Vehicle control device, vehicle control method, and program

Abstract

To provide a vehicle control device that even when there is an error in road compartment lines only one line of which has been recognized, so that the lines erroneously match map information, still can secure safety in automatic operation.SOLUTION: The vehicle control device is provided with: a recognizing part that recognizes road compartment lines extending in a travelling direction of a vehicle; a determining part that determines whether the recognized road compartment lines match map road compartment lines based on map information stored in a storing part, and when only one line of the road compartment lines is recognized, determines whether the recognized one line of the road compartment lines matches one line of the map road compartment lines; a correcting part that when it is determined that the recognized one line of the road compartment lines matches the one line of the map road compartment lines, corrects the one line of the map road compartment lines, on the basis of the recognized one line of the road compartment lines; and a control part that controls running of the vehicle.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a vehicle control device, a vehicle control method, and a program. [Background technology]

[0002] In recent years, efforts to provide access to sustainable transportation systems that take into consideration vulnerable transport participants have become more active. To achieve this, we are focusing on research and development into autonomous driving technology to further improve traffic safety and convenience.

[0003] Incidentally, in autonomous driving technology, a match between road dividing lines recognized from a camera image and road dividing lines recognized from map information is confirmed, a target trajectory of the vehicle is generated based on the matching road dividing lines on both sides or one side, and autonomous driving or driving assistance is performed along the generated target trajectory. For example, Patent Document 1 discloses that if a road dividing line recognized from a camera image exists on only one side and the road dividing line matches the map information, autonomous driving of the vehicle continues. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2022-185787 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the conventional technology, even if the road dividing line recognized on only one side contains an error and is mismatched with the map information, the autonomous driving of the host vehicle continues based on the mismatched road dividing line or map information. As a result, a lateral error occurs in the host vehicle's own position determined based on the mismatched road dividing line or map information, and the host vehicle may be shaken laterally, for example, which may impair the stability of the autonomous driving.

[0006] The present invention has been made in consideration of the above circumstances, and an object of the present invention is to provide a vehicle control device, a vehicle control method, and a program that can ensure the stability of automated driving even when road lane markings recognized on only one side contain an error and are mismatched with map information, thereby contributing to the development of sustainable transportation systems. [Means for solving the problem]

[0007] The vehicle control device according to the present invention employs the following configuration. (1) A vehicle control device according to one aspect of the present invention includes a recognition unit that recognizes road dividing lines present in the traveling direction of a vehicle, a determination unit that determines whether the recognized road dividing lines match map road dividing lines based on map information stored in a storage unit, and, if the road dividing lines are recognized on only one side, determines whether the recognized road dividing lines on the one side match the map road dividing lines on the one side, a correction unit that, if it is determined that the recognized road dividing lines on the one side match the map road dividing lines on the one side, corrects the map road dividing lines on the one side based on the recognized road dividing lines on the one side, and a driving control unit for the vehicle. and a control unit that performs the above-mentioned steps, wherein the control unit calculates a first self-position of the vehicle based on the map road dividing lines on one side before correction based on the driving state of the vehicle, and calculates a second self-position of the vehicle based on the map road dividing lines on one side after correction or the recognized road dividing lines on one side, and when an error between the first self-position and the second self-position is equal to or greater than a first threshold, controls driving of the vehicle so that the vehicle travels at a position based on the map road dividing lines on one side before correction or a position based on the map road dividing lines on one side after re-correction that is offset from the recognized road dividing lines on one side toward the map road dividing lines on one side before correction.

[0008] (2) In the above aspect (1), the position based on the pre-correction map road dividing lines is a position that exists between a plurality of map road dividing lines.

[0009] (3): In the above aspect (1), the position based on the pre-correction map road dividing lines is a future position predicted from the driving conditions when the vehicle was driving based on the pre-correction map road dividing lines.

[0010] (4): In the above aspect (1), the position based on the pre-correction map road dividing lines is a position between a plurality of map road dividing lines corrected by a future position predicted from the driving state when the vehicle was driving based on the pre-correction map road dividing lines.

[0011] (5): In the above aspect (1), when the error between the first self-position and the second self-position calculated multiple times is equal to or greater than a first threshold value, and any of the errors calculated multiple times is equal to or greater than a second threshold value, the control unit controls the vehicle's driving so that the vehicle drives at a position based on the map road dividing line before correction.

[0012] (6): In the above aspect (1), the control unit stops the driving control when the state in which the vehicle is controlled to travel at a position based on the map road dividing lines before correction continues for a predetermined period of time.

[0013] (7) In another aspect of the present invention, a vehicle control method includes a computer mounted on a vehicle that recognizes road dividing lines present in a direction of travel of the vehicle, determines whether the recognized road dividing lines match map road dividing lines based on map information stored in a storage unit, and, if the road dividing lines are recognized only on one side, determines whether the recognized road dividing lines on that side match map road dividing lines on that side, and, if it is determined that the recognized road dividing lines on that side match map road dividing lines on that side, corrects the map road dividing lines on that side based on the recognized road dividing lines on that side, and The vehicle is controlled to travel, and a first self-position of the vehicle is calculated based on the map road dividing lines on one side before correction based on the driving state of the vehicle, and a second self-position of the vehicle is calculated based on the map road dividing lines on one side after correction or the recognized road dividing lines on one side, and if the error between the first self-position and the second self-position is equal to or greater than a first threshold, the vehicle is controlled to travel at a position based on the map road dividing lines on one side before correction or a position based on the map road dividing lines on one side after recorrection which is offset from the recognized road dividing lines on one side toward the map road dividing lines on one side before correction.

