Vehicle control device, vehicle control method, and program

Abstract

To provide a vehicle control device that can deal with occurrence of erroneous recognition of camera road compartment lines or of map road compartment lines, at a timing just before an own vehicle enters a curve road.SOLUTION: The vehicle control device is provided with: a recognizing part that recognizes road compartment lines extending in a travelling direction of a vehicle; and 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. When the vehicle approaches a curve road, the determining part determines whether the recognized road compartment lines match the map road compartment lines, over a range just before a reference point set in consideration of a switching point for the curve road, of a range of the road compartment lines recognized by the recognizing part.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 been gaining momentum. To achieve this, we are focusing on research and development into autonomous driving technology to further improve traffic safety and convenience.

[0003] In autonomous driving technology, road dividing lines recognized from camera images are confirmed to coincide with road dividing lines recognized from map information, and these are used to generate a target trajectory for the vehicle. However, a problem is that these road dividing lines are prone to misrecognition. To address this problem, for example, Patent Document 1 discloses a technique for restricting image recognition on the branching side when the vehicle is located in a branching road section. Furthermore, Patent Document 2 discloses a technique for integrating information on the actual boundary and the map boundary obtained from the recognition ranges in front and behind the vehicle while traveling on a curved road, if the continuity evaluation of the actual boundary and the map boundary is high, and if the evaluation is low, the map boundary is used. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2017-068617 [Patent Document 2] Japanese Patent Application Publication No. 2018-200501 Summary of the Invention [Problem to be solved by the invention]

[0005] However, these conventional technologies all address the erroneous recognition of road dividing lines in specific sections, such as branching roads and curved roads. However, even when the vehicle is traveling on a normal straight road, road dividing lines can be erroneously recognized. For example, while the vehicle is traveling on a straight road, a road dividing line recognized from map information may be erroneously recognized, resulting in a road dividing line that should be recognized as a straight road being recognized as an S-curve road. As a result, when the vehicle is traveling under automated driving or driver assistance, driving control appropriate for a curved road is applied, and inappropriate deceleration control, for example, may be performed even when the vehicle is traveling on a straight road.

[0006] The present invention has been made in consideration of the above circumstances, and an object thereof is to provide a vehicle control device, a vehicle control method, and a program that can prevent inappropriate driving control of a vehicle from being executed due to a road division line recognized from map information being mistakenly recognized as an S-curve road, thereby contributing to the development of a sustainable transportation system. [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 embodiment of the present invention includes a determination unit that determines whether an S-shaped road candidate, which is a section represented by map road dividing lines based on map information stored in a memory unit, indicates an S-shaped road, and a control unit that performs driving control of the vehicle based on the map road dividing lines. The determination unit determines that the S-shaped road candidate is not an S-shaped road if the distance between the start point and end point of the S-shaped road candidate is less than or equal to a first threshold, and the control unit suppresses driving control of the vehicle according to the curved road if it is determined that the S-shaped road candidate is not an S-shaped road.

[0008] (2): In the above aspect (1), the determination unit determines that the S-shaped road candidate is not an S-shaped road if the distance between the start point and the end point of the S-shaped road candidate is less than or equal to a first threshold value and the curvature change amount of at least one of the forward range and the rear range of the S-shaped road candidate is less than or equal to a second threshold value.

[0009] (3): In the above aspect (1), the determination unit determines that the S-shaped road candidate is not an S-shaped road if the distance between the start point and the end point of the S-shaped road candidate is less than or equal to a first threshold value and at least one of the forward range and the rear range of the S-shaped road candidate is a straight line.

[0010] (4) In the above aspect (1), when it is determined that the S-shaped road candidate is not an S-shaped road, the control unit performs driving control so that the vehicle travels straight.

[0011] (5): In the above aspect (1), when it is determined that the S-shaped road candidate is not an S-shaped road, the control unit continues the driving control that was in effect before the determination.

[0012] (6): In the above aspect (1), when it is determined that the S-shaped road candidate is not an S-shaped road, the control unit performs driving control according to the end point of the S-shaped road candidate or the start point of a road following the S-shaped road candidate.

