Vehicle control device, vehicle control method, and program

Abstract

To suppress an erroneous determination with respect to a lane marking based on a surrounding situation of an own vehicle.SOLUTION: A vehicle control device comprises: a first recognition section which recognizes a surrounding situation including a first lane marking partitioning a travel lane of an own vehicle and another vehicle around the own vehicle based on output of a detection device detecting a surrounding situation of an own vehicle; a second recognition section which recognizes a second lane marking partitioning a travel lane around the own vehicle from map information based on positional information of the own vehicle; and a determination section which determines whether the first lane marking and the second lane marking match with each other. When the first recognition section recognizes a plurality of first partition lines on one side of the own vehicle among the first partition lines on right and left sides of the own vehicle, the second lane marking matches with a first side first lane marking included in the recognized plurality of side first partition lines, and a predetermined condition is met, the determination section reduces reliability of match information between the matched first side first lane marking and the second lane marking.SELECTED DRAWING: Figure 2

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 traffic participants have been gaining momentum. Toward this goal, efforts are being focused on research and development into autonomous driving technology to further improve traffic safety and convenience. In this context, a technology has been known that determines whether road signs recognized by image recognition processing match road signs in map information, and adjusts the reliability of the map information based on the determination result (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-212188 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in conventional automated driving technologies, even if camera lane lines obtained from captured camera images match map lane lines obtained from map information, the reliability is not necessarily high. For example, when road construction is being carried out, avoidance lane lines are temporarily drawn on the road to allow vehicles to avoid the construction area. However, the temporarily drawn lane lines may remain during or after the construction. In such cases, even if the camera lane lines and the map lane lines match, the lane lines may not be correct. As such, there is a problem that the lane lines may be misidentified depending on the surrounding conditions.

[0005] In order to solve the above-mentioned problems, one of the objects of the present application is to provide a vehicle control device, a vehicle control method, and a program that can suppress erroneous determination of lane markings based on the surrounding conditions of the vehicle, thereby contributing to the development of sustainable transportation systems. [Means for solving the problem]

[0006] A vehicle control device, a vehicle control method, and a program according to the present invention employ the following configuration. (1): A vehicle control device according to one embodiment of the present invention includes a first recognition unit that recognizes the surrounding conditions, including first dividing lines that define the lane in which the vehicle is traveling and other vehicles that exist around the vehicle, based on the output of a detection device that detects the surrounding conditions of the vehicle; a second recognition unit that recognizes second dividing lines that define the lanes around the vehicle from map information based on the position information of the vehicle; and a judgment unit that determines whether the first dividing lines and the second dividing lines match, wherein the judgment unit recognizes multiple first dividing lines on one side of the first dividing lines that exist on the left and right sides of the vehicle by the first recognition unit, and when a first one-side first dividing line included in the multiple recognized one-side first dividing lines matches the second dividing line and satisfies a predetermined condition, reduces the reliability of the matching information between the matching first one-side first dividing line and the second dividing line.

[0007] (2): In the above aspect (1), the predetermined condition includes the other vehicle passing over the first one-side first dividing line that is determined to coincide with the second dividing line.

[0008] (3): In the above aspect (1), the vehicle is further provided with a driving control unit that controls one or both of the steering and speed of the vehicle based on the judgment result by the judgment unit to perform driving control, and the driving control unit controls the driving of the vehicle based on the second one-side first demarcation line when there is a second one-side first demarcation line among the multiple one-side first demarcation lines recognized by the first recognition unit that is judged by the judgment unit not to match the second demarcation line.

[0009] (4): In the above aspect (1), the predetermined condition includes the vehicle being traveling within a predetermined distance range before a point under construction or a point where construction has been carried out in the past.

[0010] (5) In the aspect (1) above, the predetermined condition includes the presence of a physical road boundary in the traveling direction of the host vehicle.

[0011] (6): In the above aspect (1), the vehicle further includes a driving control unit that controls one or both of the steering and speed of the vehicle based on the judgment result by the judgment unit to perform driving control, and the driving control unit causes the vehicle to run along the road physical boundary when there is a road physical boundary that extends in a direction different from the matched first one-side first dividing line and second dividing line.

[0012] (7): In the above aspect (3), when the second one-side first dividing line extends along the physical boundary of the road, the determination unit determines that the second one-side first dividing line is a correct dividing line, and the driving control unit causes the vehicle to travel along the second one-side first dividing line.

[0013] (8): In the above aspect (7), the driving control unit adjusts the position of the second one-side first dividing line along the direction in which the road physical boundary extends, and causes the vehicle to run along the adjusted position of the second one-side first dividing line.

[0014] (9): In the above aspect (8), the driving control unit adjusts the position of the second one-side first dividing line when the distance between the road physical boundary and the second one-side first dividing line is less than a predetermined distance.

[0015] (10): In the aspect (6) above, the driving control unit does not perform driving control based on the road physical boundary when the vehicle is traveling on a lane having a gradient of a predetermined value or more.

[0016] (11): In the above aspect (6), the driving control unit drives the vehicle along the road physical boundary when sign information indicating a construction site is present in the direction of travel of the vehicle.

[0017] (12): A vehicle control method according to one embodiment of the present invention is a vehicle control method in which a computer recognizes the surrounding conditions, including first dividing lines that define the lane in which the vehicle is traveling and other vehicles that are present around the vehicle, based on the output of a detection device that detects the surrounding conditions of the vehicle; recognizes second dividing lines that define the lanes around the vehicle from map information based on the position information of the vehicle; determines whether the first dividing lines and the second dividing lines match; recognizes multiple first dividing lines on one side of the first dividing lines that exist on the left and right sides of the vehicle; and if a first one-side first dividing line included in the recognized multiple one-side first dividing lines matches the second dividing line and satisfies predetermined conditions, reduces the reliability of the matching information between the matching first one-side first dividing line and the second dividing line.

[0018] (13): A program according to one embodiment of the present invention is a program that causes a computer to recognize the surrounding conditions, including first dividing lines that define the lane in which the vehicle is traveling and other vehicles that are present around the vehicle, based on the output of a detection device that detects the surrounding conditions of the vehicle; recognize second dividing lines that define the lanes around the vehicle from map information based on the position information of the vehicle; determine whether the first dividing lines and the second dividing lines match; and, when multiple first dividing lines on one side of the first dividing lines present on the left and right sides of the vehicle are recognized, and a first one-side first dividing line included in the multiple recognized one-side first dividing lines matches the second dividing line and satisfies predetermined conditions, reduce the reliability of the matching information between the matching first one-side first dividing line and the second dividing line. [Effects of the Invention]

[0019] According to the above aspects (1) to (13), it is possible to suppress erroneous determination of the lane markings based on the surrounding conditions of the vehicle. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a configuration diagram of a vehicle system 1 including a vehicle control device according to an embodiment. [Figure 2] 2 is a functional configuration diagram of a first control unit 120 and a second control unit 160. FIG. [Figure 3] FIG. 4 is a diagram for explaining the determination process and the operation control in the first scene. [Figure 4] FIG. 10 is a diagram for explaining the determination process and the driving control in the second scene. [Figure 5] FIG. 10 is a diagram for explaining the determination process and the driving control in the third scene. [Figure 6] 3 is a flowchart illustrating an example of processing executed by the automatic driving control device 100 according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0021] Hereinafter, with reference to the drawings, embodiments of a vehicle control device, a vehicle control method, and a program according to the present invention will be described. Hereinafter, an embodiment will be described in which a host vehicle is applied to an autonomous vehicle including a vehicle control device, as an example. Autonomous driving refers to performing driving control by automatically controlling, for example, one or both of the steering and speed of a vehicle. The above-mentioned driving control may include, for example, an adaptive cruise control system (ACC), a traffic jam pilot (TJP), a lane keeping assistance system (LKAS), an automated lane change (ALC), a collision mitigation brake system (CMBS), and the like. Furthermore, an autonomous vehicle may be manually controlled by a vehicle user (e.g., a passenger) (so-called manual driving). Furthermore, although the following description will be given of a case where a law stipulating left-hand traffic applies, if a law stipulating right-hand traffic applies, the terms left and right may be reversed.

[0022] [Overall configuration] 1 is a configuration diagram of a vehicle system 1 including a vehicle control device according to an embodiment. The vehicle (hereinafter referred to as host vehicle M) on which the vehicle system 1 is mounted is, for example, a two-wheeled, three-wheeled, or four-wheeled vehicle, and its drive source is 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 battery (storage battery) such as a secondary battery or a fuel cell.