[0014] (8) A program according to another aspect of the present invention causes a computer mounted on a vehicle to recognize road dividing lines present in the direction of travel of the vehicle, determine whether the recognized road dividing lines match map road dividing lines based on map information stored in a storage unit, and, if the road dividing lines are recognized on only one side, determine whether the recognized road dividing lines on that side match map road dividing lines on that side, and, if it is determined that the recognized road dividing lines on that side match map road dividing lines on that side, correct the map road dividing lines on that side based on the recognized road dividing lines on that side, and The vehicle is controlled to travel, and a first self-position of the vehicle is calculated based on the map road dividing lines on one side before correction based on the driving state of the vehicle, and a second self-position of the vehicle is calculated based on the map road dividing lines on one side after correction or the recognized road dividing lines on one side, and if the error between the first self-position and the second self-position is equal to or greater than a first threshold, the vehicle is controlled to travel at a position based on the map road dividing lines on one side before correction or a position based on the map road dividing lines on one side after recorrection which is offset from the recognized road dividing lines on one side toward the map road dividing lines on one side before correction. [Effects of the Invention]

[0015] According to the above aspects (1) to (8), even if there is an error in the road dividing line recognized on only one side and it is mismatched with the map information, the stability of automated driving can be ensured. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a configuration diagram of a vehicle system using a vehicle control device according to an embodiment. [Figure 2] FIG. 2 is a functional configuration diagram of a first control unit and a second control unit. [Figure 3] FIG. 2 is a diagram illustrating an example of a correspondence relationship between a driving mode, a control state of a host vehicle, and a task. [Figure 4]FIG. 10 is a diagram showing an example of the rolling of the host vehicle that occurs when the map road dividing line is corrected to match the other camera road dividing line that has been erroneously recognized. [Figure 5] 10A and 10B are diagrams for explaining calculation of a first self-location and a second self-location, and determination based on the calculated first self-location and second self-location. [Figure 6] 10 is a diagram for explaining a method of calculating a position based on a map road-dividing line ML before correction using odometry information. FIG. [Figure 7] 3 is a flowchart showing an example of the flow of processing executed by the automatic driving control device 100. DETAILED DESCRIPTION OF THE INVENTION

[0017] Hereinafter, embodiments of a vehicle control device, a vehicle control method, and a program according to the present invention will be described with reference to the drawings.

[0018] [Overall configuration] 1 is a configuration diagram of a vehicle system 1 that uses a vehicle control device according to an embodiment. The vehicle on which the vehicle system 1 is mounted may be, for example, a two-wheeled, three-wheeled, or four-wheeled vehicle, and its drive source may be an internal combustion engine such as a diesel engine or a gasoline engine, an electric motor, or a combination of these. The electric motor operates using power generated by a generator connected to the internal combustion engine, or discharged power from a secondary battery or a fuel cell.

[0019] The vehicle system 1 includes, for example, a camera 10, a radar device 12, a LIDAR (Light Detection and Ranging) 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 monitor camera 70, a driving operator 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 connected to each other via multiplexed communication lines such as a CAN (Controller Area Network) communication line, serial communication lines, a wireless communication network, etc. Note that the configuration shown in FIG. 1 is merely an example, and some of the configuration may be omitted, or other configurations may be added.

[0020] The camera 10 is, for example, a digital camera using a solid-state imaging element such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor). The camera 10 is attached to any location of a vehicle (hereinafter referred to as the host vehicle M) in which the vehicle system 1 is installed. When capturing an image of the front, the camera 10 is attached to the top of the front windshield, the back of the rearview mirror, or the like. The camera 10, for example, periodically and repeatedly captures images of the surroundings of the host vehicle M. The camera 10 may be a stereo camera.

[0021] The radar device 12 emits radio waves such as millimeter waves around the vehicle M and detects radio waves reflected by an object (reflected waves) to detect at least the position (distance and direction) of the object. The radar device 12 is attached to any location on the vehicle M. The radar device 12 may detect the position and speed of an object using an FM-CW (Frequency Modulated Continuous Wave) method.

[0022] The LIDAR 14 irradiates the surroundings of the vehicle M with light (or electromagnetic waves with wavelengths similar to light) and measures the scattered light. The LIDAR 14 detects the distance to the target based on the time between light emission and light reception. The irradiated light is, for example, pulsed laser light. The LIDAR 14 is attached to any location on the vehicle M.

[0023] The object recognition device 16 performs sensor fusion processing on the detection results from some or all of the camera 10, the radar device 12, and the LIDAR 14 to recognize 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 may output the detection results from the camera 10, the radar device 12, and the LIDAR 14 directly to the automatic driving control device 100. The object recognition device 16 may be omitted from the vehicle system 1.

[0024] The communication device 20 communicates with other vehicles in the vicinity of the vehicle M, for example, using a cellular network, a Wi-Fi network, Bluetooth (registered trademark), DSRC (Dedicated Short Range Communication), etc., or communicates with various server devices via a wireless base station.

[0025] The HMI 30 presents various information to the occupants of the vehicle M and accepts input operations by the occupants. The HMI 30 includes various display devices, a speaker, a buzzer, a touch panel, switches, keys, and the like.

[0026] The vehicle sensor 40 includes a vehicle speed sensor that detects the speed of the host vehicle M, an acceleration sensor that detects acceleration, a yaw rate sensor that detects angular velocity around a vertical axis, a direction sensor that detects the direction of the host vehicle M, and the like.

[0027] 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 a hard disk drive (HDD) or flash memory. The GNSS receiver 51 identifies the position of the vehicle M based on signals received from GNSS satellites. The position of the vehicle M may be identified or supplemented by an inertial navigation system (INS) that uses the output of the vehicle sensors 40. The navigation HMI 52 includes a display device, a speaker, a touch panel, keys, etc. The navigation HMI 52 may share some or all of the components with the HMI 30 described above. The route determination unit 53 determines, for example, a route (hereinafter, a map route) from the position of the vehicle M identified by the GNSS receiver 51 (or any input position) to a destination input by the occupant using the navigation HMI 52, with reference to the first map information 54. The first map information 54 is information that represents road shapes using, for example, links indicating roads and nodes connected by the links. The first map information 54 may also include information such as road curvature and POI (Point of Interest) information. The route on the map is output to the MPU 60. The navigation device 50 may provide route guidance using the navigation HMI 52 based on the route on the map. The navigation device 50 may be realized, for example, by the functions of a terminal device such as a smartphone or tablet device owned by the occupant. The navigation device 50 may transmit the current position 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.

