper limit, MAX2When the number of coordinate points is 300 (for example), the coordinate points in the third range are thinned out so that the interval between the coordinate points in the third range becomes 1 [m] or more.

[0128] Next, the mode change processing unit 154 determines whether the number of coordinate points after thinning out still exceeds the upper limit N. MAX (Step S208).

[0129] The mode change processing unit 154 determines that the number of coordinate points after thinning exceeds the upper limit N. MAX In the case of , the driving mode of the host vehicle M is changed to a driving mode with a lower control level (step S210).

[0130] On the other hand, the mode change processing unit 154 sets the number of coordinate points before thinning to the upper limit N. MAX In the following cases or after thinning, the number of coordinate points is the upper limit N MAX In the following cases, the driving mode of the host vehicle M is not changed, but the current driving mode is continued (maintained) (step S212 ).

[0131] Next, the action plan generating unit 140 switches whether or not to output the target trajectory to the second control unit 160 according to the driving mode changed or maintained by the mode changing processing unit 154 (step S214 ). The processing of this flowchart is thus terminated.

[0132] According to the second embodiment described above, the mode change processing unit 154 performs the operation when the number of coordinate points exceeds the upper limit N. MAX Then, the mode change processing unit 154 thins out the coordinate points after the thinning out, and the number of the coordinate points after the thinning out is the upper limit number N. MAX In the following cases, the control level of the autonomous driving will not be reduced, and the number of coordinate points after thinning exceeds the upper limit N MAX In this case, the control level of autonomous driving is reduced.

[0133] This control reduces the amount of map information by thinning out coordinate points even when traveling in locations where the amount of map information increases and the processing load is high. This results in more appropriate autonomous driving than in the first embodiment.

[0134] [Note]

[0135] The above-described embodiment can also be expressed as follows.

[0136] (Performance example 1)

[0137] A vehicle control device comprising:

[0138] a memory storing a program; and

[0139] Hardware processor,

[0140] The hardware processor performs the following processing by executing the program:

[0141] Identify the surrounding conditions of the vehicle;

[0142] performing automatic driving to control at least one of acceleration, deceleration, and steering of the vehicle based on the recognized situation and map information including a plurality of coordinate points representing lanes on a path of the vehicle; and

[0143] The control level of the autonomous driving is changed according to the number of the coordinate points.

[0144] (Performance example 2)

[0145] A vehicle control device comprising:

[0146] a memory storing a program; and

[0147] Hardware processor,

[0148] The hardware processor executes the program to perform the following processing:

[0149] Identify the surrounding conditions of the vehicle;

[0150] determining an event that identifies a state of the vehicle while traveling based on the recognized situation, the route to the vehicle's destination, and the vehicle's position;

[0151] determining the driving mode of the vehicle to be any one of a plurality of driving modes including a first driving mode (e.g., mode C, mode D, or mode E) and a second driving mode (e.g., mode A or mode B) that places a lighter task on the driver than the first driving mode,

[0152] Based on the determined event, automatic driving is performed to control at least one of acceleration, deceleration, and steering of the vehicle.

[0153] If the determined task of the driving mode is not performed by the driver, the driving mode of the vehicle is changed to a driving mode with a heavier task,

[0154] When the number of coordinate points exceeds an upper limit, the driving mode of the vehicle is changed to a driving mode with a heavier task than when the number of coordinate points is equal to or less than the upper limit.

[0155] While specific embodiments of the present invention have been described above, the present invention is not limited to these embodiments at all, and various modifications and substitutions can be made without departing from the spirit of the present invention.

[0156] Description of reference numerals:

[0157] 10 cameras

[0158] 12 radar devices

[0159] 14LIDAR

[0160] 16 Object recognition device

[0161] 20 communication devices

[0162] 30HMI

[0163] 40 vehicle sensors

[0164] 50 navigation device

[0165] 51GNSS receiver

[0166] 52 Navigation HMI

[0167] 53 Path Determination Unit

[0168] 54 First Map Information

[0169] 60MPU

[0170] 61 Recommended Lane Decision Department

[0171] 62 Second Map Information

[0172] 70 driver monitoring cameras

[0173] 82 steering wheel

[0174] 84 steering control sensor

[0175] 100 automatic driving control devices

[0176] 120 First Control Unit

[0177] 130 Identification Department

[0178] 140 Action Plan Generation Department

[0179] 150 Mode Determination Department

[0180] 160 Second Control Unit

[0181] 162 Acquisition Department

[0182] 164 speed control unit

[0183] 166 Steering Control Unit

[0184] 200 driving force output device

[0185] 210 brake device

[0186] 220 steering device.

Claims

1. A vehicle control device, wherein: The vehicle control device comprises: a recognition unit that recognizes a condition surrounding the vehicle; and a driving control unit that performs automatic driving to control at least one of acceleration, deceleration, and steering of the vehicle based on the situation recognized by the recognition unit and map information including a plurality of coordinate points representing lanes on a path of the vehicle; The driving control unit changes the control level of the automatic driving according to the number of the coordinate points. The driving control unit thins out the coordinate points when the number of the coordinate points exceeds an upper limit. The driving control unit does not lower the control level of the automatic driving when the number of the coordinate points after thinning out is less than the upper limit. The driving control unit lowers the control level of the automatic driving when the number of the coordinate points after thinning out exceeds the upper limit.

2. The vehicle control device according to claim 1, wherein: The driving control unit changes the control level of the automatic driving according to the sum of the number of the coordinate points in a first range in front of the vehicle when viewed from the position of the vehicle on the path and the number of the coordinate points in a second range in rear of the vehicle when viewed from the position of the vehicle on the path, The first range is wider than the second range.

3. A vehicle control method, wherein: The vehicle control method causes a computer mounted on the vehicle to execute the following processing: Identify the surrounding conditions of the vehicle; performing automatic driving to control at least one of acceleration, deceleration, and steering of the vehicle based on the recognized situation and map information including a plurality of coordinate points representing lanes on a path of the vehicle; changing the control level of the autonomous driving according to the number of the coordinate points; When the number of the coordinate points exceeds an upper limit, thinning out the coordinate points; When the number of the coordinate points after thinning out is less than the upper limit, the control level of the automatic driving is not lowered; and When the number of the coordinate points after thinning out exceeds the upper limit, the control level of the automatic driving is lowered.

4. A storage medium storing a program, wherein: The program is for causing a computer mounted on a vehicle to execute the following processing: Identify the surrounding conditions of the vehicle; performing automatic driving to control at least one of acceleration, deceleration, and steering of the vehicle based on the recognized situation and map information including a plurality of coordinate points representing lanes on a path of the vehicle; changing the control level of the autonomous driving according to the number of the coordinate points; When the number of the coordinate points exceeds an upper limit, thinning out the coordinate points; When the number of the coordinate points after thinning out is less than the upper limit, the control level of the automatic driving is not lowered; and When the number of the coordinate points after thinning out exceeds the upper limit, the control level of the automatic driving is lowered.

Images