[0013] (7): In the above aspect (1), when it is determined that the S-shaped road candidate is not an S-shaped road, the control unit does not execute curve road deceleration control for the S-shaped road candidate.

[0014] (8): In another aspect of the present invention, a vehicle control method is provided in which a computer determines whether an S-shaped road candidate, which is a section represented by map road dividing lines based on map information stored in a memory unit, indicates an S-shaped road, performs vehicle driving control based on the map road dividing lines, determines that the S-shaped road candidate is not an S-shaped road if the distance between the start point and end point of the S-shaped road candidate is less than or equal to a first threshold, and suppresses vehicle driving control according to the curved road if it is determined that the S-shaped road candidate is not an S-shaped road.

[0015] (9): A program according to another aspect of the present invention causes a computer to determine whether an S-shaped road candidate, which is a section represented by map road dividing lines based on map information stored in a memory unit, indicates an S-shaped road, and controls the vehicle's driving based on the map road dividing lines.If the distance between the start point and end point of the S-shaped road candidate is less than or equal to a first threshold, the program determines that the S-shaped road candidate is not an S-shaped road.If it is determined that the S-shaped road candidate is not an S-shaped road, the program suppresses the vehicle's driving control according to the curved road.

[0016] According to the above aspects (1) to (9), it is possible to prevent inappropriate driving control from being performed on the vehicle due to the road dividing line recognized from the map information being mistakenly recognized as an S-curve road. [Brief explanation of the drawings]

[0017] [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] 10 is a diagram for explaining conditions under which a determining unit 132 extracts an S-curve road candidate. FIG. [Figure 5]10 is a diagram for explaining a method in which a determining unit 132 determines an S-curve road candidate as noise. FIG. [Figure 6] 10 is a diagram for explaining a method by which the determining unit 132 correctly determines that an S-curve road candidate is an S-curve road. 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

[0018] 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.

[0019] [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.

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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 center 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, and information on prohibited sections where Mode A or Mode B (described later) is prohibited. Furthermore, in this embodiment, the second map information 62 stores curvature information associated with each point constituting a lane boundary (i.e., a left-side road dividing line and a right-side road dividing line). The second map information 62 may be updated as needed by the communication device 20 communicating with another device.

[0031] 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.

[0032] 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).

[0033] 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 described later is an example of a "vehicle control device."

[0034] 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.

[0035] 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).

[0036] 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 recognition unit 130 calculates 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 they match), it recognizes either the map road dividing lines or the camera road dividing lines (or their median, 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.

[0037] 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.

[0038] The determination unit 132 of the recognition unit 130 acquires map road dividing lines that exist within a predetermined range (for example, within several hundred meters) in the traveling direction from the current position of the vehicle M, and determines whether the acquired map road dividing lines indicate an S-curve road. Details of the processing by the determination unit 132 will be described later.

[0039] 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.

[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 curved road driving event (S-curve road driving event), a low-speed following driving event, a lane change event, a branching event, a merging event, and a takeover event. The behavior plan generation unit 140 generates a target trajectory according to the activated event. For example, when the recognition unit 130 recognizes the presence of a curved road based on camera road dividing lines or map road dividing lines present in the traveling direction of the host vehicle M as a curved road driving event, the behavior plan generation unit 140 generates a target trajectory such that the host vehicle M decelerates compared to when the presence of a curved road is not recognized (for example, when a straight road is recognized). Furthermore, for example, when the determining unit 132, which will be described later, determines that a map road dividing line present in the traveling direction of the host vehicle M indicates an S-curve road, the behavior plan generating unit 140 generates a target trajectory such that the host vehicle M decelerates compared to when the map road dividing line does not indicate an S-curve road, as an S-curve road driving event. Because an S-curve road is a type of curved road, an S-curve road driving event may be included in the curved road driving event. Slowing down the host vehicle M in response to the recognition of an S-curve road is an example of "vehicle driving control according to a curved road."

