WO2021102957A1 - Procédé de suivi de voie, dispositif embarqué, et support de stockage - Google Patents

Procédé de suivi de voie, dispositif embarqué, et support de stockage Download PDF

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Publication number
WO2021102957A1
WO2021102957A1 PCT/CN2019/122100 CN2019122100W WO2021102957A1 WO 2021102957 A1 WO2021102957 A1 WO 2021102957A1 CN 2019122100 W CN2019122100 W CN 2019122100W WO 2021102957 A1 WO2021102957 A1 WO 2021102957A1
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WIPO (PCT)
Prior art keywords
vehicle
lane
information
line
path
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PCT/CN2019/122100
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English (en)
Chinese (zh)
Inventor
胡子豪
王子涵
刘洋
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驭势（上海）汽车科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by 驭势（上海）汽车科技有限公司 filed Critical 驭势（上海）汽车科技有限公司
Priority to CN201980002776.8A priority Critical patent/CN113677581B/xx
Priority to PCT/CN2019/122100 priority patent/WO2021102957A1/fr
Publication of WO2021102957A1 publication Critical patent/WO2021102957A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/14—Adaptive cruise control
    • B60W30/16—Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
    • B60W30/165—Automatically following the path of a preceding lead vehicle, e.g. "electronic tow-bar"

Definitions

  • the embodiments of the present disclosure relate to the technical field of intelligent driving, and in particular to a lane keeping method, vehicle-mounted equipment, and storage medium.
  • At least one embodiment of the present disclosure provides a lane keeping method, an in-vehicle device, and a storage medium.
  • an embodiment of the present disclosure proposes a lane keeping method, including:
  • the embodiments of the present disclosure also provide a vehicle-mounted device, including: a processor and a memory; the processor is used to execute the steps of the method described in the first aspect by calling a program or instruction stored in the memory.
  • the embodiments of the present disclosure also propose a non-transitory computer-readable storage medium for storing a program or instruction, and the program or instruction causes a computer to execute the steps of the method described in the first aspect.
  • FIG. 1 is an overall architecture diagram of an intelligent driving vehicle provided by an embodiment of the present disclosure
  • Fig. 2 is a block diagram of an intelligent driving system provided by an embodiment of the present disclosure
  • Fig. 3 is a block diagram of a lane keeping module provided by an embodiment of the present disclosure.
  • FIG. 4 is a block diagram of a vehicle-mounted device provided by an embodiment of the present disclosure.
  • FIG. 5 is a flowchart of a lane keeping method provided by an embodiment of the present disclosure.
  • Fig. 6 is a schematic diagram of a traffic jam condition provided by an embodiment of the present disclosure.
  • the traffic jam conditions are common and complex conditions.
  • 101 is the vehicle
  • 102 to 107 are surrounding vehicles
  • 108 and 109 are lane lines.
  • the embodiments of the present disclosure provide a lane keeping solution suitable for traffic congestion conditions, and improve the safety of driving under traffic congestion conditions.
  • FIG. 1 is an overall architecture diagram of an intelligent driving vehicle provided by an embodiment of the disclosure.
  • the intelligent driving vehicle includes: a sensor group, an intelligent driving system 100, a vehicle underlying execution system, and other components that can be used to drive the vehicle and control the operation of the vehicle.
  • the sensor group is used to collect the data of the external environment of the vehicle and detect the position data of the vehicle.
  • the sensor group includes, but is not limited to, at least one of a camera, a lidar, a millimeter wave radar, an ultrasonic radar, a GPS (Global Positioning System, global positioning system), and an IMU (Inertial Measurement Unit), for example.
  • the sensor group is also used to collect dynamics data of the vehicle.
  • the sensor group further includes, but is not limited to, at least one of a wheel speed sensor, a speed sensor, an acceleration sensor, a steering wheel angle sensor, and a front wheel angle sensor, for example.
  • the intelligent driving system 100 is used to obtain data of a sensor group, and all sensors in the sensor group transmit data at a higher frequency during the driving of the intelligent driving vehicle.
  • the intelligent driving system 100 is also used for environmental perception and vehicle positioning based on the data of the sensor group, path planning and decision-making based on environmental perception information and vehicle positioning information, and generating vehicle control instructions based on the planned path, thereby controlling the vehicle according to the plan Route driving.
  • the intelligent driving system 100 is also used to obtain environmental information around the vehicle; and then determine lane-changing information of vehicles around the vehicle based on the environmental information; thereby determining the vehicle’s lane-changing information based on the environmental information and lane-changing information Bear mode; based on the follow mode, plan the driving path; control the vehicle to follow the driving path.
  • the intelligent driving system 100 may be a software system, a hardware system, or a combination of software and hardware.
  • the intelligent driving system 100 is a software system that runs on an operating system
  • the on-board hardware system is a hardware system that supports the operation of the operating system.
  • the intelligent driving system 100 is also used for wireless communication with a cloud server to exchange various information.
  • the intelligent driving system 100 and the cloud server perform wireless communication through wireless communication networks (for example, including but not limited to wireless communication networks such as GPRS network, Zigbee network, Wifi network, 3G network, 4G network, 5G network, etc.).
  • the cloud server is used to coordinate the management of intelligent driving vehicles. In some embodiments, the cloud server may be used to interact with one or more intelligent driving vehicles, to coordinate and manage the scheduling of multiple intelligent driving vehicles, and so on.
  • the cloud server is a cloud server established by a vehicle service provider to provide cloud storage and cloud computing functions.
  • the vehicle file is created in the cloud server.
  • various information uploaded by the intelligent driving system 100 is stored in the vehicle file.
  • the cloud server can synchronize the driving data generated by the vehicle in real time.
  • the cloud server may be a server or a server group.
  • Server groups can be centralized or distributed. Distributed server is conducive to task allocation and optimization among multiple distributed servers, and overcomes the shortcomings of traditional centralized server resource shortage and response bottleneck.
  • the cloud server may be local or remote.