[0023] The vehicle system 1 includes, for example, a camera 10, a radar device 12, a LIDAR (Light Detection and Ranging) device 14, an object recognition device 16, a communication device 20, an HMI (Human Machine Interface) 30, vehicle sensors 40, a navigation device 50, an MPU (Map Positioning Unit) 60, a 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. The combination of the camera 10, the radar device 12, the LIDAR 14, and the object recognition device 16 is an example of a "detection device DD." The HMI 30 is an example of an "output device." The automatic driving control device 100 is an example of a "vehicle control device."

[0024] The camera 10 is a digital camera that uses 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 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, the front of the vehicle body, etc. When capturing an image of the rear, the camera 10 is attached to the top of the rear windshield, the back door, etc. When capturing an image of the side, the camera 10 is attached to a door mirror, etc. The camera 10 periodically and repeatedly captures images of the surroundings of the host vehicle M, for example. The camera 10 may be a stereo camera.

[0025] The radar device 12 emits radio waves such as millimeter waves around the vehicle M and detects radio waves reflected by surrounding objects (reflected waves) to detect at least the position (distance and direction) of the objects. The radar device 12 is attached to any location on the vehicle M. The radar device 12 may detect the position and speed of the objects using an FM-CW (Frequency Modulated Continuous Wave) method.

[0026] The LIDAR 14 irradiates light around the vehicle M and measures the scattered light. The LIDAR 14 detects the distance to the target based on the time between emitting and receiving the light. The irradiated light is, for example, a pulsed laser beam. The LIDAR 14 is attached to any location on the vehicle M.

[0027] 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. Alternatively, 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. In that case, the object recognition device 16 may be omitted from the configuration of the vehicle system 1 (detection device DD).

[0028] The communication device 20 communicates with, for example, other vehicles in the vicinity of the vehicle M, terminal devices of users using the vehicle M, or various server devices, using networks such as a cellular network, a Wi-Fi network, Bluetooth (registered trademark), DSRC (Dedicated Short Range Communication), LAN (Local Area Network), WAN (Wide Area Network), or the Internet.

[0029] The HMI 30 outputs various information to the occupants of the vehicle M and accepts input operations by the occupants. The HMI 30 includes, for example, various display devices, speakers, buzzers, touch panels, switches, keys, microphones, and the like.

[0030] 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 the yaw rate (e.g., the rotational angular velocity around a vertical axis passing through the center of gravity of the host vehicle M), and a direction sensor that detects the orientation of the host vehicle M. The vehicle sensor 40 may also include, for example, an inclination angle sensor that detects the inclination (inclination angle) of the host vehicle M based on gravity or the like. The vehicle sensor 40 may also be provided with a position sensor that detects the position of the vehicle. The position sensor is an example of a "position measurement unit." The position sensor is, for example, a sensor that acquires position information (longitude and latitude information) from a GPS (Global Positioning System) device. The position sensor may also be a sensor that acquires position information using a GNSS (Global Navigation Satellite System) receiver 51 of the navigation device 50. The vehicle sensor 40 may derive the speed of the host vehicle M from the difference (i.e., distance) of position information at a predetermined time in the position sensor. The results detected by the vehicle sensor 40 are output to the automatic driving control device 100.

[0031] The navigation device 50 includes, for example, a GNSS 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 a 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 sensor 40. The navigation HMI 52 includes a display device, a speaker, a touch panel, keys, etc. The GNSS receiver 51 may be provided in the vehicle sensor 40. 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 route on a map) from the position of the vehicle M identified by the GNSS receiver 51 (or an arbitrary 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 in which road shapes are expressed by, for example, links indicating roads and nodes connected by the links. The first map information 54 may also include POI (Point Of Interest) information and the like. 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 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. The navigation device 50 outputs the determined route on the map to the MPU 60.

[0032] 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.

[0033] 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, the number of lanes, the type and shape of road dividing lines (hereinafter referred to as dividing lines), information on the center of lanes, and road boundary information. The second map information 62 may also include information on whether the road boundary includes a structure that prevents a vehicle from passing (including crossing or coming into contact with). Examples of such structures include guardrails, curbs, medians, and fences. The term "impassable" may include the presence of a low level step that allows passage if unusual vehicle vibrations are tolerated. The second map information 62 may also include road shape information, traffic regulation information, address information (address and postal code), facility information, parking information, telephone number information, and the like. The road shape information includes, for example, the curvature (which may be interpreted as the radius of curvature; the same applies below), width, and gradient of the road. The second map information 62 may be updated as needed by the communication device 20 communicating with an external device. The first map information 54 and the second map information 62 may be provided as an integrated piece of map information.

[0034] The driving operators 80 include, for example, a steering wheel, an accelerator pedal, and a brake pedal. The driving operators 80 may also include a shift lever, a variable steering wheel, a joystick, or other operators. Each operator of the driving operators 80 is equipped with an operation detection unit that detects, for example, the amount of operation of the operator by the occupant or whether or not the operator is operated. The operation detection unit detects, for example, the steering angle and steering torque of the steering wheel, the amount of depression of the accelerator pedal and the brake pedal, etc. The operation detection unit then outputs the detection results to the automatic driving control device 100 or one or both of the driving force output device 200, the brake device 210, and the steering device 220.

[0035] The automatic driving control device 100 executes various types of driving control associated with automatic driving for the host vehicle M. The automatic driving control device 100 includes, for example, a first control unit 120, a second control unit 160, an HMI control unit 180, and a storage unit 190. The first control unit 120, the second control unit 160, and the HMI control unit 180 are each realized by, for example, a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Furthermore, 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 above-mentioned program may be stored in advance in a storage device (a storage device with a non-transitory storage medium) such as an HDD or flash memory of the automatic driving control device 100, or may be stored in a removable storage medium such as a DVD, CD-ROM, or memory card, and installed in the storage device of the automatic driving control device 100 by inserting the storage medium (non-transitory storage medium) into a drive device, card slot, etc.

[0036] The storage unit 190 may be realized by the various storage devices described above, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a ROM (Read Only Memory), or a RAM (Random Access Memory). The storage unit 190 stores, for example, various types of information, programs, and the like in the embodiments. The storage unit 190 may also store map information (for example, the first map information 54 and the second map information 62).

[0037] 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 and an action plan generation unit 140. 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 concurrently executing intersection recognition using deep learning or the like and recognition based on predefined conditions (such as the presence of traffic lights and road markings that can be pattern matched), and then scoring and comprehensively evaluating both. This ensures the reliability of autonomous driving. The first control unit 120 also executes control related to autonomous driving of the host vehicle M based on instructions from, for example, the MPU 60, the HMI control unit 180, or the like.

[0038] The recognition unit 130 recognizes the surrounding situation of the host vehicle M based on the recognition results of the detection device DD (information input from the camera 10, the radar device 12, and the LIDAR 14 via the object recognition device 16). For example, the recognition unit 130 recognizes the status of objects present around the host vehicle M (within a predetermined distance), such as their position, speed, and acceleration. The objects include, for example, other vehicles (surrounding vehicles), traffic participants (pedestrians, bicycles, etc.) traveling on the road, road structures, and other obstacles present in the vicinity. The road structures include, for example, road signs, traffic signals, railroad crossings, curbs, medians, guardrails, fences, etc. The position of the object is recognized as a position on an absolute coordinate system with a representative point of the host 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 the object may be represented by a representative point such as the center of gravity or a corner of the object, or by a represented area. The "state" of an object may include, for example, if the object is a moving object such as another vehicle, the acceleration or jerk of the moving object, or the "behavioral state" (for example, whether the other vehicle is changing lanes or is about to change lanes).

[0039] The recognition unit 130 includes, for example, a first recognition unit 132 and a second recognition unit 134. The functions of these units will be described in detail later.

[0040] The behavior plan generation unit 140 generates a behavior plan for driving the host vehicle M by autonomous driving based on the recognition results of the recognition unit 130, etc. For example, the behavior plan generation unit 140 generates a target trajectory for the host vehicle M to travel automatically (without driver operation) in the future, so that the host vehicle M can respond to the surrounding conditions of the host vehicle M, while essentially traveling in the recommended lane determined by the recommended lane determination unit 61, based on the recognition results by the recognition unit 130 and the surrounding road shapes based on the current position of the host vehicle M acquired from map information, etc. The target trajectory includes, for example, a speed element. For example, the target trajectory is expressed as a sequential arrangement of points (trajectory points) to be reached by the host vehicle M. The trajectory points are points to be reached by the host vehicle M at predetermined travel distances (e.g., on the order of several meters) along the road, and separately, target speeds and target accelerations for predetermined sampling times (e.g., on the order of a few tenths of a second) are generated as part of the target trajectory. Alternatively, the trajectory points may be positions to be reached by the host vehicle M at the sampling times for each predetermined sampling time. In this case, the target speed and target acceleration information are expressed as the interval between trajectory points.