[0028] The MPU 60 includes, for example, a recommended lane determination unit 61, and stores second map information 62 in a storage device such as an HDD or flash memory. 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, by dividing it into 100 m intervals in the vehicle 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, for example, which lane from the left the vehicle should travel in. When there is a branch point on the route on the map, the recommended lane determination unit 61 determines a recommended lane so that the vehicle M can travel on a reasonable route to the branch point.

[0029] 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 on the centers of lanes or information on lane boundaries. The second map information 62 may also include road information, traffic regulation information, address information (address and postal code), facility information, telephone number information, information on prohibited sections where mode A or mode B, described below, is prohibited, and the like. The second map information 62 may be updated as needed by the communication device 20 communicating with another device.

[0030] The driver monitor camera 70 is, for example, a digital camera that uses a solid-state imaging element such as a CCD or CMOS. The driver monitor camera 70 is attached to any location on the vehicle M in a position and orientation that allows it to capture an image of the head of an occupant (hereinafter, driver) seated in the driver's seat of the vehicle M from the front (in an orientation that captures an image of the face). For example, the driver monitor camera 70 is attached to the top of a display device provided in the center of the instrument panel of the vehicle M.

[0031] The driving operators 80 include, for example, a steering wheel 82, an accelerator pedal, a brake pedal, a shift lever, and other operators. The driving operators 80 are equipped with sensors that detect the amount of operation or the presence or absence of operation, and the detection results are output to the automatic driving control device 100 or some or all of the driving force output device 200, the brake device 210, and the steering device 220. The steering wheel 82 is an example of an "operator that accepts steering operation by the driver." The operator does not necessarily have to be annular and may be in the form of an irregular steering wheel, a joystick, a button, or the like. A steering grip sensor 84 is attached to the steering wheel 82. The steering grip sensor 84 is realized by a capacitance sensor or the like, and outputs a signal to the automatic driving control device 100 that can detect whether the driver is gripping the steering wheel 82 (meaning that the driver is in contact with the steering wheel in a state where force can be applied).

[0032] 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 each realized by, for example, a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Some or all of these components may be realized by hardware (including circuitry) such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing Unit), or an SOC (System On Chip), or may be realized by a combination of software and hardware. The program may be stored in advance in a storage device (a storage device having a non-transitory storage medium) such as a HDD or flash memory of the automatic driving control device 100, or may 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 inserting the storage medium (non-transitory storage medium) into a drive device. The automatic driving control device 100 including the determination unit 132 and the correction unit 134 described below is an example of a "vehicle control device."

[0033] FIG. 2 is a functional configuration diagram of the first control unit 120 and the second control unit 160. The first control unit 120 includes, for example, a recognition unit 130, a determination unit 132, an action plan generation unit 140, and a mode determination unit 150. The first control unit 120, for example, implements functions based on AI (Artificial Intelligence) and functions based on a predefined model in parallel. For example, the function of "recognizing intersections" may be implemented by executing intersection recognition using deep learning or the like and recognition based on predefined conditions (such as traffic lights and road markings that can be pattern-matched) in parallel, and then scoring and comprehensively evaluating both. This ensures the reliability of autonomous driving.

[0034] The recognition unit 130 recognizes the position, speed, acceleration, and other states of objects around the vehicle M based on information input from the camera 10, the radar device 12, and the LIDAR 14 via the object recognition device 16. The position of an object is recognized as a position on an absolute coordinate system with a representative point of the vehicle M (such as the center of gravity or the center of the drive shaft) as the origin, and is used for control. The position of an object may be represented by a representative point such as the center of gravity or a corner of the object, or may be represented by an area. The "state" of an object may include the acceleration or jerk of the object, or the "behavioral state" (for example, whether the object is changing lanes or is about to change lanes).

[0035] The recognition unit 130 also recognizes, for example, the lane in which the host vehicle M is traveling (driving lane). For example, the recognition unit 130 recognizes the driving lane by comparing a pattern of road dividing lines obtained from the second map information 62 (hereinafter, sometimes referred to as "map road dividing lines") with a pattern of road dividing lines around the host vehicle M recognized from an image captured by the camera 10 (hereinafter, sometimes referred to as "camera road dividing lines"). More specifically, the determination unit 132 of the recognition unit 130 calculates, for example, the deviation between the map road dividing lines and the camera road dividing lines, and if it determines that the calculated deviation is equal to or less than a threshold (i.e., if it determines that there is a match), it recognizes at least one of the map road dividing lines and the camera road dividing lines (or their medians, etc.) as the driving lane. Note that the recognition unit 130 may recognize driving lanes by recognizing road boundaries (road boundaries) including not only road dividing lines but also road dividing lines, shoulders, curbs, medians, guardrails, etc. This recognition may take into account the position of the vehicle M obtained from the navigation device 50 and the processing results by the INS. The recognition unit 130 also recognizes stop lines, obstacles, red lights, toll booths, and other road phenomena.

[0036] When recognizing the driving lane, the recognition unit 130 recognizes the position and attitude of the host vehicle M with respect to the driving lane. For example, the recognition unit 130 may recognize the deviation of the reference point of the host vehicle M from the center of the lane and the angle it forms with a line connecting the centers of the lanes in the traveling direction of the host vehicle M as the relative position and attitude of the host vehicle M with respect to the driving lane. Alternatively, the recognition unit 130 may recognize the position of the reference point of the host vehicle M with respect to either side edge of the driving lane (a road dividing line or a road boundary) as the relative position of the host vehicle M with respect to the driving lane.