  • the cloud server can be used to charge vehicles for parking, tolls, etc. In some embodiments, the cloud server is also used to analyze the driving behavior of the driver and evaluate the safety level of the driving behavior of the driver.
  • the cloud server may be used to obtain information about the road side unit (RSU: Road Side Unit) and the intelligent driving vehicle, and may send the information to the intelligent driving vehicle.
  • the cloud server may send the detection information corresponding to the intelligent driving vehicle in the road monitoring unit to the intelligent driving vehicle according to the information of the intelligent driving vehicle.
  • the road monitoring unit may be used to collect road monitoring information.
  • the road monitoring unit may be an environmental sensor, such as a camera, a lidar, etc., or a road device, such as a V2X device, a roadside traffic light device, and the like.
  • the road monitoring unit may monitor the road conditions subordinate to the corresponding road monitoring unit, for example, the type, speed, priority level, etc. of passing vehicles. After the road monitoring unit collects the road monitoring information, the road monitoring information can be sent to the cloud server, or can be sent to the intelligent driving vehicle passing the road.
  • the bottom-level execution system of the vehicle is used to receive vehicle control instructions to control the driving of the vehicle.
  • the vehicle bottom-level execution system includes, but is not limited to: a steering system, a braking system, and a driving system.
  • the steering system, braking system, and drive system are mature systems in the vehicle field and will not be repeated here.
  • the intelligent driving vehicle may further include a vehicle CAN bus not shown in FIG. 1, and the vehicle CAN bus is connected to the underlying execution system of the vehicle.
  • the information interaction between the intelligent driving system 100 and the underlying execution system of the vehicle is transmitted through the vehicle CAN bus.
  • the intelligent driving vehicle can be controlled by the driver and the intelligent driving system 100 to control the vehicle.
  • the driver drives the vehicle by operating a device that controls the traveling of the vehicle.
  • the devices that control the traveling of the vehicle include, but are not limited to, a brake pedal, a steering wheel, and an accelerator pedal, for example.
  • the device for controlling the driving of the vehicle can directly operate the execution system at the bottom of the vehicle to control the driving of the vehicle.
  • the intelligent driving vehicle may also be an unmanned vehicle, and the driving control of the vehicle is executed by the intelligent driving system 100.
  • FIG. 2 is a block diagram of an intelligent driving system 200 provided by an embodiment of the disclosure.
  • the smart driving system 200 may be implemented as the smart driving system 100 or a part of the smart driving system 100 in FIG. 1 for controlling the driving of the vehicle.
  • the intelligent driving system 200 can be divided into multiple modules, for example, it can include: a perception module 201, a planning module 202, a control module 203, a lane keeping module 204, and other modules that can be used for intelligent driving.
  • the perception module 201 is used for environmental perception and positioning.
  • the sensing module 201 is used to obtain data such as sensor data, V2X (Vehicle to X, wireless communication for vehicles) data, and high-precision maps.
  • the sensing module 201 is configured to perform environment perception and positioning based on at least one of acquired sensor data, V2X (Vehicle to X, vehicle wireless communication) data, and high-precision maps.
  • the perception module 201 is used to generate perception positioning information to realize obstacle perception, recognition of the drivable area of the camera image, and positioning of the vehicle.
  • Environmental Perception can be understood as the ability to understand the scene of the environment, such as the location of obstacles, the detection of road signs/marks, the detection of pedestrians/vehicles, and the semantic classification of data.
  • environment perception can be realized by fusing data from multiple sensors such as cameras, lidars, millimeter wave radars, and so on.
  • Localization is a part of perception, which is the ability to determine the position of an intelligent driving vehicle relative to the environment.
  • Positioning can be: GPS positioning, GPS positioning accuracy is tens of meters to centimeters, high positioning accuracy; positioning can also use GPS and inertial navigation system (Inertial Navigation System) positioning method.
  • Localization can also use SLAM (Simultaneous Localization And Mapping, simultaneous localization and map construction). The goal of SLAM is to construct a map while using the map for positioning. SLAM uses the observed environmental features to determine the current vehicle's location and current observation features s position.
  • V2X is the key technology of the intelligent transportation system, which enables communication between vehicles, vehicles and base stations, base stations and base stations, so as to obtain a series of traffic information such as real-time road conditions, road information, pedestrian information, etc., to improve the safety of intelligent driving and reduce Congestion, improve traffic efficiency, provide on-board entertainment information, etc.
  • High-precision maps are geographic maps used in the field of intelligent driving. Compared with traditional maps, the differences are: 1) High-precision maps include a large amount of driving assistance information, for example, relying on the accurate three-dimensional representation of the road network: including intersections and intersections. The location of road signs, etc.; 2) High-precision maps also include a lot of semantic information, such as reporting the meaning of different colors on traffic lights, and for example indicating the speed limit of the road, and the starting position of the left-turn lane; 3) The high-precision map can reach centimeters Class precision to ensure the safe driving of intelligent driving vehicles.
  • the planning module 202 is configured to perform path planning and decision-making based on the perception positioning information generated by the perception module 201.
  • the planning module 202 is configured to perform path planning and decision-making based on the perception positioning information generated by the perception module 201 in combination with at least one of V2X data, high-precision maps and other data.
  • the planning module 202 is used to plan a route and make decisions: behaviors (including but not limited to following, overtaking, stopping, detouring, etc.), vehicle heading, vehicle speed, desired acceleration of the vehicle, desired steering wheel angle And so on, generate planning decision information.
  • the control module 203 is configured to perform path tracking and trajectory tracking based on the planning decision information generated by the planning module 202.
  • control module 203 is used to generate control instructions for the vehicle's bottom-level execution system, and issue control instructions so that the vehicle's bottom-level execution system controls the vehicle to travel along a desired path, for example, by controlling the steering wheel, brakes, and accelerator to control the vehicle. Horizontal and vertical control.
  • control module 203 is also used to calculate the front wheel angle based on the path tracking algorithm.
  • the desired path curve in the path tracking process has nothing to do with time parameters.