[0041] The action plan generation unit 140 may set an autonomous driving event when generating the target trajectory. Examples of the event include a constant speed driving event in which the host vehicle M drives in the same lane at a constant speed, a following driving event in which the host vehicle M follows another vehicle that is within a predetermined distance (for example, within 100 m) ahead of the host vehicle M and is closest to the host vehicle M, a lane change event in which the host vehicle M changes lanes from the host vehicle's own lane to an adjacent lane, a branching event in which the host vehicle M branches off into a lane on the destination side at a road branching point, a merging event in which the host vehicle M merges into a main lane at a merging point, a takeover event in which the autonomous driving is terminated and the host vehicle M switches to manual driving, and so on. Examples of the event may also include an overtaking event in which the host vehicle M temporarily changes lanes to an adjacent lane, overtakes a leading vehicle in the adjacent lane, and then changes lanes back to the original lane, and an avoidance event in which the host vehicle M performs at least one of braking and steering to avoid an obstacle ahead of the host vehicle M.

[0042] Furthermore, the behavior plan generation unit 140 may change an event already determined for the current section to another event or set a new event for the current section, depending on the surrounding conditions of the host vehicle M recognized while the host vehicle M is traveling. Furthermore, the behavior plan generation unit 140 may change an event already set for the current section to another event or set a new event for the current section, depending on the operation of the occupant on the HMI 30. The behavior plan generation unit 140 generates a target trajectory according to the set event.

[0043] The behavior plan generation unit 140 also includes, for example, a determination unit 142 and an execution control unit 144. Details of these functions will be described later. For example, the recognition unit 130 and the determination unit 142 are an example of a "determination device." The execution control unit 144 and the second control unit 160 are an example of a "driving control unit."

[0044] 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.

[0045] The second control unit 160 includes, for example, a target trajectory acquisition unit 162, a speed control unit 164, and a steering control unit 166. The target trajectory 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.

[0046] Returning to FIG. 1 , the HMI control unit 180 notifies the occupant of predetermined information via the HMI 30. The predetermined information includes, for example, information related to the traveling of the vehicle M, such as information related to the state of the vehicle M and information related to driving control. The information related to the state of the vehicle M includes, for example, the speed of the vehicle M, engine speed, and shift position. The information related to driving control includes, for example, whether or not driving control is being performed by autonomous driving, information inquiring about whether or not to start autonomous driving, information related to the driving control status by autonomous driving, information related to the automation level, and information prompting the occupant to drive when switching from autonomous driving to manual driving. The predetermined information may also include information unrelated to the traveling of the vehicle M, such as television programs and content (e.g., movies) stored on a storage medium such as a DVD. The predetermined information may also include, for example, information related to the current location and destination during autonomous driving, and the remaining amount of fuel in the vehicle M. The HMI control unit 180 may output the information received by the HMI 30 to the communication device 20, the navigation device 50, the first control unit 120, etc.

[0047] Furthermore, the HMI control unit 180 may cause the HMI 30 to output inquiry information for the occupant, processing results by the first control unit 120 and the second control unit 160, etc. Furthermore, the HMI control unit 180 may transmit various pieces of information to be output by the HMI 30 to a terminal device used by the user of the vehicle M via the communication device 20.

[0048] Traveling drive force output device 200 outputs a traveling drive force (torque) to the drive wheels for the vehicle to travel. Traveling drive 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 second control unit 160 or information input from the accelerator pedal of driving operator 80.

[0049] The braking device 210 includes, 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 the second control unit 160 or information input from the brake pedal of the driving operation device 80, so that a braking torque corresponding to the braking operation is output to each wheel. The braking device 210 may include a backup mechanism that transmits hydraulic pressure generated by operation of the brake pedal to the cylinder via a master cylinder. Note that the braking device 210 is not limited to the configuration described above, and may also be an electronically controlled hydraulic braking device that controls an actuator according to information input from the second control unit 160 to transmit hydraulic pressure from the master cylinder to the cylinder.

[0050] The steering device 220 includes, for example, a steering ECU and an electric motor. The electric motor changes the direction of the steered wheels by, for example, applying a force to a rack and pinion mechanism. The steering ECU drives the electric motor to change the direction of the steered wheels in accordance with information input from the second control unit 160 or information input from the steering wheel of the driving operator 80.

[0051] [Recognition and Action Plan Generation] Next, the functions of the recognition unit 130 (first recognition unit 132, second recognition unit 134) and the action plan generation unit 140 (determination unit 142, execution control unit 144) will be described in detail. Note that the following mainly describes the determination process in the embodiment and the contents of driving control (cruising control) based on the determination result, divided into several scenes. [Scene 1] FIG. 3 is a diagram illustrating the determination process and driving control in the first scenario. The example in FIG. 3 shows lane markings CL1 and CL2 recognized by the detection device DD, lane markings ML1 to ML3 obtained from map information (e.g., second map information 62) based on the position information of the host vehicle M, and lane markings RL1 to RL5 actually drawn on the road. In the map information, lane L1 is defined by lane markings ML1 and ML2, and lane L2 is defined by lane markings ML2 and ML3. Lanes L1 and L2 are lanes on which a vehicle can travel in the same direction (the X-axis direction in the figure). In the example in FIG. 3, lane markings CL1 to CL2 are an example of a "first lane marking," and lane markings ML1 to ML3 are an example of a "second lane marking." In the example in FIG. 3, the host vehicle M travels on lane L1 at a speed VM.

[0052] In the first scene, other vehicles m1 and m2 are present around the host vehicle M. In the example of Fig. 3, the other vehicle m1 is traveling ahead of the host vehicle M at a speed Vm1, and the other vehicle m2 is traveling ahead of the host vehicle M (other vehicle m1) at a speed Vm2. In Fig. 3, a road construction site is present on the lane L1, and temporary dividing lines RL4 and RL5 are drawn to allow vehicles to avoid entering the no-travel area AR1 that includes the construction site. During the construction, vehicles traveling on the lane L1 can avoid entering the no-travel area AR1 by traveling through the area defined by the dividing lines RL4 and RL5 and moving toward the lane L2.

[0053] The first recognition unit 132 recognizes the surrounding conditions of the host vehicle M based on the output of the detection device DD that detects the surrounding conditions of the host vehicle M. For example, the first recognition unit 132 recognizes left and right lane markings CL1 and CL2 that demarcate the driving lane (lane L1) of the host vehicle M based on an image captured by the camera 10 (hereinafter referred to as a camera image). The first recognition unit 132 may also recognize a lane marking that demarcates an adjacent lane (lane L2) adjacent to the driving lane. Hereinafter, the lane markings CL1 and CL2 may be referred to as "camera lane markings CL1 and CL2."

[0054] For example, the first recognition unit 132 analyzes the camera image, extracts edge points in the image that have a large difference in brightness from adjacent pixels, and recognizes each of the camera lane marking lines CL1 and CL2 on the image plane by connecting the edge points. The first recognition unit 132 also converts the positions of the camera lane marking lines CL1 and CL2 into a vehicle coordinate system (e.g., the XY plane coordinates in FIG. 3 ) based on the position of a representative point of the host vehicle M. The first recognition unit 132 may also recognize the curvature or curvature change amount of each of the camera lane marking lines CL1 and CL2. The curvature change amount is, for example, the time rate of change in the curvature of the camera lane marking lines CL1 and CL2 recognized by the camera 10 at a distance X [m] ahead as viewed from the host vehicle M. The first recognition unit 132 may also recognize the curvature or curvature change amount of the lane markings defined by the camera lane marking lines CL1 and CL2 by averaging the curvature or curvature change amount of each of the camera lane marking lines CL1 and CL2. The camera division lines CL1 and CL2 may be recognized or corrected based on the output of a detection device other than the camera 10.