[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, when the determination unit 132 determines that a map road dividing line present in the traveling direction of the host vehicle M indicates an S-curve road, the mode determination unit 150 changes the driving mode of the host vehicle M to a driving mode with a heavier task. For example, when the mode determination unit 150 determines that a map road dividing line present in the traveling direction of the host vehicle M indicates an S-curve road 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 a mode equal to or lower than mode C (mode C, mode D, or mode E). "Changing the driving mode of the host vehicle M to a driving mode with a heavier task" is an example of "vehicle driving control according to a curved road."

[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] [S-curve road detection process] As described above, the determination unit 132 determines whether a map road dividing line present in the traveling direction of the host vehicle M indicates an S-curve road. If it is determined that the map road dividing line indicates an S-curve road, the first control unit 120 executes vehicle travel control according to the curved road. However, in the prior art, for example, while the host vehicle M is traveling on a straight road, an erroneous recognition of the map road dividing line may occur, and a map road dividing line that should be recognized as a straight road may be recognized as an S-curve road. As a result, travel control according to the curved road may be applied to the host vehicle M traveling under automated driving or driving assistance, and inappropriate deceleration control, for example, may be executed even though the host vehicle is traveling on a straight road.

[0058] With this as a background, the determination unit 132 first extracts an S-curve road candidate from map road dividing lines present in the traveling direction of the host vehicle M, and determines whether or not the extracted S-curve road candidate is noise. If the determination unit 132 determines that the S-curve road candidate is noise, the first control unit 120 continues the autonomous driving or driving assistance of the host vehicle M without lowering the driving mode level of the host vehicle M or executing deceleration control. The determination process executed by the determination unit 132 will be described below.

[0059] 4 is a diagram for explaining the conditions under which the determination unit 132 extracts S-curve road candidates. The graph shown in FIG. 4 shows the relationship between the distance X [m] from the vehicle M and the curvature Y [m] at each point constituting the map road dividing line, which exists in the traveling direction of the vehicle M. -1]. As an example, Fig. 4 shows a case where the map road dividing line curves clockwise when the curvature Y is a positive value, and the map road dividing line curves counterclockwise when the curvature Y is a negative value, but the sign relationship may be reversed. The determination unit 132 first determines whether a predetermined range of map road dividing lines present in the traveling direction of the host vehicle M satisfy all of conditions 1 to 6 (or any combination including at least one of the conditions) for extracting an S-curve road candidate, and if it determines that the map road dividing line satisfies these conditions, it extracts the map road dividing line as an S-curve road candidate.

[0060] The determination unit 132 determines, as condition 1, whether the signs of consecutive peak points of the curvature of the map road-dividing line are reversed. This condition is for determining whether the map road-dividing line is an S-curve road, first turning in one direction (right or left) and then turning in the other direction (left or right). In the example of FIG. 4, the graph includes peak point P1 and peak point P2, and the signs of these consecutive peak points P1 and P2 are reversed. Therefore, the determination unit 132 determines that the graph shown in FIG. 4 satisfies condition 1.

[0061] The determination unit 132 further determines, as condition 2, whether the distance between successive peak points is equal to or less than a predetermined value. This condition is for determining whether the map road-dividing line has a sufficiently small distance between peak points suitable for determining that the road is an S-curve. In the case of FIG. 4, the determination unit 132 determines whether the distance between peak point P1 and peak point P2 is equal to or less than a predetermined value.

[0062] The determination unit 132 further determines whether the total amplitude Y, which is the sum of the amplitude Yl at peak point P1 and the amplitude Ys ​​at peak point P2, is equal to or greater than a predetermined value as condition 3. This condition is for determining whether the map road-dividing line has a sufficiently large degree of curvature suitable for determining that the road is an S-curve.

[0063] The determination unit 132 further determines, as condition 4, whether the amplitude ratio Yl / Ys of the amplitude Yl of the peak point P2 to the amplitude Ys ​​of the peak point P1 is equal to or greater than a predetermined value (here, the predetermined value is assumed to be a value greater than 1). This condition is set in order to determine whether the map road division line has this tendency, since an S-curve road generally has a tendency for the amplitude of the next peak point P2 to be larger than the amplitude of the first peak point P1.