  • tracking control it can be assumed that the intelligent driving vehicle is moving at a constant speed at the current speed, and the driving path is approached to the desired path at a certain cost rule; and the trajectory
  • the expected path curve is related to time and space, and the intelligent driving vehicle is required to reach a preset reference path point within a specified time.
  • Path tracking is different from trajectory tracking. It is not subject to time constraints and only needs to track the desired path within a certain error range.
  • the lane keeping module 204 is used to obtain environmental information around the vehicle; and then determine lane-changing information of vehicles around the vehicle based on the environmental information; thereby determining the following mode of the vehicle based on the environmental information and lane-changing information; planning based on the following mode Driving path; controlling the vehicle to drive according to the driving path.
  • the function of the lane keeping module 204 can be integrated into the perception module 201, the planning module 202 or the control module 203, or it can be configured as a module independent of the intelligent driving system 200, and the lane keeping module 204 can be a software module.
  • Hardware modules or a combination of software and hardware modules can be integrated into the perception module 201, the planning module 202 or the control module 203, or it can be configured as a module independent of the intelligent driving system 200, and the lane keeping module 204 can be a software module. , Hardware modules or a combination of software and hardware modules.
  • the lane keeping module 204 is a software module running on an operating system
  • the on-board hardware system is a hardware system that supports the running of the operating system.
  • FIG. 3 is a block diagram of a lane keeping module 300 provided by an embodiment of the disclosure.
  • the lane keeping module 300 may be implemented as the lane keeping module 204 or a part of the lane keeping module 204 in FIG. 2.
  • the lane keeping module 300 may include but is not limited to the following units: an acquisition unit 301, a first determination unit 302, a second determination unit 303, a planning unit 304 and a control unit 305.
  • the obtaining unit 301 is used to obtain environmental information around the vehicle.
  • the environmental information is information obtained through perception based on sensor data, and the environmental information may include, but is not limited to, at least one of the following: lane line information, information of the vehicle ahead of the own lane, vehicle information in the left lane of the own vehicle, and own vehicle Vehicle information in the right lane.
  • the own lane can be understood as the lane where the vehicle is located;
  • the left lane of the vehicle can be understood as the lane adjacent to and on the left side of the lane;
  • the right lane of the vehicle can be understood as being adjacent to the lane and located on the right of the lane.
  • Side lane is used to obtain environmental information around the vehicle.
  • the environmental information is information obtained through perception based on sensor data
  • the environmental information may include, but is not limited to, at least one of the following: lane line information, information of the vehicle ahead of the own lane, vehicle information in the left lane of the own vehicle, and own vehicle Vehicle information in the right
  • the lane line information may include, but is not limited to: location, line shape, and credibility.
  • the information of the vehicle in front of the lane may include, but is not limited to: the relative distance and relative speed of two vehicles in front of the lane (for example, 102 and 103 in FIG. 6) and the vehicle.
  • the vehicle information in the left lane of the own vehicle may include, but is not limited to: the relative distance and relative speed between the left neighboring vehicle (such as 104 in Figure 6) and the own vehicle, and the left front vehicle of the own vehicle (such as 105 in Figure 6) and the own vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: location, line shape, and credibility.
  • the information of the vehicle in front of the lane may include, but is not limited to: the relative distance and relative speed of two vehicles in front of the lane (for example, 102 and 103 in FIG. 6) and the vehicle.
  • the vehicle information in the left lane of the own vehicle may include, but is not limited to
  • the vehicle information in the right lane of the own vehicle may include, but is not limited to: the relative distance and relative speed between the adjacent vehicle on the right of the vehicle (e.g. 106 in Figure 6) and the vehicle, the vehicle ahead of the vehicle on the right (e.g. 107 in Figure 6) and the vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: the relative distance and relative speed between the adjacent vehicle on the right of the vehicle (e.g. 106 in Figure 6) and the vehicle, the vehicle ahead of the vehicle on the right (e.g. 107 in Figure 6) and the vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: the relative distance and relative speed between the adjacent vehicle on the right of the vehicle (e.g. 106 in Figure 6) and the vehicle, the vehicle ahead of the vehicle on the right (e.g. 107 in Figure 6) and the vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: the relative distance and relative speed between the
  • the two vehicles in front of the lane may be two vehicles directly in front of the lane.
  • the front right is relative to the front left and front right.
  • the front vehicle can be understood as a vehicle driving in the lane where the vehicle is located and located in front of the vehicle.
  • the first determining unit 302 is configured to determine lane-changing information of vehicles around the vehicle based on the environmental information.
  • the lane-changing information of vehicles around the own vehicle may include, but is not limited to: vehicle information that cuts out the lane from the vehicle in front of the lane, for example, the logo of the vehicle that cuts out of the lane from the own lane to the left lane of the own vehicle, and For example, the identification of the vehicle cut from the own lane to the right lane of the vehicle.
  • vehicle information is not limited to the identification, but may also be other information, such as the direction of lane change (left or right lane change) ).
  • cutting out the own lane can be understood as changing lanes from the own lane to the adjacent lane.
  • the adjacent lane can be understood as the left lane of the vehicle or the right lane of the vehicle.
  • the lane-changing information of the vehicles surrounding the own vehicle may include, but is not limited to: information of vehicles that cut into the own lane from the left lane of the own vehicle and the right lane of the own vehicle, for example, the identification of the vehicle that cuts into the own lane from the left lane of the own vehicle , Another example is the identification of the vehicle that cuts into the lane from the right lane of the vehicle. Among them, cutting into the own lane can be understood as changing lanes from the adjacent lane to the own lane.
  • the first determining unit 302 determines whether the lane line is valid, and determines lane-changing information of vehicles around the vehicle based on the determination result, wherein the validity or invalidity of the lane line can be determined by the existing method, and will not be repeated.
  • the effective lane line can be understood as: at least one lane line on the left and right sides exists and is of good quality. Invalid lane line can be understood as: both left and right lane lines are invalid, where invalid can be understood as: lane line is missing or poor quality.