[0055] Furthermore, when at least one of the camera lane marks on the left and right sides of the vehicle M has multiple lane marks due to forks (branching), the first recognition unit 132 recognizes each lane mark. In the example of FIG. 3, it is assumed that multiple camera lane marks CL2a and CL2b are recognized along the camera lane mark CL2 on the right side of the vehicle M. The camera lane mark CL2a is an example of a "first one-side first lane mark" or a "first one-side camera lane mark," and the lane mark CL2b is an example of a "second one-side first lane mark" or a "second one-side camera lane mark." Furthermore, the first recognition unit 132 recognizes construction sites, no-travel areas AR1, obstacles, and the like that exist in the traveling direction.

[0056] The first recognition unit 132 also recognizes other vehicles present in the vicinity (within a predetermined distance) of the host vehicle M. For example, the first recognition unit 132 recognizes other vehicles m1 and m2 present ahead of the host vehicle M based on the output of the detection device DD that detects the surrounding conditions of the host vehicle M. The first recognition unit 132 also recognizes the positions (relative positions with respect to the host vehicle M) and speeds (relative speeds with respect to the host vehicle M) of the other vehicles m1 and m2. The first recognition unit 132 may also recognize traveling position information of the other vehicles m1 and m2. The traveling position information is, for example, traveling trajectories K1 and K2 based on the positions of representative points of the other vehicles m1 and m2 at a predetermined time while they are traveling. The traveling position information may also include, for example, information regarding the predicted future traveling trajectories of the other vehicles m1 and m2 based on the traveling trajectories K1 and K2 and the orientations of the other vehicles m1 and m2.

[0057] The second recognition unit 134 recognizes lane markings around (within a predetermined distance from) the host vehicle M from map information based on the position of the host vehicle M detected by, for example, the vehicle sensor 40 or the GNSS receiver 51. For example, the second recognition unit 134 refers to map information based on the position information of the host vehicle M, and recognizes lane markings ML1 to ML3 that exist in the direction in which the host vehicle M is traveling or in which the host vehicle M can travel. Hereinafter, the lane markings ML1 to ML3 may be referred to as "map lane markings ML1 to ML3."

[0058] Furthermore, the second recognition unit 134 may recognize, among the recognized map division lines ML1 to ML3, map division lines ML1 and ML2 as division lines that divide the lane L1 on which the host vehicle M is traveling. Furthermore, the second recognition unit 134 recognizes the curvature or curvature change amount of each of the map division lines ML1 to ML3 from the map information. Furthermore, the second recognition unit 134 may average the curvature or curvature change amount of each of the map division lines ML1 to ML3 to recognize the curvature or curvature change amount for each of the lanes L1 and L2 divided by the map division lines.

[0059] The determination unit 142 determines whether at least one of the camera lane lines CL (CL1, CL2) and the map lane lines ML (ML1-ML3) is correct, for example, based on at least one of the camera lane lines CL (CL1, CL2) and the map lane lines ML (ML1-ML3) and the travel trajectories K1, K2 of the other vehicles m1, m2. Based on the determination result by the determination unit 142, the execution control unit 144 generates a target trajectory for driving control by controlling one or both of the steering and speed of the host vehicle M so that the host vehicle M travels along the lane line determined to be correct, generates a target trajectory for driving control to avoid contact with an obstacle, or performs control to end driving control (or not start driving control) if both lane lines are determined to be incorrect.

[0060] In the example of FIG. 3, the determination unit 142 first determines whether the camera lane markings CL (CL1, CL2) recognized by the first recognition unit 132 match the map lane markings ML (ML1, ML2) recognized by the second recognition unit 134. For example, the determination unit 142 derives the degree of match between the lane markings CL1 and ML1 located closest to the left of the host vehicle M, and the degree of match between the lane markings CL2 and ML2 located closest to the right of the host vehicle M. If the derived degree of match is equal to or greater than a threshold, the determination unit 142 determines that the camera lane markings CL and the map lane markings ML match; if the degree of match is less than the threshold, the determination unit 142 determines that they do not match. The above-described match determination is repeatedly performed at a predetermined timing or period.

[0061] For example, the determination unit 142 superimposes the camera lane lines CL1 and CL2 and the map lane lines ML1 and ML2 on the plane of the vehicle coordinate system (XY plane) based on the position of the representative point of the vehicle M. Then, the determination unit 142 determines the degree of match between the lane lines to be compared (lane lines CL1 and ML1, and lane lines CL2 and ML2). The degree of match is, for example, an index value related to the amount of deviation in lateral position (e.g., the Y-axis direction in the figure), and the smaller the amount of deviation, the greater the degree of match. The degree of match according to the amount of deviation may be derived, for example, by a predetermined function that uses the amount of deviation as input and outputs the degree of match, or may be derived using a table or the like in which the amount of deviation and the degree of match are associated. In the example of Figure 3, the degree of match may be derived for each of the amount of lateral deviation D1 between lane lines CL1 and ML1 and the amount of lateral deviation D2 between lane lines CL2 and ML2, or the degree of match may be derived based on the average, maximum, or minimum of the deviations D1 and D2. Furthermore, as shown in Figure 3, in areas where multiple camera lane lines CL2 exist on one side, the degree of match is derived between each of camera lane lines CL2a and CL2b and map lane line ML2.

[0062] Furthermore, the degree of match may be, for example, an index value related to the angle (deviation angle) formed by the two lane markings being compared, instead of (or in addition to) the lateral position deviation amount described above. In this case, the smaller the deviation angle, the greater the degree of match. In the example of FIG. 3, the degree of match may be derived from the deviation angle formed by lane markings CL1 and ML1 and the deviation angle formed by lane markings CL2 (CL2a, CL2b) and ML2, respectively, or may be derived based on the average, maximum, or minimum value of each angle.

[0063] The degree of match may be an index value related to the difference in curvature change between the lane markings, instead of (or in addition to) the lateral position deviation or the deviation angle of the lane markings. In this case, the smaller the difference in curvature change, the greater the degree of match. The curvature change is mainly used when the lane is curved. The determination unit 142 may derive the degree of match based on the average value of the difference in curvature change between the lane markings CL1 and ML1 and the difference in curvature change between the lane markings CL2 (CL2a, CL2b) and ML2, or may derive the degree of match based on the maximum or minimum difference. The determination unit 142 may also derive the degree of match based on the difference between the average value of the curvature change between the lane markings CL1 and CL2 and the average value of the curvature change between the lane markings ML1 and ML2, or based on the difference between the curvature change of the lane (lane L1) recognized from the camera image and the curvature change of the lane L1 recognized from the map information. The degree of match according to the difference in the deviation angle or curvature change amount may be derived, for example, using a predetermined function or a correspondence table, in the same way as the deviation amount.

[0064] Furthermore, for example, when the recognition accuracy of the camera lane markings CL1 and CL2 (CL2a and CL2b) recognized by the first recognition unit 132 falls below a threshold value or when the camera lane markings CL cannot be recognized, the determination unit 142 may derive the degree of match using the angle between the travel trajectories K1 and K2 of other vehicles m1 and m2 traveling in the vicinity and the map lane markings ML. The determination unit 142 may also set virtual lane markings parallel to the travel trajectories K1 and K2 and derive the degree of match between the set virtual lane markings and the map lane markings ML. The determination unit 142 may also determine whether the camera lane markings CL match the travel trajectories K1 and K2, regardless of the recognition results of the camera lane markings CL. Similarly, when the camera lane markings CL are recognized but the surrounding map lane markings ML cannot be recognized from the map information, the determination unit 142 may determine whether the camera lane markings CL match the travel trajectories K1 and K2 and use the determination results to determine whether the camera lane markings CL are correct. Furthermore, the determination unit 142 may determine whether the camera lane lines CL match the traveling trajectories K1 and K2, regardless of the recognition result of the map lane lines ML.

[0065] If the determination unit 142 determines that the camera lane line CL and the map lane line ML match based on the match determination using the degree of match described above, the determination unit 142 determines that the camera lane line CL and the map lane line ML are correct lane lines in the accuracy determination. Furthermore, if the determination unit 142 determines that the camera lane line CL and the map lane line ML do not match, the determination unit 142 may determine that at least one of the camera lane line CL and the map lane line ML is incorrect. For example, if the camera lane line CL and the map lane line ML do not match and the host vehicle M is performing driving control to avoid an obstacle ahead, the determination unit 142 may determine that the camera lane line CL is incorrect (or that the map lane line ML is correct).