[0037] If the correction unit 134 of the recognition unit 130 determines that the map road dividing line and the camera road dividing line match, it corrects the map road dividing line to match the recognized camera road dividing line (in other words, it corrects the position of the host vehicle M on the second map information 62). More specifically, the correction unit 134 first identifies the position of the host vehicle M (including, for example, the distance and the orientation of the host vehicle M) based on the recognized camera road dividing line from the camera image. Because it is determined that the map road dividing line and the camera road dividing line match, the correction unit 134 equates the map road dividing line with the camera road dividing line and identifies the position of the host vehicle M based on the camera road dividing line as the position of the host vehicle M based on the map road dividing line (for example, a position in GNSS coordinates). As a result, the correction unit 134 can correct and determine the position of the host vehicle M based on the identified map road dividing line as the position of the host vehicle M on the second map information 62.

[0038] The behavior plan generation unit 140 automatically (without driver input) generates a target trajectory for the host vehicle M to travel in the recommended lane determined by the recommended lane determination unit 61, and to avoid approaching any objects recognized by the recognition unit 130 (excluding objects that can be overcome, such as road dividing lines, road markings, and manholes). For example, the recognition unit 130 sets a risk area centered on the object whose status has been output, and within the risk area, the recognition unit 130 sets a risk as an index value indicating the degree to which the host vehicle M should not approach. The behavior plan generation unit 140 generates a target trajectory for the host vehicle M to avoid passing through points where the risk is equal to or greater than a predetermined value and to travel within the recognized travel lane. Because some objects are moving, the risk distribution is not one per control cycle, but is set for multiple future time points, taking into account the future position of the object predicted based on the object's speed. For example, the target trajectory is expressed as a sequential list of points (trajectory points) to be reached by the host vehicle M. The trajectory points are points that the host vehicle M should reach at every predetermined travel distance (for example, about several meters) along the road, and separately, the target speed and target acceleration are generated as part of the target trajectory at every predetermined sampling time (for example, about a few tenths of a second). The trajectory points may also be positions that the host vehicle M should reach at every predetermined sampling time. In this case, the information on the target speed and target acceleration is expressed as the interval between the trajectory points.

[0039] Furthermore, in this embodiment, when the determination unit 132 determines that the map road dividing line and the camera road dividing line match on at least one side, the behavior plan generation unit 140 generates a target trajectory for the host vehicle M to travel along (at least taking into consideration) the matched map road dividing line and camera road dividing line. As an example, the behavior plan generation unit 140 generates a target trajectory for traveling at a point shifted a predetermined distance from the matched map road dividing line and camera road dividing line.

[0040] The behavior plan generation unit 140 may set an autonomous driving event when generating the target trajectory. The autonomous driving events include a constant speed driving event, a low-speed following driving event, a lane change event, a branching event, a merging event, a takeover event, etc. The behavior plan generation unit 140 generates a target trajectory according to the activated event.

[0041] The mode determination unit 150 determines the driving mode of the host vehicle M to be one of a plurality of driving modes that assign different tasks to the driver. FIG. 3 is a diagram showing an example of the correspondence between the driving modes, the control state of the host vehicle M, and the tasks. The driving modes of the host vehicle M include, for example, five modes, Mode A to Mode E. The control state, i.e., the degree of automation of the driving control of the host vehicle M, is Mode A, which is the highest, followed by Mode B, Mode C, and Mode D, with Mode E being the lowest. Conversely, the tasks assigned to the driver are Mode A, which is the lightest, followed by Mode B, Mode C, and Mode D, with Mode E being the most severe. Note that Modes D and E are non-autonomous driving control states, and therefore the autonomous driving control device 100 is responsible for terminating control related to autonomous driving and transitioning to driving assistance or manual driving. The contents of each driving mode are exemplified below.

[0042] In Mode A, the vehicle is in an autonomous driving state, and the driver is not required to monitor the road ahead or grip the steering wheel 82 (in the figure, gripping the steering wheel). However, even in Mode A, the driver is required to be in a position where he or she can quickly switch to manual driving in response to a request from a system centered on the automatic driving control device 100. Note that, as used herein, "automatic driving" refers to control of both steering and acceleration / deceleration without driver input. "Ahead" refers to the space in the direction of travel of the host vehicle M, as viewed through the front windshield. Mode A is a driving mode that can be implemented, for example, on a motorway such as an expressway, when certain conditions are met, such as the host vehicle M traveling at a predetermined speed (e.g., approximately 50 km / h) or less and there is a vehicle ahead to be followed, and is sometimes referred to as TJP (Traffic Jam Pilot). If these conditions are no longer met, the mode determination unit 150 changes the driving mode of the host vehicle M to Mode B.

[0043] In mode B, the vehicle is in a driving assistance state, and the driver is tasked with monitoring the area ahead of the vehicle M (hereinafter referred to as forward monitoring), but is not tasked with holding the steering wheel 82. In mode C, the vehicle is in a driving assistance state, and the driver is tasked with monitoring the area ahead and holding the steering wheel 82. Mode D is a driving mode that requires some degree of driver operation for at least one of steering and acceleration / deceleration of the vehicle M. For example, in mode D, driving assistance such as ACC (Adaptive Cruise Control) and LKAS (Lane Keeping Assist System) is provided. Mode E is a manual driving state in which the driver must perform both steering and acceleration / deceleration operations. In both mode D and mode E, the driver is naturally tasked with monitoring the area ahead of the vehicle M.

[0044] The driving modes are not limited to those illustrated in FIG. 3 and may be defined by other definitions. For example, among driving modes that require both forward monitoring and gripping the steering wheel, there may be driving modes with lenient thresholds for determining that the steering wheel is being gripped and driving modes with stricter thresholds. More specifically, driving modes may be defined such that in one driving mode, it is sufficient for the driver to have either the left or right hand touching the steering wheel 82, while in another driving mode that imposes a heavier task on the driver, the driver must grip the steering wheel 82 with both hands with a strength equal to or greater than a threshold. Driving modes that differ in the severity of the tasks imposed on the driver may be defined in any other way.