  • the quality of the lane line is determined based on the lane line information, that is, based on the position, line shape, and credibility of the lane line.
  • the credibility is not lower than the preset range. If the reliability threshold is used, the quality of the lane line is determined to be good; otherwise, the quality of the lane line is determined to be poor.
  • the preset distance range, preset curvature range, and preset credibility threshold can be set based on actual needs, and this embodiment does not limit specific values.
  • the first determining unit 302 is based on the validity of the lane line and uses the lane line information to determine lane-changing information of vehicles around the vehicle. In some embodiments, the first determining unit 302 determines the vehicle information of the vehicle in front of the vehicle lane that cuts out of the vehicle lane based on the lane line information in the environment information and the information of the vehicle ahead of the vehicle lane. In some embodiments, the first determining unit 302 determines that the left lane of the own vehicle and the right lane of the own vehicle cut into the own lane based on the lane line information in the environment information, the vehicle information in the left lane of the own vehicle, and the vehicle information in the right lane of the own vehicle. Vehicle information.
  • the first determining unit 302 uses the motion information of the own vehicle to determine lane-changing information of vehicles around the own vehicle based on the invalid lane line.
  • the motion information of the vehicle may include, but is not limited to: vehicle speed, steering wheel angle, yaw rate, etc.
  • the first determining unit 302 determines the motion trajectory of the own vehicle based on the motion information of the own vehicle; furthermore, determines lane-changing information of vehicles around the own vehicle based on the boundary of the motion trajectory.
  • the boundary of the motion trajectory is a lateral boundary of the motion trajectory, wherein the lateral direction is a direction perpendicular to the lane line.
  • the first determining unit 302 determines the information of the vehicle that cuts out the own lane among the vehicles in front of the lane based on the lateral boundary of the motion trajectory and the information of the vehicle ahead of the lane. In some embodiments, the first determining unit 302 determines the vehicle that cuts into the own lane in the left lane of the own vehicle and the right lane of the own vehicle based on the lateral boundary of the motion trajectory, the vehicle information in the left lane of the own vehicle, and the vehicle information in the right lane of the own vehicle. information.
  • the second determining unit 303 is configured to determine the following mode of the own vehicle based on the environment information around the own vehicle and the lane-changing information of the surrounding vehicles of the own vehicle. In some embodiments, the second determining unit 303 determines lane-changing information of vehicles around the vehicle under traffic jam conditions, and makes decisions from multiple following modes for lane keeping based on the environmental information around the vehicle. A follow mode.
  • the follow mode may include, but is not limited to: a follow mode, a follow mode, and a degraded mode.
  • the following mode includes: the vehicle follows the lane line to maintain the lane; the following mode includes: the vehicle follows the vehicle directly in front to maintain the lane; the degraded mode includes: the vehicle does not follow the vehicle directly in front to cut out of the lane, and keep other vehicles in the same lane.
  • the stability of the vehicle in the lane In some embodiments, the stability of the vehicle when other vehicles cut into the lane is maintained.
  • the braking force is not greater than the preset braking force threshold
  • the steering wheel angle is not greater than the preset angle threshold
  • neither the application of braking force nor the rotation of the steering wheel are greater than the preset braking force threshold. It can be completed at one time to prevent the occurrence of vehicle shaking and instability caused by sudden braking and sudden steering.
  • the preset braking force threshold and the preset angle threshold can be set according to actual needs, and the specific values are not limited in this embodiment. It can be understood that the way to maintain the stability of the vehicle can also be other ways to prevent unstable situations such as vehicle shaking, sudden turning, and emergency stopping.
  • the second determining unit 303 determines that the following mode is the line-following mode based on that the lane line is valid and there is no lane change information. In some embodiments, the second determining unit 303 determines that the following mode is the following mode based on the invalid lane line and no lane change information. In some embodiments, the second determining unit 303 determines to follow the lane based on the lane change information including the vehicle information of the vehicle in front of the vehicle that cuts out of the lane and/or the information of the vehicle that cuts into the lane in the left lane of the vehicle and the right lane of the vehicle. The mode is degraded mode.
  • the planning unit 304 is configured to plan a travel path based on the following mode determined by the second determining unit 303. In some embodiments, the planning unit 304 plans the travel path based on the lane line information and the state of the lane line when the following mode is the line-following mode. The state of the lane line includes valid and invalid. In some embodiments, the planning unit 304 determines the lane center line based on the lane line information and the state of the lane line; and then plans the travel path based on the lane center line.
  • the planning unit 304 determines the center line of the lane based on the lane line information and the state of the lane line, specifically: if the lane lines on both sides (for example, 108 and 109 in FIG. 6) are valid, it is based on both sides.
  • the lane line generates the lane center line; if one side lane line is valid and the other side lane line is invalid, the lane center line is generated based on the effective side lane line and the lane width.
  • Method 1 Generate the lane center line directly based on the effective side lane line and lane width;
  • Method 2 First generate the invalid side lane line based on the effective side lane line and lane width, and then generate the lane center line from the effective side lane line and the invalid side lane line .
  • the vehicle can be smoothly controlled to keep driving in the current lane.
  • the planning unit 304 plans the travel path based on the environmental information when the following mode is the following mode. In some embodiments, the planning unit 304 plans the travel path based on the environmental information, specifically: determining the relative position of the vehicle in front of the lane and the vehicle as the end of the path; and then generating multiple path curves from the vehicle to the end of the path; thereby filtering The path curve that satisfies the condition is the driving path; where the condition is the maximum average distance from the vehicle surrounding the vehicle (for example, 102 to 107 in FIG. 6) from the path curve. In some embodiments, multiple path curves from the vehicle to the end of the path can be generated based on the traditional spline function generation method, which will not be repeated here. In this embodiment, when the lane lines on both sides are invalid, a new follow-up mode is added, which enables the vehicle to follow the preceding vehicle and keep driving in the current lane.