[0066] The determination unit 142 may also determine that the camera lane lines CL are incorrect (or that the map lane lines ML are correct) if the camera lane lines CL do not match the map lane lines ML and if a predetermined number or more of the recognized travel trajectories of other vehicles are travel trajectories that follow the map lane lines ML (including within a predetermined tolerance range).The determination unit 142 may also determine that the map lane lines ML are incorrect (or that the camera lane lines CL are correct) if the camera lane lines CL do not match the map lane lines ML and if a predetermined number or more of the recognized travel trajectories of other vehicles are travel trajectories that follow the camera lane lines CL (including within a predetermined tolerance range).The determination unit 142 may also determine that the camera lane lines and map lane lines are incorrect, for example, if the degree of match is smaller than a lower limit value that is smaller than a threshold value.

[0067] Here, for example, when the first recognition unit 132 recognizes multiple camera lane markings on one side of the camera lane markings CL1, CL2 on both the left and right sides of the vehicle M's driving lane L1, and a first camera lane marking included in the multiple recognized camera lane markings matches a map lane marking ML and satisfies a predetermined condition, the determination unit 142 reduces the reliability of the matching information between the matching first camera lane marking and the second lane marking. The matching information is, for example, the degree of match, and reducing the reliability means, for example, reducing the degree of match. The matching information may also be the result of determining whether the lane markings are correct or incorrect.

[0068] In the example of FIG. 3, of the camera lane lines CL1 and CL2, the camera lane line CL2 on one side is recognized as having two branches, and of the multiple recognized camera lane lines CL2a and CL2b, the camera lane line CL2a, which is the first one-side camera lane line, matches the map lane line ML2 (the degree of match is equal to or greater than a threshold). In this case, if a predetermined condition is further satisfied, the determination unit 142 reduces the degree of match between the camera lane line CL2a and the map lane line ML2, making it less likely that the map lane line ML2 is determined to be the correct lane line. The determination unit 142 may also reduce the reliability of the result of the correct / incorrect determination. If the reliability of the determination result is reduced, the determination unit 142 does not determine that the map lane line ML2 is the correct lane line.

[0069] The predetermined condition is, for example, that another vehicle m1, m2 traveling ahead of the host vehicle M has passed over the map lane line ML2 (or the camera lane line CL2a) that has been determined to match. "Passing" means that a predetermined position (e.g., the center, center of gravity, or tip) of the other vehicle m1, m2 or the entire vehicle body crosses (or straddles) the map lane line ML2 and moves into another lane (adjacent lane), etc. Whether or not the other vehicle m1, m2 has passed over the map lane line ML2 may be determined, for example, from the behavior of the other vehicle m1, m2 or based on the traveling trajectories K1, K2. In this way, when the other vehicle m1, m2 has passed over a lane that has been determined to match, it is highly likely that the lane along the lane line is not the correct lane. Therefore, by reducing the reliability of the matching information, erroneous determination of the lane line or road shape can be suppressed.

[0070] The above-mentioned predetermined condition may include a condition that a predetermined number or more of other vehicles traveling ahead of the host vehicle M have passed over the map lane line ML2 (or the camera lane line CL2a). For example, if only one other vehicle passes over the map lane line ML2, there is a possibility that the other vehicle has changed lanes from lane L1 to lane L2. Therefore, by including the condition that a predetermined number of two or more other vehicles have passed, the lane line or road shape can be determined more accurately. The above-mentioned predetermined condition may also include a condition that all other vehicles traveling ahead of the host vehicle M and in the lane (lane L1) in which the host vehicle M is traveling have passed over the map lane line ML2 (or the camera lane line CL2a).

[0071] The predetermined condition may include, for example, the vehicle M traveling within a predetermined distance range before a construction site (or a no-travel area AR1 that includes the construction site). The construction site may be a construction site where construction is currently underway, or a construction site where construction was previously underway (a predetermined time ago). Whether or not construction is currently underway is determined, for example, from road signs or billboards indicating construction, construction vehicles, construction workers, physical road boundaries (described later), and the like, which are recognized by the first recognition unit 132. Whether or not construction was previously underway is determined, for example, by obtaining a construction history of the surrounding area based on the position information of the vehicle M from a server or the like that manages construction history, via the communication device 20 or the like. During construction or for a predetermined period after construction, there is a high possibility that temporarily drawn lane markings remain in the road environment. Therefore, by reducing the reliability of the matching information in this case, erroneous determination of lane markings (road shapes based on lane markings) can be suppressed.

[0072] For example, when the reliability of the matching information is reduced due to the above-described conditions being satisfied and there is a single-side camera lane marking among the multiple recognized single-side camera lane marks that does not match a map lane marking, the execution control unit 144 may execute driving control to cause the host vehicle M to travel along the single-side camera lane marking. In the example of FIG. 3, among the multiple recognized single-side camera lane marks CL2a and CL2b, the second single-side camera lane marking, CL2b, does not match any of the map lane marks ML1 to ML3. Therefore, in the section where the camera lane marking CL2 branches off, the execution control unit 144 generates a target trajectory so that the host vehicle M travels along the camera lane marking CL2b and causes the host vehicle M to travel along the generated target trajectory. Because the camera lane marking CL2b is likely to be a new lane marking drawn due to construction work, causing the host vehicle M to travel along the camera lane marking, thereby enabling autonomous driving control of the host vehicle M to continue.

[0073] In this way, according to the first scenario, even if information about construction (road information during or after construction) is not reflected in map information during or after construction, for example, it is possible to suppress erroneous determination of lane markings (road shapes based on lane markings). Furthermore, because traveling along an incorrect route is suppressed, it is possible to suppress the activation of automatic brakes and the execution of control to switch from automatic driving to manual driving, and driving control can be continued.

[0074] [Second Scene] FIG. 4 is a diagram illustrating the determination process and driving control in a second scenario. The example of FIG. 4 differs from the first scenario shown in FIG. 3 in that there are no other vehicles around the host vehicle M and that a road physical boundary RPB exists. The road physical boundary RPB is, for example, a boundary for dividing a lane by an object OB (e.g., a fence, a safety fence, a barricade, or a pylon (registered trademark)) installed on the road, which is different from the lane markings pre-drawn on the road. The road physical boundary RPB is installed, for example, to prevent vehicles from entering a no-travel area. There may be multiple objects OB, or multiple objects OB may be arranged or connected. In the example of FIG. 4, as viewed from the host vehicle M, a road physical boundary RPB1 exists along a lane marking line RL1 up to point P1, a road physical boundary RPB2 exists along a lane marking line RL4 from point P1 to point P2, and a road physical boundary RPB3 exists along a lane marking line RL2 from point P2 onward. The road physical boundaries RPB1 to RPB3 may be connected or integrated physical boundaries.

[0075] In the second scenario, the first recognition unit 132 recognizes multiple lane markings on one side of the lane markings CL1 and CL2 on both the left and right sides of the lane L1 of the host vehicle M, and if a first lane marking on one side of the lane markings matches a map lane marking ML and satisfies a predetermined condition, the determination unit 142 reduces the reliability of the matching information between the matching first lane marking and the second lane marking. Here, the predetermined condition in the second scenario is, for example, the presence of a road physical boundary RPB (RPB1 to RPB3) in the traveling direction of the host vehicle M. For example, as shown in the road physical boundary RPB2 in FIG. 4, it is highly likely that at least a portion of the road physical boundary RPB is not aligned with the map lane markings ML1 to ML3 registered in the map information. Therefore, the road physical boundary RPB does not match the map lane marking (the degree of match with the map lane marking is low). Therefore, by including as a predetermined condition that the road physical boundary RPB exists in the traveling direction of the host vehicle M, the determination unit 142 can suppress erroneous determination of the lane markings (road shape based on the lane markings).

[0076] In a second scenario, when a road physical boundary RPB exists that extends in a direction that differs by a predetermined angle or more from the extension direction of the matched camera lane marking CL2a and map lane marking ML2, the executive control unit 144 may execute driving control to cause the host vehicle M to travel along the road physical boundary RPB. In the example of FIG. 4, the road physical boundary RPB2 extends in a direction that differs by a predetermined angle or more from the extension direction of the matched camera lane marking CL2a and map lane marking ML2. In this case, the executive control unit 144 generates a target trajectory K11 so that the host vehicle M travels along the road physical boundary RPB2 in the section from points P1 to P2 where the road physical boundary RPB2 exists, and causes the host vehicle M to travel along the generated target trajectory K11.

[0077] In this way, according to the second scenario, by determining that the direction in which the road physical boundary RPB is positioned is a direction in which driving is possible while avoiding entering no-driving areas, including construction sites, and driving along the road physical boundary RPB, it is possible to suppress erroneous judgments about dividing lines (road shapes based on dividing lines) and to continue driving control.