[0064] The determination unit 132 further determines whether the amplitude Yl of the peak point P2 is equal to or greater than a predetermined value as condition 5. This condition is for determining whether the map road-dividing line has a sufficiently large amplitude Yl of the peak point P2 suitable for determining that the road is an S-curve road.

[0065] The determination unit 132 further determines, as condition 6, whether the curvature difference d between the start point S1 and the end point E1 of a section of the map road-dividing line that includes two peak points P1 and P2 where the sign of the curvature reverses is equal to or less than a predetermined value. This condition is for determining the leading and trailing ends of an S-curve road among the map road-dividing line. In other words, the determination unit 132 may first determine the start point S1 of the map road-dividing line where the curvature begins to change, and then define as the end point E1 a point on the section of the map road-dividing line that includes two peak points P1 and P2 where the sign of the curvature reverses, where the curvature difference d from the start point S1 first becomes equal to or less than the predetermined value.

[0066] In this way, the determination unit 132 extracts, as S-curve road candidates, sections that satisfy all of the above conditions 1 to 6 (or any combination including at least one of the conditions) from the map road dividing lines that exist in the traveling direction of the vehicle M. After extracting an S-curve road candidate, the determination unit 132 then determines whether the S-curve road candidate is noise.

[0067] Fig. 5 is a diagram illustrating a method by which the determination unit 132 determines an S-curve road candidate as noise. In Fig. 5, solid lines AL represent actual roads, and dotted lines ML represent map road-dividing lines. That is, Fig. 5 illustrates a situation in which the map road-dividing lines are erroneously recognized as an S-curve road, even though the host vehicle M is actually traveling on a straight road. It is assumed that the determination unit 132 has extracted the section from the start point S1 to the end point E1 of the map road-dividing lines as an S-curve road candidate.

[0068] When the determination unit 132 extracts an S-curve road candidate, the determination unit 132 determines whether the extracted S-curve road candidate is noise as a first condition for noise determination. More specifically, the determination unit 132 first determines whether the distance d1 from the start point S1 to the end point E1 of the S-curve road candidate is equal to or less than a first threshold. This condition is for determining whether the extracted S-curve road candidate has a distance that is unrealistic (too short) for an S-curve road. In other words, if the distance d1 is equal to or less than the first threshold, this means that the S-curve road candidate is too short for actual vehicle travel and is therefore likely to be noise.

[0069] Next, as a second condition for noise determination, the determination unit 132 determines whether the curvature change amount in at least one of the forward range and the rear range of the extracted S-curve road candidate is equal to or less than a second threshold. In the case of FIG. 5, the determination unit 132 determines whether the curvature change amount in at least one (or both) of a first range R1, which is a predetermined distance rearward in the traveling direction from the start point S1 of the S-curve road candidate, and a second range R2, which is a predetermined distance forward in the traveling direction from the end point E1 of the S-curve road candidate, is equal to or less than the second threshold. This condition is for determining whether the extracted S-curve road candidate has an unrealistic (steady) curvature change amount for an S-curve road in the forward / backward direction. In other words, if the S-curve road candidate is actually an S-curve road, the curvature change amount in at least one (or both) of the forward / backward directions generally tends to be greater than the second threshold. Therefore, if the curvature change amount is equal to or less than the second threshold, the S-curve road candidate is likely to be noise. The condition of whether the curvature change amount of at least one (or both) of the first range R1 and the second range R2 is less than or equal to the second threshold value can also be expressed as the condition of whether at least one (or both) of the first range R1 and the second range R2 has a steady shape with no change in road shape, specifically, whether it is a straight or steadily curved road.

[0070] In this way, the determination unit 132 determines whether the extracted S-curve road candidate satisfies the first and second conditions for noise determination, and if it is determined that the S-curve road candidate satisfies the first and second conditions, it determines that the S-curve road candidate is noise. In the case of FIG. 5, the determination unit 132 determines that the distance d1 is equal to or less than the first threshold, and determines that the curvature change amount is equal to or less than the second threshold in both the first range R1 and the second range R2, and therefore determines that the extracted S-curve road candidate is noise. Alternatively, the determination unit 132 may determine whether the S-curve road candidate satisfies at least one of the first and second conditions, and if it is determined that the S-curve road candidate satisfies at least one of the first and second conditions, it may determine that the S-curve road candidate is noise.