  • the planning unit 304 plans the travel path based on the movement information of the vehicle and the lane-changing information of vehicles around the vehicle when the following mode is the degraded mode. In some embodiments, the planning unit 304 uses the vehicle's motion information, historical planning path and first information of vehicles around the vehicle to plan the travel path based on the vehicle information of the vehicle ahead of the vehicle in the vehicle lane. Follow the preceding vehicle to cut out of the own lane; wherein, the first information includes: vehicle information of the vehicle in front of the lane that does not cut out of the own lane, vehicle information of the own vehicle in the left lane, and vehicle information of the own vehicle in the right lane.
  • the planning unit 304 plans the travel path based on the vehicle information in the left lane of the own vehicle and the right lane of the own vehicle that cuts into the own lane, using the movement information of the own vehicle, the historical planning path, and the second information of the surrounding vehicles of the own vehicle. , To prevent the planned route jump of the own vehicle caused by the change of the path end point; wherein, the second information includes: information of the vehicle ahead of the own lane, information of the adjacent vehicle on the left of the own vehicle, and information of the adjacent vehicle on the right of the own vehicle.
  • the control unit 305 is used to control the vehicle to drive according to the driving path. In some embodiments, the control unit 305 controls the vehicle to keep driving in the current lane based on the planned travel path. In some embodiments, the control unit 305 generates the lateral control instruction and the longitudinal control instruction of the vehicle based on the driving path; and then sends the lateral control instruction and the longitudinal control instruction to the vehicle chassis controller to control the vehicle to maintain the lane.
  • the vehicle chassis controller belongs to a part of the vehicle bottom-level execution system shown in FIG. 1.
  • the control unit 305 generates a lateral control instruction based on the driving path, specifically: determining the preview longitudinal distance based on the motion information of the vehicle and the road curvature; and then determining the lateral direction corresponding to the preview longitudinal distance based on the driving path Relative position; thus based on the preview longitudinal distance and the lateral relative position, the vehicle lateral control command is generated.
  • the preview longitudinal distance is the longitudinal distance of the front aiming point relative to the vehicle related to the vehicle speed and preview time coefficient. It is a key parameter in the traditional geometric vehicle lateral control method.
  • the preview longitudinal distance can also be used. The method is determined and will not be repeated.
  • the lateral control commands may include, but are not limited to: steering wheel angle commands and torque control commands.
  • the torque control command is a lateral control command sent to the steering mechanism controller for execution.
  • the control unit 305 generates a longitudinal control instruction based on the driving path, specifically: determining the acceleration and driving path of the vehicle based on the motion information of the vehicle, lane-changing information of vehicles around the vehicle, road curvature, and driving path. The speed of the vehicle in front of the lane; and based on the acceleration of the vehicle and the speed of the vehicle in front of the lane, a longitudinal control command is generated.
  • the longitudinal control command may include, but is not limited to: a shaft end torque command and a brake deceleration command. Among them, the shaft end torque command is a longitudinal control command sent to the engine for execution.
  • each unit in the lane keeping module 300 is only a logical function division, and there may be other division methods in actual implementation, such as the acquisition unit 301, the first determination unit 302, the second determination unit 303,
  • the planning unit 304 and the control unit 305 may be implemented as one unit; the acquisition unit 301, the first determination unit 302, the second determination unit 303, the planning unit 304, or the control unit 305 may also be divided into multiple sub-units.
  • each unit or subunit can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraint conditions of the technical solution. Those skilled in the art can use different methods for each specific application to realize the described functions.
  • Fig. 4 is a schematic structural diagram of a vehicle-mounted device provided by an embodiment of the present disclosure.
  • the on-board equipment can support the operation of the intelligent driving system.
  • the vehicle-mounted device includes: at least one processor 401, at least one memory 402, and at least one communication interface 403.
  • the various components in the vehicle-mounted device are coupled together through the bus system 404.
  • the communication interface 403 is used for information transmission with external devices. Understandably, the bus system 404 is used to implement connection and communication between these components.
  • the bus system 404 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clear description, various buses are marked as the bus system 404 in FIG. 4.
  • the memory 402 in this embodiment may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory.
  • the memory 402 stores the following elements, executable units or data structures, or a subset of them, or an extended set of them: operating systems and applications.
  • the operating system includes various system programs, such as a framework layer, a core library layer, and a driver layer, which are used to implement various basic services and process hardware-based tasks.
  • Application programs including various application programs, such as Media Player, Browser, etc., are used to implement various application services.
  • a program that implements the lane keeping method provided by the embodiments of the present disclosure may be included in an application program.
  • the processor 401 calls a program or instruction stored in the memory 402, specifically, it may be a program or instruction stored in an application program, and the processor 401 is configured to execute each lane keeping method provided by the embodiment of the present disclosure. Example steps.
  • the lane keeping method provided by the embodiment of the present disclosure may be applied to the processor 401 or implemented by the processor 401.
  • the processor 401 may be an integrated circuit chip with signal processing capability. In the implementation process, the steps of the foregoing method can be completed by an integrated logic circuit of hardware in the processor 401 or instructions in the form of software.
  • the foregoing processor 401 may be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (ASIC), a ready-made programmable gate array (Field Programmable Gate Array, FPGA) or other Programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
  • the steps of the lane keeping method provided by the embodiments of the present disclosure may be directly embodied as executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software units in the decoding processor.
  • the software unit may be located in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers.
  • the storage medium is located in the memory 402, and the processor 401 reads the information in the memory 402 and completes the steps of the method in combination with its hardware.
  • Fig. 5 is a flowchart of a lane keeping method provided by an embodiment of the disclosure.
  • the execution body of the method is a vehicle-mounted device.
  • the execution body of the method is an intelligent driving system supported by the vehicle-mounted device.
  • the lane keeping method may include but is not limited to the following steps 501 to 505:
  • the environmental information is information obtained through perception based on sensor data, and the environmental information may include, but is not limited to, at least one of the following: lane line information, information of the vehicle ahead of the own lane, vehicle information in the left lane of the own vehicle, and own vehicle Vehicle information in the right lane.