[0078] The determination unit 142 may determine whether the camera lane marking CL is correct or not based on the road physical boundary RPB. In this case, for example, if multiple camera lane marks on one side are recognized and one of them (e.g., a camera lane marking that does not match a map lane marking) extends along the extension direction of the road physical boundary RPB (or parallel to the extension direction of the road physical boundary RPB), the determination unit 142 determines that the camera lane marking CL2b is the correct lane marking. In the example of FIG. 4, the camera lane marking CL2b, which is the second one-side camera lane marking that does not match a map lane marking, extends along the extension direction of the road physical boundary RPB2, so the determination unit 142 determines that the camera lane marking CL2b is the correct lane marking.

[0079] If it is determined that the camera lane marking CL2b is a correct lane marking, the execution control unit 144 generates a target trajectory for the host vehicle M to travel along the camera lane marking CL2b, and causes the host vehicle M to travel along the generated target trajectory. Here, as described above, when traveling along the road physical boundary RPB, the host vehicle M needs to travel at a position spaced a predetermined distance from the road physical boundary RPB to avoid contact between the road physical boundary RPB and the host vehicle M. However, even if the camera lane marking CL2b comes into contact with the host vehicle M (for example, even if the host vehicle M travels on the camera lane marking CL2b), there is no significant impact. Therefore, by generating a target trajectory K12 for traveling the host vehicle M along the camera lane marking CL2b, the execution control unit 144 can generate the target trajectory K12 at a position farther from the road physical boundary RPB2 than the target trajectory K11, thereby allowing the host vehicle M to travel more safely.

[0080] If the distance between the camera lane marking CL2b and the road physical boundary RPB2 is short (less than a predetermined distance), the executive control unit 144 may adjust the position of the camera lane marking CL2b and then perform driving control to cause the host vehicle M to travel along the camera lane marking CL2b. In this case, the executive control unit 144 adjusts the position of the camera lane marking CL2b so that the distance between the camera lane marking CL2b and the road physical boundary RPB2 is equal to or greater than the predetermined distance. The predetermined distance is, for example, a distance (which may further include a predetermined safety margin) at which the host vehicle M does not come into contact with the road physical boundary RPB2 even when a predetermined position (e.g., the right side, center, or center of gravity) of the host vehicle M is traveling on the camera lane marking CL2b. The predetermined distance may be a fixed distance or may be variably set based on the vehicle width of the host vehicle M or the width of the lane L1.

[0081] In this way, even if the camera lane marking CL2b and the road physical boundary RPB2 are close to each other, by adjusting the position of the camera lane marking CL2b, it is possible to generate a target trajectory K12 that will allow the host vehicle M to travel at a position that does not come into contact with the road physical boundary RPB2, and to travel along this target trajectory K12. Furthermore, because the host vehicle M can travel at a position away from the road physical boundary RPB2, it is possible to prevent the occupants of the host vehicle M from feeling anxious about the possibility of coming into contact with the road physical boundary RPB2.

[0082] Furthermore, instead of generating a target trajectory based on the camera lane markings CL2b as described above, the execution control unit 144 may generate a target trajectory based on the camera lane markings CL1 and cause the host vehicle M to travel along the generated target trajectory. In this case, the execution control unit 144 generates the target trajectory using, for example, a portion of the camera lane markings CL1 that does not match and deviates from the map lane markings ML1 but that is along the road physical boundary RPB2. This allows adjustments to ensure that the host vehicle M travels at a position reliably away from the road physical boundary RPB2. In this way, in the embodiment, a target trajectory can be generated for a more appropriate position (for example, a position away from the road physical boundary) using the camera lane markings CL2b that are on the same side as the determined matching side or a portion of the camera lane markings CL1 on the side not determined to match (the side that was once excluded), and the host vehicle M can travel along the target trajectory.

[0083] Furthermore, in the second scenario, when the host vehicle M is traveling on a road (lane L1) having a gradient equal to or greater than a predetermined value, the execution control unit 144 may not execute driving control based on the road physical boundary RPB. The road gradient may be acquired from the second map information 62 based on the position information of the host vehicle M, or may be acquired based on the inclination (inclination angle) of the host vehicle M detected by the vehicle sensor 40. When the host vehicle M is traveling on a sloped road, the recognition accuracy of the position, shape, size, etc. of the road physical boundary RPB (object OB) decreases compared to when the host vehicle M is traveling on a flat road. Therefore, when the host vehicle M is traveling on a road having a gradient equal to or greater than a predetermined value, the execution control unit 144 does not generate a target trajectory for driving the host vehicle M along the road physical boundary RPB. This makes it possible to prevent driving control based on an incorrect target trajectory from being executed when traveling on a slope.

[0084] In addition, when the vehicle M is traveling on a road (lane L1) with a gradient of a predetermined value or more, instead of performing driving control based on the road physical boundary RPB, it is possible not to determine whether the dividing line is correct or incorrect based on the road physical boundary RPB.

[0085] According to the second scenario described above, for example, even in a situation where there are no other vehicles in the vicinity, it is possible to suppress erroneous determination of the lane markings (road shape based on lane markings) based on the road physical boundary RPB. Furthermore, it is possible to continue driving control by generating a target trajectory at an appropriate position based on the road physical boundary RPB and causing the host vehicle M to travel along the generated target trajectory.

[0086] [Scene 3] Fig. 5 is a diagram for explaining the determination process and driving control in the third scene. The example of Fig. 5 differs from the second scene shown in Fig. 4 in that there is sign information indicating the presence of a construction site in the traveling direction of the host vehicle M. The sign information is, for example, a road sign RS or a signboard SB. Therefore, the following explanation will mainly focus on the above difference.

[0087] For example, at a road construction site, as shown in FIG. 5, road signs RS1 and RS2 and a signboard SB1 are installed before or near the construction site to notify surrounding vehicles of road construction-related information before a vehicle arrives at the construction site. In a third scenario, the first recognition unit 132 recognizes the road signs RS1 and RS2 and the signboard SB1 in addition to the camera lane markings CL and the road physical boundary RPB. In this case, the first recognition unit 132 may recognize the specific content of the road signs RS1 and RS2 and the signboard SB1 from feature information such as the shape, pattern, text information, and color information of the road signs RS1 and RS2 and the signboard SB1 contained in the camera image. The first recognition unit 132 may also recognize the distance to the construction site from the type and installation location of the road signs RS1 and RS2 and the signboard SB1.

[0088] In the third scenario, similar to the second scenario, the first recognition unit 132 recognizes multiple camera lane markings on one side of the camera lane markings CL1 and CL2 on both the left and right sides of the vehicle M's driving lane L1, and if a first camera lane marking included in the multiple recognized camera lane markings matches a map lane marking ML and satisfies a predetermined condition (i.e., if a road physical boundary RPB exists in the direction of travel of the vehicle M), the determination unit 142 reduces the reliability of the matching information between the matching first camera lane marking and the second lane marking. In this case, if a construction site is predicted to exist within a predetermined distance in the direction of travel of the vehicle M based on the recognition results of road signs RS1 and RS2 and signboard SB1 by the first recognition unit 132, the execution control unit 144 performs driving control to cause the vehicle M to travel along the road physical boundary RPB.

[0089] In this way, according to the third scenario, the presence of a construction site can be more accurately determined from surrounding sign information. Therefore, when a road physical boundary RPB is present in the traveling direction of the vehicle M and sign information indicating a construction site is present, driving control is performed based on the road physical boundary RPB rather than the camera lane markings CL or the map lane markings ML, thereby enabling efficient driving control to be performed with priority given to the road physical boundary RPB.

[0090] [About operation control] Here, the driving control by the driving control unit will be described. The execution control unit 144 determines driving control for the host vehicle M based on the determination result by the determination unit 142, and executes the determined driving control. "Determining driving control" may include, for example, determining the content (type) of driving control and determining whether to execute (suppress) driving control. "Executing driving control" may include, for example, switching and executing the content of driving control, as well as continuing driving control that is already being executed. "Suppressing driving control" may include not only not executing (terminating) driving control, but also lowering the automation level of driving control. Furthermore, the driving control executed by the execution control unit 144 may include ACC, TJP, LKAS, ALC, CMBS, etc., and may also include various other driving controls for avoiding contact with surrounding vehicles. The execution control unit 144 generates a target trajectory for executing driving control and outputs the generated target trajectory to the second control unit 160.