[0071] Fig. 6 is a diagram illustrating a method by which the determination unit 132 correctly determines an S-curve road candidate as an S-curve road. Fig. 6 shows a situation in which the host vehicle M is actually traveling on an S-curve road. Unlike the case of Fig. 5, in the situation shown in Fig. 6, the determination unit 132 determines that the distance d1 from the start point S1 to the end point E1 of the S-curve road candidate is greater than the first threshold value, and also determines that the amount of curvature change in both the first range R1 and the second range R2 is greater than the second threshold value, and therefore determines that the extracted S-curve road candidate is a normal S-curve road.

[0072] When the determination unit 132 determines that the S-curve road candidate is noise, as described above, the first control unit 120 continues the autonomous driving or driving assistance of the host vehicle M before the determination, without lowering the driving mode level of the host vehicle M or executing deceleration control according to the curved road. At this time, the first control unit 120 may perform driving control so that the host vehicle M travels straight, or may perform driving control according to the end point E1 of the S-curve road candidate or the start point of the road following the end point E1. For example, the first control unit 120 may perform driving control of the host vehicle M so that the host vehicle M travels straight from the current position of the host vehicle M to the end point E1 of the S-curve road candidate or the start point of the road following the end point E1. Furthermore, as another aspect, the action plan generation unit 140 may generate a target trajectory based on odometry information (speed, acceleration, etc.) of the host vehicle M so that the host vehicle M passes through a point predicted based on the speed and acceleration of the host vehicle M before the determination.

[0073] [Processing flow] 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 shown in the flowchart in Fig. 7 is repeatedly executed by the automatic driving control device 100 while the host vehicle M is traveling in a driving mode in which automatic driving or driving assistance is executed.

[0074] The determination unit 132 first determines whether or not an S-curve road candidate has been extracted from a map road dividing line present in the traveling direction of the host vehicle M (step S100). More specifically, the determination unit 132 determines whether or not the map road dividing line present in the traveling direction of the host vehicle M satisfies all of conditions 1 to 6 (or any combination including at least one of the conditions) for extracting an S-curve road candidate.

[0075] If it is determined that an S-curve road candidate has not been extracted, the determination unit 132 executes the process of step S100 again after a certain period of time. On the other hand, if it is determined that an S-curve road candidate has been extracted, the determination unit 132 next determines whether or not the distance between the start point and end point of the extracted S-curve road candidate is equal to or less than a first threshold (step S102). If it is determined that the distance between the start point and end point of the extracted S-curve road candidate is greater than the first threshold, the first control unit 120 executes driving control appropriate for the curved road (step S104). More specifically, the behavior plan generation unit 140 generates a target trajectory that decelerates the host vehicle M, and the mode determination unit 150 changes the driving mode of the host vehicle M to a driving mode with a more complex task.

[0076] On the other hand, if it is determined that the distance between the start point and end point of the extracted S-curve road candidate is equal to or less than the first threshold, the determination unit 132 next determines whether the amount of curvature change in the forward range and rearward range of the S-curve road candidate is equal to or less than a second threshold (step S106). If it is determined that the amount of curvature change in the forward range and rearward range of the S-curve road candidate is greater than the second threshold, the first control unit 120 executes driving control appropriate for the curved road (step S104). On the other hand, if it is determined that the amount of curvature change in the forward range and rearward range of the S-curve road candidate is equal to or less than the second threshold, the first control unit 120 executes driving control appropriate for the curved road (step S108). This ends the processing of this flowchart.

[0077] In the above description, the determination unit 132 first extracts S-curve road candidates from the map road-dividing lines based on conditions 1 to 6 for extracting S-curve road candidates, and then determines whether the extracted S-curve road candidates satisfy the first and second conditions for noise determination. However, the present invention is not limited to this configuration, and the determination unit 132 may search for a section from the map road-dividing lines that simultaneously satisfies conditions 1 to 6 for extracting S-curve road candidates and the first and second conditions for noise determination.