  • the own lane can be understood as the lane where the vehicle is located;
  • the left lane of the vehicle can be understood as the lane adjacent to and on the left side of the lane;
  • the right lane of the vehicle can be understood as being adjacent to the lane and located on the right of the lane.
  • Side lane is lane line information, information of the vehicle ahead of the own lane, vehicle information in the left lane of the own vehicle, and own vehicle Vehicle information in the right lane.
  • the lane line information may include, but is not limited to: location, line shape, and credibility.
  • the information of the vehicle in front of the lane may include, but is not limited to: the relative distance and relative speed of two vehicles in front of the lane (for example, 102 and 103 in FIG. 6) and the vehicle.
  • the vehicle information in the left lane of the own vehicle may include, but is not limited to: the relative distance and relative speed between the left neighboring vehicle (such as 104 in Figure 6) and the own vehicle, and the left front vehicle of the own vehicle (such as 105 in Figure 6) and the own vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: location, line shape, and credibility.
  • the information of the vehicle in front of the lane may include, but is not limited to: the relative distance and relative speed of two vehicles in front of the lane (for example, 102 and 103 in FIG. 6) and the vehicle.
  • the vehicle information in the left lane of the own vehicle may include, but is not limited to
  • the vehicle information in the right lane of the own vehicle may include, but is not limited to: the relative distance and relative speed between the adjacent vehicle on the right of the vehicle (e.g. 106 in Figure 6) and the vehicle, the vehicle ahead of the vehicle on the right (e.g. 107 in Figure 6) and the vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: the relative distance and relative speed between the adjacent vehicle on the right of the vehicle (e.g. 106 in Figure 6) and the vehicle, the vehicle ahead of the vehicle on the right (e.g. 107 in Figure 6) and the vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: the relative distance and relative speed between the adjacent vehicle on the right of the vehicle (e.g. 106 in Figure 6) and the vehicle, the vehicle ahead of the vehicle on the right (e.g. 107 in Figure 6) and the vehicle.
  • the relative distance and relative speed of the car may include, but is not limited to: the relative distance and relative speed between the
  • the two vehicles in front of the lane may be two vehicles directly in front of the lane.
  • the front right is relative to the front left and front right.
  • the front vehicle can be understood as a vehicle driving in the lane where the vehicle is located and located in front of the vehicle.
  • the lane-changing information of vehicles around the own vehicle may include, but is not limited to: vehicle information that cuts out the lane from the vehicle in front of the lane, for example, the logo of the vehicle that cuts out of the lane from the own lane to the left lane of the own vehicle, and For example, the identification of the vehicle cut from the own lane to the right lane of the vehicle.
  • vehicle information is not limited to the identification, but may also be other information, such as the direction of lane change (left or right lane change) ).
  • cutting out the own lane can be understood as changing lanes from the own lane to the adjacent lane.
  • the adjacent lane can be understood as the left lane of the vehicle or the right lane of the vehicle.
  • the lane-changing information of the vehicles surrounding the own vehicle may include, but is not limited to: information of vehicles that cut into the own lane from the left lane of the own vehicle and the right lane of the own vehicle, for example, the identification of the vehicle that cuts into the own lane from the left lane of the own vehicle , Another example is the identification of the vehicle that cuts into the lane from the right lane of the vehicle. Among them, cutting into the own lane can be understood as changing lanes from the adjacent lane to the own lane.
  • the effective lane line can be understood as: at least one lane line on the left and right sides exists and is of good quality.
  • Invalid lane line can be understood as: both left and right lane lines are invalid, where invalid can be understood as: lane line is missing or poor quality.
  • the quality of the lane line is determined based on the lane line information, that is, based on the position, line shape, and credibility of the lane line.
  • the credibility is not lower than the preset range. If the reliability threshold is used, the quality of the lane line is determined to be good; otherwise, the quality of the lane line is determined to be poor.
  • the preset distance range, preset curvature range, and preset credibility threshold can be set based on actual needs, and this embodiment does not limit specific values.
  • the lane line information is used to determine the lane-changing information of the vehicles around the vehicle. In some embodiments, based on the lane line information in the environment information and the information of the vehicle ahead of the own lane, the information of the vehicle that cuts out the own lane among the vehicles ahead of the own lane is determined. In some embodiments, based on the lane line information in the environment information, the vehicle information in the left lane of the own vehicle, and the vehicle information in the right lane of the own vehicle, the information of the vehicle that cuts into the own lane in the left lane of the own vehicle and the right lane of the own vehicle is determined.
  • the motion information of the own vehicle is used to determine the lane-changing information of vehicles around the own vehicle.
  • the motion information of the vehicle may include, but is not limited to: vehicle speed, steering wheel angle, yaw rate, etc.
  • the motion trajectory of the own vehicle is determined based on the motion information of the own vehicle; furthermore, the lane-changing information of vehicles around the own vehicle is determined based on the boundary of the motion trajectory.
  • the boundary of the motion trajectory is a lateral boundary of the motion trajectory, wherein the lateral direction is a direction perpendicular to the lane line.
  • the vehicle information of the vehicle ahead of the own lane is determined.
  • the vehicle information in the left lane of the own vehicle, and the vehicle information in the right lane of the own vehicle the information of the vehicle that cuts into the own lane in the left lane of the own vehicle and the right lane of the own vehicle is determined.
  • a follow-up mode is decided from among multiple follow-up modes for lane keeping.
  • the follow mode may include, but is not limited to: a follow mode, a follow mode, and a degraded mode.
  • the following mode includes: the vehicle follows the lane line to maintain the lane; the following mode includes: the vehicle follows the vehicle directly in front to maintain the lane; the degraded mode includes: the vehicle does not follow the vehicle directly in front to cut out of the lane, and keep other vehicles in the same lane.
  • the stability of the vehicle in the lane In some embodiments, the stability of the vehicle when other vehicles cut into the lane is maintained.