[0091] Here, the driving control executed by the execution control unit 144 includes at least a first driving control and a second driving control. The first driving control is, for example, driving control that controls one or both of the steering and the speed of the host vehicle M based on a lane marking (e.g., a lane marking where a camera lane marking and a map lane marking coincide) recognized by the first recognition unit 132 or the second recognition unit 134. For example, the first driving control is driving control that causes the host vehicle M to travel so that a representative point of the host vehicle M passes through the center of a lane marked by lane markings. The second driving control is, for example, driving control that controls one or both of the steering and the speed of the host vehicle M based on map lane markings and traveling position information of other vehicles. For example, the second driving control is driving control that causes the host vehicle M to travel so that a representative point of the host vehicle M travels on a trajectory that follows the traveling trajectory of the other vehicle m1.

[0092] Furthermore, the driving control may include a third driving control in which at least steering control of the vehicle M is performed, either steering or speed, while giving priority to camera lane lines over map lane lines, and a fourth driving control in which at least steering control of the vehicle M is performed, either steering or speed, while giving priority to map lane lines over camera lane lines. Prioritizing camera lane lines over map lane lines means, for example, that processing is basically performed based on the camera lane lines, but temporarily switches to processing based on the map lane lines when, for example, the recognition accuracy of the camera lane lines falls below a threshold or they become unrecognizable. Prioritizing map lane lines over camera lane lines means, for example, that processing is basically performed based on the map lane lines, but temporarily switches to processing based on the camera lane lines when, for example, the map lane lines cannot be identified. The third driving control and the fourth driving control are driving controls, for example, when the camera lane lines and the map lane lines do not match (when the degree of match is less than a threshold).

[0093] Furthermore, the driving control may include multiple driving control measures based on automation levels (an example of the degree of automation). The automation levels may include, for example, a first level, a second level with a lower degree of automation of driving control than the first level, and a third level with a lower degree of automation of driving control than the second level. The automation levels may also include a fourth level with a lower degree of automation of driving control than the third level. Here, the automation level may be a level determined by standardized information, laws and regulations, or an index value set independently. Therefore, the types, contents, and number of automation levels are not limited to the following examples. A low degree of automation of driving control means, for example, a low automation rate in driving control and a large (heavy) task assigned to the driver. A low degree of automation of driving control means a low degree of control of the steering or acceleration / deceleration of the host vehicle M by the automatic driving control device 100 (a high degree of need for the driver to intervene in steering or acceleration / deceleration operations). Tasks assigned to the driver include, for example, monitoring the surroundings of the host vehicle M and operating driving controls. The operation of the driving controls includes, for example, the driver gripping the steering wheel (hereinafter referred to as a hands-on state). The tasks assigned to the driver are, for example, tasks for the occupant (driver tasks) necessary to maintain the autonomous driving of the host vehicle M. Therefore, if the occupant is unable to perform the assigned tasks, the automation level will be reduced. For example, the first level of driving control may include driving controls such as ACC, ALC, LKAS, TJP, etc. Furthermore, the second or third level of driving control may include driving controls such as ACC, ALC, LKAS, etc. Furthermore, the fourth level of driving control may include manual driving. Furthermore, the fourth level of driving control may include driving controls such as ACC, etc. Of the first to fourth levels, the first level has the highest degree of automation of driving control, and the fourth level has the lowest degree of automation of driving control.

[0094] Furthermore, at the first level, no tasks are assigned to the occupant (the driver has the lightest tasks). At the second level, the task assigned to the occupant is, for example, monitoring the surroundings (particularly ahead) of the vehicle M. At the third level, the task assigned to the occupant includes, for example, monitoring the surroundings of the vehicle M as well as being in a hands-on state. At the fourth level, the task assigned to the occupant (e.g., the driver) is, for example, monitoring the surroundings of the vehicle M and being in a hands-on state, as well as operating the driving operator 80 to control the steering and speed of the vehicle M. In other words, at the fourth level, the occupant is ready to immediately take over driving, and the driver has the most severe tasks. The content of driving control and the tasks assigned to the occupant at each automation level are not limited to the examples described above. The automatic driving control device 100 executes driving control at one of the first to fourth levels based on the surrounding conditions of the vehicle M and the tasks being performed by the occupant. At least some of the first to fourth levels may be associated with the above-mentioned first to fourth operational controls, for example.

[0095] For example, when the determination unit 142 determines that both the camera lane markings CL and the map lane markings ML are correct (for example, the camera lane markings CL and the map lane markings ML match), the execution control unit 144 generates a target trajectory for executing the first driving control. Furthermore, when the determination unit 142 determines that one of the camera lane markings CL and the map lane markings ML is correct, the execution control unit 144 generates a target trajectory for executing one of the second to fourth driving controls based on the correct lane marking. Furthermore, the execution control unit 144 may perform control such as terminating driving control of the host vehicle M and switching to manual driving by the occupant based on the determination result. Furthermore, the execution control unit 144 may switch the automation level corresponding to the driving control based on the determination result. In this case, for example, when the camera lane markings CL and the map lane markings ML are determined to be correct, the first level driving control is executed, and when the camera lane markings CL and the map lane markings ML are determined to be incorrect, the second to fourth level driving control is executed depending on the situation. Furthermore, the execution control unit 144 generates a target trajectory according to each determination result in the first to third scenarios described above, and executes driving control of the host vehicle M.

[0096] [Processing flow] The following describes the processing executed by the automatic driving control device 100 of the embodiment. FIG. 6 is a flowchart showing an example of the processing executed by the automatic driving control device 100 of the embodiment. The following mainly describes the driving control processing, which includes processing to suppress erroneous determination of lane markings, among the processing executed by the automatic driving control device 100. Furthermore, the processing shown below may be repeatedly executed at a predetermined timing or at a predetermined cycle, and may be repeatedly executed while automatic driving by the automatic driving control device 100 is being performed.

[0097] 6, the first recognition unit 132 recognizes lane lines (camera lane lines) present around the host vehicle M (within a predetermined distance) based on the output of the detection device DD that detects the surrounding conditions of the host vehicle M (step S100). In the processing of step S100, the first recognition unit 132 may recognize other vehicles, physical road boundaries, sign information, obstacles, etc. present around the host vehicle. Next, the second recognition unit 134 refers to map information based on the position information of the host vehicle M, and recognizes lane lines (map lane lines) present around the host vehicle M from the map information (step S110).

[0098] Next, the determination unit 142 determines whether multiple lane markings on one side of the left and right camera lane markings that define the lane of the host vehicle M have been recognized (step S120). If it is determined that multiple lane markings have been recognized, the determination unit 142 determines whether any one of the multiple recognized lane markings (first one-side camera lane marking) matches the map lane marking (step S130). If it is determined that there is a match (for example, the degree of match is equal to or greater than a threshold), the determination unit 142 determines whether a predetermined condition is satisfied (step S140). If it is determined that the predetermined condition is satisfied, the determination unit 142 reduces the reliability of the match between the first one-side camera lane marking and the map lane marking (step S150).

[0099] Next, the determination unit 142 determines whether or not there is a one-side camera lane marking (second one-side camera lane marking) among the multiple recognized one-side camera lane marks that does not match a map lane marking (the degree of match is less than a threshold) (step S160). If a second one-side camera lane marking is present, the execution control unit 144 executes driving control to cause the host vehicle M to travel along the second one-side camera lane marking (step S170). Furthermore, if it is determined in the processing of step S120 that multiple one-side camera lane marks have not been recognized, if it is determined in the processing of step S130 that the multiple one-side camera lane marks do not match the map lane marking, if it is determined in the processing of step S140 that a predetermined condition is not satisfied, or if it is determined in the processing of step S160 that a second one-side camera lane marking does not exist, the execution control unit 144 suppresses driving control of the host vehicle M (step S180). Suppressing the operation control includes, for example, switching from the first operation control to any of the second to fourth operation controls, ending the first operation control, not executing the operation control when the operation control is not being executed, lowering the automation level, etc. This ends the flow chart.

[0100] In an embodiment, instead of the processing of step S160 shown in FIG. 6, it may be determined whether or not a road physical boundary exists in the traveling direction of the host vehicle M, and if it is determined that a road physical boundary exists, instead of the processing of step S170, driving control may be executed to cause the host vehicle M to travel along the road physical boundary.