[0045] The automatic driving control device 100 (and the driving assistance device (not shown)) executes an automated lane change according to the driving mode. There are two types of automated lane changes: a system-requested automated lane change (1) and a driver-requested automated lane change (2). The automated lane change (1) is an automated lane change for overtaking, which is performed when the speed of the vehicle ahead is slower than the speed of the vehicle itself by a standard or more, and an automated lane change for proceeding toward the destination (an automated lane change due to a change in the recommended lane). The automated lane change (2) is a lane change in which, when conditions related to the speed and the positional relationship with surrounding vehicles are met and the driver operates the turn signal, the vehicle M changes lanes in the direction of the operation.

[0046] In mode A, the automatic driving control device 100 does not perform either automated lane change (1) or (2). In modes B and C, the automatic driving control device 100 performs either automated lane change (1) or (2). In mode D, the driving assistance device (not shown) does not perform automated lane change (1), but performs automated lane change (2). In mode E, neither automated lane change (1) nor (2) is performed.

[0047] When the driver does not perform a task related to the determined driving mode (hereinafter, the current driving mode), the mode determination unit 150 changes the driving mode of the vehicle M to a driving mode with a more severe task.

[0048] For example, in mode A, if the driver is in a position where he or she cannot switch to manual driving in response to a request from the system (for example, if the driver continues to look away from the road outside the allowable area or if a sign of driving difficulty is detected), the mode determination unit 150 uses the HMI 30 to prompt the driver to switch to manual driving, and if the driver does not comply, the mode determination unit 150 performs control such as pulling the host vehicle M to the shoulder of the road and gradually stopping it, and stopping the automatic driving. After the automatic driving is stopped, the host vehicle enters a state of mode D or E, and the host vehicle M can be started by manual operation by the driver. The same applies below to "stopping automatic driving." In mode B, if the driver is not monitoring the road ahead, the mode determination unit 150 performs control such as prompting the driver to monitor the road ahead using the HMI 30, and if the driver does not comply, pulling the host vehicle M to the shoulder of the road and gradually stopping it, and stopping the automatic driving. In mode C, if the driver is not monitoring the road ahead or is not gripping the steering wheel 82, the mode determination unit 150 uses the HMI 30 to prompt the driver to monitor the road ahead and / or grip the steering wheel 82, and if the driver does not comply, the mode determination unit 150 controls the vehicle M to move to the shoulder of the road and gradually stop, thereby terminating automatic driving.

[0049] The mode determination unit 150 further monitors the driver's state for the above-mentioned mode change and determines whether the driver's state is appropriate for the task. For example, the mode determination unit 150 analyzes the image captured by the driver monitor camera 70 and performs posture estimation processing to determine whether the driver is in a position that prevents them from switching to manual driving in response to a request from the system. In addition, the driver state determination unit 152 analyzes the image captured by the driver monitor camera 70 and performs line-of-sight estimation processing to determine whether the driver is monitoring the road ahead.

[0050] Furthermore, in this embodiment, if the determination unit 132 determines that the map road dividing lines and the camera road dividing lines do not match on both sides, the mode determination unit 150 changes the driving mode of the host vehicle M to a driving mode with a more difficult task. For example, if the mode determination unit 150 determines that the map road dividing lines and the camera road dividing lines do not match on both sides while the host vehicle M is traveling in a driving mode (mode A or mode B) that does not require gripping the steering wheel, the mode determination unit 150 changes the driving mode to mode C or a lower mode.

[0051] The mode determination unit 150 further performs various processes for changing the mode. For example, the mode determination unit 150 instructs the action plan generation unit 140 to generate a target trajectory for stopping on the shoulder of the road, instructs a driving assistance device (not shown) to operate, and controls the HMI 30 to prompt the driver to take action.

[0052] The second control unit 160 controls the traveling 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 the scheduled time.

[0053] Returning to FIG. 2, 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 information on the target trajectory (trajectory points) 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 brake device 210 based on a speed element associated with the target trajectory stored in the memory. The steering control unit 166 controls the steering device 220 according to the curvature of the target trajectory stored in the memory. The processing of the speed control unit 164 and the steering control unit 166 is realized by, for example, a combination of feedforward control and feedback control. As an example, the steering control unit 166 executes a combination of feedforward control according to the curvature of the road ahead of the host vehicle M and feedback control based on the deviation from the target trajectory.

[0054] The driving force output device 200 outputs a driving force (torque) for the vehicle to travel to the drive wheels. The driving force output device 200 includes, for example, a combination of an internal combustion engine, an electric motor, a transmission, etc., and an ECU (Electronic Control Unit) that controls these. The ECU controls the above components according to information input from the second control unit 160 or information input from the driving operator 80.

[0055] Braking device 210 may include, for example, a brake caliper, a cylinder that transmits hydraulic pressure to the brake caliper, an electric motor that generates hydraulic pressure in the cylinder, and a brake ECU. The brake ECU controls the electric motor according to information input from second control unit 160 or information input from driving operation device 80, so that a brake torque corresponding to the braking operation is output to each wheel. Braking device 210 may include a backup mechanism that transmits hydraulic pressure generated by operation of a brake pedal included in driving operation device 80 to the cylinder via a master cylinder. Note that braking device 210 is not limited to the configuration described above, and may also be an electronically controlled hydraulic brake device that controls an actuator according to information input from second control unit 160 to transmit hydraulic pressure from a master cylinder to the cylinder.

[0056] The steering device 220 includes, for example, a steering ECU and an electric motor. The electric motor applies a force to a rack and pinion mechanism to change the direction of the steered wheels. The steering ECU drives the electric motor in accordance with information input from the second control unit 160 or information input from the driving operator 80 to change the direction of the steered wheels.

[0057] [Processing when one side is lost and the other side is matched] As described above, the determination unit 132 compares the map road division lines and the camera road division lines on both sides. If the determination unit 132 determines that the map road division lines and the camera road division lines match for at least one side, the action plan generation unit 140 generates a target trajectory for the host vehicle M to travel along the matched map road division lines and camera road division lines. However, for example, if recognition of one camera road division line fails (is lost) while the other camera road division line is misrecognized (e.g., a road curb is misrecognized as a camera road division line), and the map road division line matches the other camera road division line where the misrecognition occurred, the correction unit 134 corrects the map road division line to match the other camera road division line where the misrecognition occurred. As a result, the host vehicle M traveling along the other camera road division line or map road division line may experience lateral sway, which may impair the stability of autonomous driving or driving assistance.