  • the braking force is not greater than the preset braking force threshold
  • the steering wheel angle is not greater than the preset angle threshold
  • neither the application of braking force nor the rotation of the steering wheel are greater than the preset braking force threshold. It can be completed at one time to prevent the occurrence of vehicle shaking and instability caused by sudden braking and sudden steering.
  • the preset braking force threshold and the preset angle threshold can be set according to actual needs, and the specific values are not limited in this embodiment. It can be understood that the way to maintain the stability of the vehicle can also be other ways to prevent unstable situations such as vehicle shaking, sudden turning, and emergency stopping.
  • the following mode is the line-following mode. In some embodiments, based on the invalid lane line and no lane change information, it is determined that the following mode is the following mode. In some embodiments, it is determined that the following mode is a degraded mode based on the lane-changing information including the vehicle information of the vehicle in front of the lane that cuts out of the lane and/or the information of the vehicle that cuts into the lane in the left lane of the vehicle and the right lane of the vehicle.
  • Plan a driving route based on the determined following mode.
  • the travel path is planned based on the lane line information and the state of the lane line.
  • the state of the lane line includes valid and invalid.
  • the lane center line is determined based on the lane line information and the state of the lane line; and then the travel path is planned based on the lane center line.
  • the center line of the lane is determined based on the lane line information and the state of the lane line, specifically: if the lane lines on both sides (such as 108 and 109 in Figure 6) are valid, then generate based on the lane lines on both sides Lane center line; if one side lane line is valid and the other side lane line is invalid, the lane center line is generated based on the effective side lane line and lane width. In some embodiments, there are two ways to generate the lane centerline based on the effective side lane line and the lane width.
  • Method 1 Generate the lane center line directly based on the effective side lane line and lane width;
  • Method 2 First generate the invalid side lane line based on the effective side lane line and lane width, and then generate the lane center line from the effective side lane line and the invalid side lane line .
  • the vehicle can be smoothly controlled to keep driving in the current lane.
  • the driving route is planned based on the environmental information.
  • planning the travel path is specifically: determining the relative position of the vehicle in front of the lane and the vehicle as the end of the path; then generating multiple path curves from the vehicle to the end of the path; thereby filtering those that meet the conditions
  • the path curve is the driving path; wherein, the condition is the maximum average distance between the vehicles around the vehicle (for example, 102 to 107 in FIG. 6) from the path curve.
  • multiple path curves from the vehicle to the end of the path can be generated based on the traditional spline function generation method, which will not be repeated here.
  • a new follow-up mode is added, which enables the vehicle to follow the preceding vehicle and keep driving in the current lane.
  • the travel path is planned based on the movement information of the vehicle and the lane-changing information of vehicles around the vehicle.
  • the motion information of the vehicle, the historical planning path and the first information of the vehicles surrounding the vehicle are used to plan the driving path to prevent the vehicle from following the vehicle in front Cut out the own lane; wherein, the first information includes: vehicle information in the vehicle ahead of the lane that does not cut out the lane, vehicle information in the left lane of the vehicle, and vehicle information in the right lane of the vehicle.
  • the movement information of the own vehicle, the historical planning path and the second information of the surrounding vehicles of the own vehicle are used to plan the driving path to prevent The planned path jump of the own vehicle caused by the change of the path end point; wherein the second information includes: information of the vehicle ahead of the own lane, information of the adjacent vehicle on the left of the own vehicle, and information of the adjacent vehicle on the right of the own vehicle.
  • the vehicle chassis controller belongs to a part of the vehicle bottom-level execution system shown in FIG. 1.
  • generating the lateral control instruction is specifically: determining the preview longitudinal distance based on the motion information of the vehicle and the road curvature; and then determining the horizontal relative position corresponding to the preview longitudinal distance based on the driving path;
  • the vehicle lateral control command is generated.
  • the preview longitudinal distance is the longitudinal distance of the front aiming point relative to the vehicle related to the vehicle speed and preview time coefficient. It is a key parameter in the traditional geometric vehicle lateral control method.
  • the preview longitudinal distance can also be used. The method is determined and will not be repeated.
  • the lateral control commands may include, but are not limited to: steering wheel angle commands and torque control commands.
  • the torque control command is a lateral control command sent to the steering mechanism controller for execution.
  • the longitudinal control instruction is generated based on the driving path, specifically: determining the acceleration of the own vehicle and the vehicle ahead of the own lane based on the motion information of the own vehicle, the lane-changing information of the surrounding vehicles, the road curvature and the traveling path Based on the acceleration of the vehicle and the speed of the vehicle in front of the lane, a longitudinal control command is generated.
  • the longitudinal control command may include, but is not limited to: a shaft end torque command and a brake deceleration command. Among them, the shaft end torque command is a longitudinal control command sent to the engine for execution.
  • the embodiment of the present disclosure also proposes a non-transitory computer-readable storage medium, which stores a program or instruction, and the program or instruction causes a computer to execute the steps of the various embodiments of the lane keeping method, In order to avoid repetitive descriptions, I will not repeat them here.
  • a follow-up mode is determined from multiple follow-up modes for lane keeping. Thereby planning the driving path and controlling the vehicle to keep driving in the current lane, which has industrial applicability.

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
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  • Traffic Control Systems (AREA)

Abstract

L'invention concerne un procédé de suivi de voie, un dispositif embarqué, et un support de stockage. Le procédé comprend les étapes suivantes: l'acquisition d'information d'un environnement autour du présent véhicule (501); la détermination d'information de changement de voie de véhicules autour du présent véhicule sur la base de l'information de l'environnement (502); la détermination d'un mode suivant du présent véhicule sur la base de l'information de l'environnement et de l'information de changement de voie (503); la planification d'un trajet de déplacement sur la base du mode suivant (504); et la commande du véhicule pour suivre le trajet de déplacement (505). Dans une situation de trafic congestionné, selon le procédé, au moyen de la détermination d'information de changement de voie de véhicules autour du présent véhicule et la détermination, sur la base d'information d'un environnement autour du présent véhicule, d'un mode suivant parmi une pluralité de modes suivants pour le maintien de voie, un trajet de déplacement est planifié et le véhicule est commandé pour maintenir un déplacement dans la voie de circulation actuelle.