[0101] [Variations] For example, in the above-described embodiment, the determination unit 142 may determine the degree of deviation instead of determining the degree of match between the camera lane markings (or the driving trajectory) and the map lane markings. The degree of deviation is, for example, an index value that increases as the difference in the amount of deviation, the deviation angle, or the amount of curvature change between the camera lane markings and the map lane markings increases. Also, in the embodiment, even if another vehicle is present around (ahead of) the host vehicle M, the determination unit 142 may determine whether the lane markings are correct or not, or generate a target trajectory for the host vehicle M to travel, based on physical road boundaries and sign information. Also, in the embodiment, when three or more camera lane markings on at least one side are recognized, the determination unit 142 may determine whether each camera lane marking is matched with the map lane marking. Also, when a predetermined number or more camera lane markings on one side are recognized, the determination unit 142 may not perform a match determination, assuming that the recognition accuracy has deteriorated.

[0102] According to the above-described embodiment, the automatic driving control device 100 (an example of a vehicle control device) is equipped with a first recognition unit 132 that recognizes the surrounding conditions, including camera marking lines (an example of first marking lines) that mark the lane of travel of the vehicle M and other vehicles present around the vehicle, based on the output of a detection device DD that detects the surrounding conditions of the vehicle M; a second recognition unit 134 that recognizes map marking lines (an example of second marking lines) that mark the lanes around the vehicle from map information based on the position information of the vehicle M; and a judgment unit 142 that judges whether the first marking lines and the second marking lines match.When the first recognition unit 132 recognizes multiple camera marking lines on one side of the camera marking lines present on the left and right sides of the vehicle M, and a first one-side camera marking line included in the recognized multiple one-side camera marking lines matches a map marking line and satisfies predetermined conditions, the judgment unit 142 reduces the reliability of the matching information between the matching first one-side camera marking line and the map marking line, thereby suppressing erroneous judgment of marking lines based on the surrounding conditions of the vehicle. Therefore, more appropriate driving control can be performed according to the recognition result of the surroundings of the vehicle. Furthermore, according to the embodiment, the continuity of driving control can be further improved, which can contribute to the development of a sustainable transportation system.

[0103] Furthermore, according to the embodiment, even when the camera lane markings on one side and the map lane markings match, it is possible to more accurately suppress erroneous determinations by determining whether the lane markings are correct or not based on the driving trajectory of other vehicles, physical road boundaries, etc. Furthermore, according to the embodiment, by performing the above-described control when a construction site or the like is present in the traveling direction, it is possible to suppress erroneous determinations even in road conditions that are prone to erroneous determinations of lane markings or road shapes, such as when lane markings are temporarily drawn to allow the vehicle to avoid the construction site, old lane markings before they were changed by construction remain, or lane markings have been redrawn, and it is possible to execute (continue) driving control using more appropriate information.

[0104] The above-described embodiment can be expressed as follows. a storage medium for storing computer-readable instructions; a processor connected to the storage medium; The processor executes the computer-readable instructions to: Based on an output from a detection device that detects a surrounding situation of the host vehicle, the surrounding situation including a first dividing line that divides the lane in which the host vehicle is traveling and other vehicles that exist around the host vehicle is recognized; Recognizing second lane markings that demarcate lanes around the vehicle from map information based on the position information of the vehicle; determining whether the first demarcation line and the second demarcation line coincide with each other; a plurality of first demarcation lines on one side of the vehicle are recognized, and when a first one-side first demarcation line included in the plurality of recognized one-side first demarcation lines matches the second demarcation line and satisfies a predetermined condition, the reliability of the matching information between the matched first one-side first demarcation line and the second demarcation line is reduced; Operation control device.

[0105] 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]

[0106] 1...vehicle system, 10...camera, 12...radar device, 14...LIDAR, 16...object recognition device, 20...communication device, 30...HMI, 40...vehicle sensor, 50...navigation device, 60...MPU, 80...driving operator, 100...automatic driving control device, 120...first control unit, 130...recognition unit, 132...first recognition unit, 134...second recognition unit, 140...action plan generation unit, 142...determination unit, 144...execution control unit, 160...second control unit, 162...target trajectory acquisition unit, 164...speed control unit, 166...steering control unit, 180...HMI control unit, 190...memory unit, 200...driving force output device, 210...brake device, 220...steering device, M...host vehicle

Claims

1. a first recognition unit that recognizes a surrounding situation including a first dividing line that divides the lane in which the host vehicle is traveling and other vehicles that exist around the host vehicle based on an output of a detection device that detects a surrounding situation of the host vehicle; a second recognition unit that recognizes second lane markings that demarcate lanes around the host vehicle from map information based on the position information of the host vehicle; a determination unit that determines whether the first demarcation line and the second demarcation line coincide with each other, When the first recognition unit recognizes a plurality of first demarcation lines on one side among the first demarcation lines present on the left and right sides of the vehicle, a first one-side first demarcation line included in the recognized plurality of one-side first demarcation lines matches the second demarcation line, and a predetermined condition is satisfied, the determination unit reduces the reliability of matching information between the matched first one-side first demarcation line and the second demarcation line. Vehicle control device.

2. the predetermined condition includes the other vehicle passing over the first one-side first marking line that is determined to coincide with the second marking line; The vehicle control device according to claim 1 .

3. a driving control unit that controls one or both of the steering and the speed of the host vehicle based on the determination result by the determination unit, and executes driving control; When a second one-side first demarcation line is present that is determined by the determination unit not to match the second demarcation line among the plurality of one-side first demarcation lines recognized by the first recognition unit, the driving control unit controls the traveling of the host vehicle based on the second one-side first demarcation line. The vehicle control device according to claim 1 .

4. The predetermined condition includes that the vehicle is traveling within a predetermined distance range before a point under construction or a point where construction has been carried out in the past. The vehicle control device according to claim 1 .

5. the predetermined condition includes a condition that a road physical boundary exists in the traveling direction of the host vehicle. The vehicle control device according to claim 1 .

6. a driving control unit that controls one or both of the steering and the speed of the host vehicle based on the determination result by the determination unit, and executes driving control; the driving control unit, when there is a road physical boundary extending in a direction different from the first one-side first demarcation line and the second demarcation line that match, causes the host vehicle to travel along the road physical boundary. The vehicle control device according to claim 1 .

7. the determination unit determines that the second one-side first demarcation line is a correct demarcation line when the second one-side first demarcation line extends along a road physical boundary; the driving control unit causes the host vehicle to travel along the second one-side first dividing line, The vehicle control device according to claim 3.

8. the driving control unit adjusts a position of the second one-side first dividing line along a direction in which a road physical boundary extends, and causes the host vehicle to travel along the adjusted position of the second one-side first dividing line; The vehicle control device according to claim 7.

9. the driving control unit adjusts a position of the second one-side first dividing line when a distance between the road physical boundary and the second one-side first dividing line is less than a predetermined distance; The vehicle control device according to claim 8.

10. the driving control unit does not execute driving control based on the road physical boundary when the host vehicle is traveling on a lane having a gradient equal to or greater than a predetermined value. The vehicle control device according to claim 6.

11. the driving control unit causes the host vehicle to travel along the road physical boundary when sign information indicating a construction site is present in the traveling direction of the host vehicle. The vehicle control device according to claim 6.

12. The computer Based on an output from a detection device that detects a surrounding situation of the host vehicle, the surrounding situation including a first dividing line that divides the lane in which the host vehicle is traveling and other vehicles present around the host vehicle is recognized; recognizes second lane markings that demarcate lanes around the vehicle from map information based on the position information of the vehicle; determining whether the first demarcation line and the second demarcation line coincide with each other; a plurality of first demarcation lines on one side of the vehicle are recognized, and when a first one-side first demarcation line included in the plurality of recognized one-side first demarcation lines matches the second demarcation line and satisfies a predetermined condition, the reliability of the matching information between the matched first one-side first demarcation line and the second demarcation line is reduced; Vehicle control method.

13. On the computer, Based on an output from a detection device that detects a surrounding situation of the host vehicle, the surrounding situation including a first dividing line that divides the lane in which the host vehicle is traveling and other vehicles present around the host vehicle is recognized; recognizes second lane markings that demarcate lanes around the vehicle from map information based on the position information of the vehicle; determining whether the first demarcation line and the second demarcation line coincide with each other; a plurality of first demarcation lines on one side of the vehicle are recognized, and when a first one-side first demarcation line included in the plurality of recognized one-side first demarcation lines matches the second demarcation line and satisfies a predetermined condition, the reliability of the matching information between the matched first one-side first demarcation line and the second demarcation line is reduced; program.

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