[0078] According to the present embodiment described above, the determination unit determines that the S-shaped road candidate is not an S-shaped road if the distance between the start point and the end point of the S-shaped road candidate is equal to or less than the first threshold, and the control unit suppresses vehicle cruise control according to the curved road when it is determined that the S-shaped road candidate is not an S-shaped road. This makes it possible to prevent inappropriate cruise control from being performed on the host vehicle due to the road dividing line recognized from the map information being mistakenly recognized as an S-shaped curved road.

[0079] The above-described embodiment can be expressed as follows. a storage device storing a program; a hardware processor; The hardware processor executes the program, determining whether an S-shaped road candidate, which is a section represented by a map road dividing line based on map information stored in a storage unit, indicates an S-shaped road; Carrying out vehicle travel control based on the map road division lines; If the distance between the start point and the end point of the S-shaped road candidate is equal to or less than a first threshold, the S-shaped road candidate is determined to be not an S-shaped road; suppressing travel control of the vehicle according to the curved road when it is determined that the S-shaped road candidate is not an S-shaped road; The vehicle control device is configured as follows.

[0080] 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]

[0081] 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 140 Action Plan Generation Unit 150 Mode determination unit 160 Second Control Section

Claims

1. a determination unit that determines whether an S-shaped road candidate, which is a section represented by a map road dividing line based on map information stored in a storage unit, indicates an S-shaped road; a control unit that controls vehicle travel based on the map road division lines, the determination unit determines that the S-shaped road candidate is not an S-shaped road when a distance in a road longitudinal direction between a start point and an end point of the S-shaped road candidate is equal to or less than a first threshold value; the control unit suppresses travel control of the vehicle according to a curved road when it is determined that the S-shaped road candidate is not an S-shaped road. Vehicle control device.

2. the determination unit determines that the S-shaped road candidate is not an S-shaped road when a distance in the road longitudinal direction between a start point and an end point of the S-shaped road candidate is equal to or less than a first threshold value and a curvature change amount of at least one of a front range and a rear range of the S-shaped road candidate is equal to or less than a second threshold value; The vehicle control device according to claim 1 .

3. the determination unit determines that the S-shaped road candidate is not an S-shaped road when a distance in the road longitudinal direction between a start point and an end point of the S-shaped road candidate is equal to or less than a first threshold value and at least one of a front range and a rear range of the S-shaped road candidate is a straight line; The vehicle control device according to claim 1 .

4. the control unit performs driving control so that the vehicle travels straight when it is determined that the S-shaped road candidate is not an S-shaped road. The vehicle control device according to claim 1 .

5. When it is determined that the S-shaped road candidate is not an S-shaped road, the control unit continues the driving control that was performed before the determination. The vehicle control device according to claim 1 .

6. when it is determined that the S-shaped road candidate is not an S-shaped road, the control unit performs driving control according to an end point of the S-shaped road candidate or a start point of a road following the S-shaped road candidate. The vehicle control device according to claim 1 .

7. the control unit does not execute curve road deceleration control for the S-shaped road candidate when it is determined that the S-shaped road candidate is not an S-shaped road. The vehicle control device according to claim 1 .

8. The computer determining whether an S-shaped road candidate, which is a section represented by a map road dividing line based on map information stored in a storage unit, indicates an S-shaped road; Carrying out vehicle travel control based on the map road division lines; If a distance in a road longitudinal direction between a start point and an end point of the S-shaped road candidate is equal to or less than a first threshold, the S-shaped road candidate is determined to be not an S-shaped road; suppressing travel control of the vehicle according to the curved road when it is determined that the S-shaped road candidate is not an S-shaped road; Vehicle control method.

9. On the computer, determining whether an S-shaped road candidate, which is a section represented by a map road dividing line based on map information stored in a storage unit, indicates an S-shaped road; Controlling the vehicle's travel based on the road division lines on the map; When a distance in a road longitudinal direction between a start point and an end point of the S-shaped road candidate is equal to or less than a first threshold, the S-shaped road candidate is determined to be not an S-shaped road; suppressing a curved road-appropriate driving control of the vehicle when it is determined that the S-shaped road candidate is not an S-shaped road; program.

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