PCT/CN2019/122100 2019-11-29 2019-11-29 Procédé de suivi de voie, dispositif embarqué, et support de stockage WO2021102957A1 (fr)

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CN201980002776.8A CN113677581B (en) 2019-11-29 Lane keeping method, vehicle-mounted equipment and storage medium
PCT/CN2019/122100 WO2021102957A1 (fr) 2019-11-29 2019-11-29 Procédé de suivi de voie, dispositif embarqué, et support de stockage

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113353078A (zh) * 2021-06-24 2021-09-07 中汽创智科技有限公司 一种无车道线自动跟车轨迹确定方法及装置
CN113415274A (zh) * 2021-07-14 2021-09-21 重庆长安汽车股份有限公司 自动驾驶的跟车轨迹规划系统、方法、车辆及存储介质
CN113515038A (zh) * 2021-09-07 2021-10-19 西南交通大学 一种车辆换道方法、装置、设备及可读存储介质
CN113665588A (zh) * 2021-09-10 2021-11-19 苏州轻棹科技有限公司 一种自动驾驶车辆基于无线道路数据控制车辆行驶的方法
CN113722835A (zh) * 2021-09-14 2021-11-30 吉林大学 拟人化随机换道驾驶行为建模方法
CN114013439A (zh) * 2021-11-15 2022-02-08 合众新能源汽车有限公司 车辆主动跟车方法和系统
CN114084158A (zh) * 2021-12-17 2022-02-25 吉林大学 一种自动驾驶冗余控制系统
CN114255594A (zh) * 2021-12-28 2022-03-29 吉林大学 一种自主代客泊车运动规划与运动控制方法
CN115223131A (zh) * 2021-11-09 2022-10-21 广州汽车集团股份有限公司 一种自适应巡航的跟随目标车辆检测方法、装置及汽车
WO2023173713A1 (fr) * 2022-03-16 2023-09-21 广州小鹏自动驾驶科技有限公司 Procédé et appareil de commande de direction de véhicule, véhicule et support de stockage

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160039458A1 (en) * 2012-01-17 2016-02-11 Ford Global Technologies, Llc Autonomous lane control system
CN106218636A (zh) * 2016-07-21 2016-12-14 浙江吉利汽车研究院有限公司 一种交通拥堵辅助系统
CN109606346A (zh) * 2018-12-29 2019-04-12 武汉超控科技有限公司 一种自动驾驶的车道保持系统
CN109649390A (zh) * 2018-12-19 2019-04-19 清华大学苏州汽车研究院（吴江） 一种自动驾驶汽车自主跟车系统及方法
CN110341707A (zh) * 2019-08-07 2019-10-18 浙江吉利汽车研究院有限公司 车道保持控制系统及车道保持控制方法、车辆

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160039458A1 (en) * 2012-01-17 2016-02-11 Ford Global Technologies, Llc Autonomous lane control system
CN106218636A (zh) * 2016-07-21 2016-12-14 浙江吉利汽车研究院有限公司 一种交通拥堵辅助系统
CN109649390A (zh) * 2018-12-19 2019-04-19 清华大学苏州汽车研究院（吴江） 一种自动驾驶汽车自主跟车系统及方法
CN109606346A (zh) * 2018-12-29 2019-04-12 武汉超控科技有限公司 一种自动驾驶的车道保持系统
CN110341707A (zh) * 2019-08-07 2019-10-18 浙江吉利汽车研究院有限公司 车道保持控制系统及车道保持控制方法、车辆

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113353078A (zh) * 2021-06-24 2021-09-07 中汽创智科技有限公司 一种无车道线自动跟车轨迹确定方法及装置
CN113415274B (zh) * 2021-07-14 2022-07-05 重庆长安汽车股份有限公司 自动驾驶的跟车轨迹规划系统、方法、车辆及存储介质
CN113415274A (zh) * 2021-07-14 2021-09-21 重庆长安汽车股份有限公司 自动驾驶的跟车轨迹规划系统、方法、车辆及存储介质
CN113515038A (zh) * 2021-09-07 2021-10-19 西南交通大学 一种车辆换道方法、装置、设备及可读存储介质
CN113515038B (zh) * 2021-09-07 2021-11-26 西南交通大学 一种车辆换道方法、装置、设备及可读存储介质
CN113665588A (zh) * 2021-09-10 2021-11-19 苏州轻棹科技有限公司 一种自动驾驶车辆基于无线道路数据控制车辆行驶的方法
CN113722835A (zh) * 2021-09-14 2021-11-30 吉林大学 拟人化随机换道驾驶行为建模方法
CN113722835B (zh) * 2021-09-14 2023-10-20 吉林大学 拟人化随机换道驾驶行为建模方法
CN115223131A (zh) * 2021-11-09 2022-10-21 广州汽车集团股份有限公司 一种自适应巡航的跟随目标车辆检测方法、装置及汽车
CN114013439A (zh) * 2021-11-15 2022-02-08 合众新能源汽车有限公司 车辆主动跟车方法和系统
CN114013439B (zh) * 2021-11-15 2024-03-22 合众新能源汽车股份有限公司 车辆主动跟车方法和系统
CN114084158A (zh) * 2021-12-17 2022-02-25 吉林大学 一种自动驾驶冗余控制系统
CN114255594A (zh) * 2021-12-28 2022-03-29 吉林大学 一种自主代客泊车运动规划与运动控制方法
CN114255594B (zh) * 2021-12-28 2024-03-15 吉林大学 一种自主代客泊车运动规划与运动控制方法
WO2023173713A1 (fr) * 2022-03-16 2023-09-21 广州小鹏自动驾驶科技有限公司 Procédé et appareil de commande de direction de véhicule, véhicule et support de stockage

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