[0058] 4 is a diagram showing an example of lateral sway of the host vehicle M caused by correcting a map road-dividing line to match the other camera road-dividing line that has been erroneously recognized. In the left part of FIG. 4, the symbol CL represents the camera road-dividing line, the symbol ML represents the map road-dividing line before correction, the symbol AL represents the actual road-dividing line, and the symbol TL represents the target trajectory generated by the behavior plan generation unit 140. The left part of FIG. 4 shows a situation in which the determination unit 132 determines that the map road-dividing line ML and the camera road-dividing line CL match on both sides.

[0059] Then, as shown in the right part of Figure 4, assume that the left camera road dividing line CL is lost and simultaneously an erroneous recognition occurs for the right camera road dividing line CL (hereinafter, the erroneously recognized camera road dividing line may be referred to as CL'), and the erroneously recognized camera road dividing line CL' coincides with the map road dividing line ML. In this case, as described above, the correction unit 134 corrects the map road dividing line ML so that it matches the recognized camera road dividing line CL', thereby obtaining the corrected map road dividing line ML'. As a result, the corrected map road dividing line ML' shifts toward the camera road dividing line CL' (shifted to the right in Figure 4) compared to the map road dividing line ML before correction. As a result, the action plan generation unit 140 also shifts the target trajectory TL to obtain the shifted target trajectory TL'. Because the target trajectory TL' has shifted laterally compared to the target trajectory TL, lateral sway occurs in the host vehicle M traveling autonomously or in a driving-assisted manner.

[0060] To prevent lateral shaking due to the above-described events, the behavior plan generation unit 140 according to this embodiment compares a first self-position calculated based on the pre-correction map road-dividing lines and odometry information of the host vehicle M with a second self-position calculated based on the post-correction map road-dividing lines or the recognized camera road-dividing lines when one of the camera road-dividing lines is lost while the other camera road-dividing lines match the map road-dividing lines (hereinafter simply referred to as "one-side lost, one-side match"). Here, the odometry information is, for example, information indicating parameters such as the acceleration, wheel speed, and orientation of the host vehicle M, or information indicating the future position of the host vehicle M predicted from these parameters. The odometry information is an example of a "driving state" in the claims. When the error between the first self-position and the second self-position is equal to or greater than a first threshold th1, the behavior plan generation unit 140 generates a target trajectory TL so that the vehicle travels along a position based on the pre-correction map road-dividing lines. This is because if the error between the first self-position and the second self-position is large, it is assumed that there is a high possibility that an error has occurred in the camera road dividing line (or the corrected map road dividing line) that was used to calculate the second self-position.

[0061] 5 is a diagram for explaining the calculation of the first self-location and the second self-location, and the determination based on the calculated first self-location and the second self-location. The left part of FIG. 5 shows, as an example, a situation in which the camera road-dividing line and the map road-dividing line matched on both sides at time t, but one-side lost and one-side match occurred at time t+1.

[0062] As shown in FIG. 5, when a one-side lost, one-side match occurs, the behavior plan generation unit 140 first calculates the self-position P(t+1)_odo of the host vehicle M at time t+1 as the first self-position, using the odometry information at time t, starting from the position P(t) of the host vehicle M relative to the uncorrected map road dividing line ML. At the same time, the behavior plan generation unit 140 calculates the self-position P(t+1)_yrm of the host vehicle M relative to the matched camera road dividing line CL on one side or the corrected map road dividing line ML' as the second self-position. At this time, the correction unit 134 may correct the self-position by applying a complementary filter, calculating a median, weighting, or other processing to the calculated first self-position P(t+1)_odo and second self-position P(t+1)_yrm, and recognize the corrected self-position as the final self-position P(t)_lm.

[0063] Next, the behavior plan generation unit 140 calculates the error d between the calculated first self-position P(t+1)_odo and the second self-position P(t+1)_yrm and determines whether the calculated error d is equal to or greater than the first threshold th1. If it is determined that the calculated error d is equal to or greater than the first threshold th1, as shown in the right part of FIG. 5 , the behavior plan generation unit 140 generates a target trajectory TL so that the host vehicle M travels along a position based on the pre-correction map road dividing lines ML without using the recognized camera road dividing lines CL on one side or the corrected map road dividing lines ML′. The second control unit 160 controls the host vehicle M to travel along the generated target trajectory TL. Here, the position based on the pre-correction map road dividing lines ML refers to a position calculated based on at least one of the map road dividing lines ML on both sides. In FIG. 5 , as an example, the behavior plan generation unit 140 generates the target trajectory TL based on the midline of the map road dividing lines ML on both sides.

[0064] Furthermore, as another example, the behavior plan generating unit 140 may calculate the target trajectory TL using odometry information. Fig. 6 is a diagram for explaining a method for calculating the target trajectory TL using odometry information. In Fig. 6, the symbol TL pr represents the target trajectory in the control cycle immediately before the occurrence of one-side lost one-side match, and symbol OD represents the odometry information of the host vehicle M in the control cycle immediately before the occurrence of one-side lost one-side match. As shown in Fig. 6, the behavior plan generation unit 140 predicts the future position of the host vehicle M based on the odometry information OD, and generates the target trajectory TL pr For example, the behavior plan generating unit 140 may calculate the final target trajectory TL by correcting the trajectory of the predicted future position and the target trajectory TL pr Alternatively, the behavior plan generating unit 140 may determine the trajectory of the future position along which the host vehicle M will travel as the target trajectory TL based on the odometry information OD.

[0065] In this way, when a one-side lost one-side match occurs and it is determined that the error d between the first self-position and the second self-position is equal to or greater than the first threshold th1, the behavior plan generation unit 140 generates a target trajectory TL as a position based on the map road dividing line ML immediately before the one-side lost one-side match occurred, and continues autonomous driving or driving assistance of the host vehicle M. Thereafter, if the one-side lost one-side match remains unresolved after a predetermined period of time has elapsed or after the host vehicle M has traveled a predetermined distance, the mode determination unit 150 changes the driving mode of the host vehicle M to a driving mode with a more complex task. On the other hand, when the one-side lost one-side match is resolved, for example, when the map road dividing line ML and the camera road dividing line CL match on both sides, the mode determination unit 150 maintains the driving mode of the host vehicle M.

[0066] In the above description, for simplicity, the behavior plan generating unit 140 calculates the first self-location and the second self-location only once and determines whether the error d between the first self-location and the second self-location is equal to or greater than the first threshold value th1. However, in practice, to more reliably determine the error and stabilize the control, the behavior plan generating unit 140 calculates the first self-location and the second self-location multiple times over multiple control cycles. If the error d between the first self-location and the second self-location calculated multiple times is consecutively equal to or greater than the first threshold value th1 and any of the errors d calculated multiple times is equal to or greater than the second threshold value th2, the behavior plan generating unit 140 generates a target trajectory TL so that the vehicle travels along a position based on the uncorrected map road dividing line ML. Here, the second threshold value th2 is a predetermined value greater than the first threshold value th1. Alternatively, the behavior plan generation unit 140 may generate a target trajectory TL to travel along a position based on the map road dividing line ML before correction when the error d between the first self-position and the second self-position calculated multiple times is consecutively greater than or equal to a first threshold value th1, or when any of the errors d calculated multiple times is greater than or equal to a second threshold value th2.

[0067] Furthermore, in the above description, when a one-side-lost, one-side-match event occurs and it is determined that the error d between the first self-location and the second self-location is equal to or greater than the first threshold th1, the behavior plan generation unit 140 generates the target trajectory TL so that the vehicle travels along a position based on the pre-correction map road dividing line ML. However, the present invention is not limited to this configuration. The behavior plan generation unit 140 may also generate the target trajectory TL so that the vehicle travels along a position based on the post-correction map road dividing line ML'. In this case, for example, instead of the post-correction map road dividing line ML' that perfectly matches the matched camera road dividing line, the behavior plan generation unit 140 may set a further post-correction map road dividing line ML'' between the pre-correction map road dividing line ML and the post-correction map road dividing line ML' that perfectly matches the matched camera road dividing line, and the behavior plan generation unit 140 may generate the target trajectory TL along the map road dividing line ML''. In other words, the map road dividing line ML'' can also be expressed as a map road dividing line that is offset from the pre-correction map road dividing line ML toward the matched camera road dividing line without matching. The map road dividing line ML'' is an example of a "map road dividing line on one side after recorrection" in the claims.

[0068] Next, the flow of processing executed by the automatic driving control device 100 will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of the flow of processing executed by the automatic driving control device 100. The processing of the flowchart shown in Fig. 7 is repeatedly executed while the host vehicle M is traveling in automatic driving (mode A) or driving assistance (mode B), for example.

[0069] First, the recognition unit 130 recognizes the camera road-dividing line CL based on the image captured by the camera 10 (step S100). Next, the determination unit 132 compares the camera road-dividing line with the map road-dividing line and determines whether a one-side-lost, one-side match has occurred (step S102). If it is determined that a one-side-lost, one-side match has not occurred, the automatic driving control device 100 returns the process to step S100.

[0070] On the other hand, if it is determined that one-side-lost, one-side-match has occurred, the correction unit 134 corrects the map road dividing line so that it matches the matched camera road dividing line (step S104). Next, the behavior plan generation unit 140 calculates a first self-position based on the map road dividing line before correction and the odometry information of the host vehicle M in the control cycle immediately before the one-side-lost, one-side-match occurred (step S106). Next, the behavior plan generation unit 140 calculates a second self-position based on the corrected map road dividing line (step S108).

[0071] Next, the behavior plan generator 140 determines whether the errors between the first self-location and the second self-location calculated over multiple control cycles are equal to or greater than a first threshold value th1 and whether any of the errors is equal to or greater than a second threshold value th2 (step S110). If it is determined that the errors between the first self-location and the second self-location calculated over multiple control cycles are not equal to or greater than the first threshold value th1 or that none of the errors is equal to or greater than the second threshold value th2, the automatic driving control device 100 returns the process to step S100.

[0072] On the other hand, if it is determined that the error between the first self-location and the second self-location calculated over multiple control cycles is equal to or greater than the first threshold th1 and that one of the errors is equal to or greater than the second threshold th2, the behavior plan generation unit 140 generates a target trajectory based on the map road dividing lines before correction (step S112).Next, the mode determination unit 150 determines whether the one-side lost one-side match condition has been resolved after a predetermined period of time (step S114).

[0073] If it is determined that the one-side lost, one-side match condition has been resolved after a predetermined period of time, the mode determination unit 150 continues the driving mode of mode A or mode B and performs normal target trajectory generation (step S116). On the other hand, if it is determined that the one-side lost, one-side match condition has not been resolved after a predetermined period of time, the mode determination unit 150 changes the driving mode to a driving mode with a more severe task (step S118). This ends the processing of this flowchart.

[0074] In the flowchart of FIG. 7, in step S112, the behavior plan generation unit 140 generates the target trajectory based on the map road dividing lines before correction. However, as described above, the behavior plan generation unit 140 may generate the target trajectory based on the map road dividing lines after re-correction.

[0075] According to the present embodiment described above, if a one-side lost, one-side match occurs while the vehicle M is traveling in autonomous driving or driving assistance mode, a first self-position of the vehicle M is calculated based on the odometry information of the vehicle M and the matched map road dividing lines on one side, and a second self-position of the vehicle M is calculated based on the corrected map road dividing lines on one side or the recognized camera road dividing lines on one side. If the error between the first self-position and the second self-position is equal to or greater than a threshold, the vehicle M is controlled to travel at a position based on the uncorrected map road dividing lines. This ensures the stability of autonomous driving even if there is an error in the road dividing lines recognized on only one side, resulting in a mismatch with the map information.

[0076] The above-described embodiment can be expressed as follows. a storage device storing a program; a hardware processor; The hardware processor executes the program, Recognizes road markings in the direction of travel of the vehicle, determining whether the recognized road dividing line matches a map road dividing line based on map information stored in a storage unit, and if the road dividing line is recognized on only one side, determining whether the recognized road dividing line on that side matches a map road dividing line on that side; when it is determined that the recognized road dividing line on one side matches the map road dividing line on one side, correcting the map road dividing line on one side based on the recognized road dividing line on one side; Carrying out driving control of the vehicle, calculating a first self-position of the vehicle based on the map road dividing line on one side before correction based on a driving state of the vehicle, and calculating a second self-position of the vehicle based on the map road dividing line on one side after correction or the recognized map road dividing line on one side after correction based on the first self-position; and, when an error between the first self-position and the second self-position is equal to or greater than a first threshold, performing driving control of the vehicle so that the vehicle travels at a position based on the map road dividing line on one side before correction. Vehicle control device.

[0077] The above describes the form for carrying out the present invention using an embodiment, but the present invention is not limited to such an embodiment, and various modifications and substitutions can be made within the scope that does not deviate from the gist of the present invention. [Explanation of symbols]

[0078] 10 Camera 12 Radar equipment 14 LIDAR 16 Object recognition device 100 Automatic driving control device 120 First Control Section 130 Recognition part 132 Judgment section 134 Correction Unit 140 Action Plan Generation Unit 150 Mode determination unit 160 Second Control Section

Claims

1. a recognition unit that recognizes road dividing lines present in the traveling direction of the vehicle; a determination unit that determines whether the recognized road-dividing line matches a map road-dividing line based on map information stored in a storage unit, and, if the road-dividing line is recognized only on one side, determines whether the recognized road-dividing line on that side matches the map road-dividing line on that side; a correction unit that corrects the map road-delimiting line on one side based on the recognized road-delimiting line on one side when it is determined that the recognized road-delimiting line on one side matches the map road-delimiting line on one side; a control unit that controls the running of the vehicle, the control unit calculates a first self-position of the vehicle based on the map road dividing line on one side before correction based on a driving state of the vehicle, and calculates a second self-position of the vehicle based on the map road dividing line on one side after correction or the recognized road dividing line on one side, and when an error between the first self-position and the second self-position is equal to or greater than a first threshold, performs driving control of the vehicle so that the vehicle travels at a position based on the map road dividing line on one side before correction or a position based on the map road dividing line on one side after recorrection that is offset from the recognized road dividing line on one side toward the map road dividing line on one side before correction. Vehicle control device.

2. the position based on the uncorrected map road dividing lines is a position that exists between a plurality of map road dividing lines; The vehicle control device according to claim 1 .

3. the position based on the pre-correction map road dividing line is a future position predicted from the driving state when the vehicle was driving based on the pre-correction map road dividing line; The vehicle control device according to claim 1 .

4. the position based on the map road dividing lines before correction is a position that exists between a plurality of map road dividing lines and is corrected by a future position that is predicted from the traveling state when the vehicle was traveling based on the map road dividing lines before correction. The vehicle control device according to claim 1 .

5. when an error between the first self-position and the second self-position calculated a plurality of times is equal to or greater than a first threshold value and any error among the errors calculated a plurality of times is equal to or greater than a second threshold value, the control unit performs driving control of the vehicle so that the vehicle travels at a position based on the map road division lines before correction. The vehicle control device according to claim 1 .

6. the control unit stops the driving control when a state in which the driving control of the vehicle is being performed so that the vehicle travels at a position based on the map road division lines before the correction continues for a predetermined period of time. The vehicle control device according to claim 1 .

7. The vehicle's on-board computer Recognizes road markings in the direction of travel of the vehicle, determining whether the recognized road dividing line matches a map road dividing line based on map information stored in a storage unit, and if the road dividing line is recognized on only one side, determining whether the recognized road dividing line on that side matches a map road dividing line on that side; when it is determined that the recognized road dividing line on one side matches the map road dividing line on one side, correcting the map road dividing line on one side based on the recognized road dividing line on one side; Carrying out driving control of the vehicle, a first self-position of the vehicle based on the map road dividing line on one side before correction based on a driving state of the vehicle, and a second self-position of the vehicle based on the map road dividing line on one side after correction or the recognized road dividing line on one side, and when an error between the first self-position and the second self-position is equal to or greater than a first threshold, performing driving control of the vehicle so that the vehicle travels at a position based on the map road dividing line on one side before correction or a position based on the map road dividing line on one side after recorrection that is offset from the recognized road dividing line on one side toward the map road dividing line on one side before correction; Vehicle control method.

8. The vehicle's onboard computer Recognizes road dividing lines in the direction of travel of the vehicle, determining whether or not the recognized road dividing line matches a map road dividing line based on map information stored in a storage unit, and if the road dividing line is recognized only on one side, determining whether or not the recognized road dividing line on that side matches a map road dividing line on that side; when it is determined that the recognized road dividing line on one side matches the map road dividing line on one side, correcting the map road dividing line on one side based on the recognized road dividing line on one side; Controlling the running of the vehicle; a first self-position of the vehicle based on the map road dividing line on one side before correction based on the driving state of the vehicle, and a second self-position of the vehicle based on the map road dividing line on one side after correction or the recognized road dividing line on one side, and when an error between the first self-position and the second self-position is equal to or greater than a first threshold, driving control is performed on the vehicle so that the vehicle travels at a position based on the map road dividing line on one side before correction or a position based on the map road dividing line on one side after recorrection that is offset from the recognized road dividing line on one side toward the map road dividing line on one side before correction; program.

Images