CN116457259A - Vehicle driving control method and device, vehicle and storage medium - Google Patents

Vehicle driving control method and device, vehicle and storage medium Download PDF

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Publication number
CN116457259A
CN116457259A CN202180072808.9A CN202180072808A CN116457259A CN 116457259 A CN116457259 A CN 116457259A CN 202180072808 A CN202180072808 A CN 202180072808A CN 116457259 A CN116457259 A CN 116457259A
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China
Prior art keywords
correction coefficient
vehicle
distance
aiming
path
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CN202180072808.9A
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Chinese (zh)
Inventor
许康熙
邓堃
徐胜亮
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Zhejiang Geely Holding Group Co Ltd
Geely Automobile Research Institute Ningbo Co Ltd
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Zhejiang Geely Holding Group Co Ltd
Geely Automobile Research Institute Ningbo Co Ltd
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Publication of CN116457259A publication Critical patent/CN116457259A/en
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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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18—Propelling the vehicle
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion

Abstract

A vehicle driving control method, a vehicle driving control device, a vehicle and a computer readable storage medium belong to the technical field of vehicles. The vehicle driving control method comprises the following steps: path planning is carried out to obtain a tracking path; acquiring a basic pre-aiming distance according to the current position information of the vehicle and the tracking path; acquiring a correction coefficient aiming at a basic pre-aiming distance, wherein the correction coefficient comprises at least one of a speed correction coefficient, a path curvature correction coefficient and a course angle correction coefficient; acquiring a target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance; and performing transverse driving control according to the target pre-aiming distance. Therefore, the calculation parameters of the path following algorithm can be optimized according to the detail condition of the driving scene, so that the purpose of optimizing the path following algorithm in the passenger parking function is achieved, the control precision of low-speed unmanned operation is improved to ensure the safety of vehicle and the reliability of the function, and the use experience of a user can be improved.

Description

Vehicle driving control method and device, vehicle and storage medium Technical Field
The present disclosure relates to the field of vehicle technologies, and in particular, to a vehicle driving control method, a vehicle driving control device, a vehicle, and a computer readable storage medium.
Background
In the future, unmanned operation will gradually enter the life of people, and the passenger parking is probably the unmanned function which is firstly applied to mass production passenger cars, and the passenger parking car owner searches for a parking space in a parking lot and parks the car into the parking space.
However, in a scene where the topography of the parking lot is not ideal (for example, a part of parking lot channels are narrow, and a parking space may have a narrow scene), stability during use of the conventional proxy parking function is poor (for example, a steady-state lateral deviation is large, a steady-state heading angle deviation is large, etc.), and one of reasons for poor stability during use of the conventional proxy parking function is that the calculation parameters (for example, the pre-aiming distance) provided to the path following algorithm in the conventional proxy parking function are not considered in a fine driving scene, and cannot be adjusted according to the fine driving scene, so that the accuracy of the path following algorithm in the conventional proxy parking function is still insufficient.
The foregoing description is provided for general background information and does not necessarily constitute prior art.
Technical problem
How to optimize the path following algorithm in the valet parking function is a problem that needs to be solved by those skilled in the art.
Technical solution
The technical problem to be solved by the application is to overcome the defects of the prior art, and the vehicle driving control method, the vehicle driving control device, the vehicle and the computer readable storage medium are provided to optimize the calculation parameters of the path following algorithm according to the detail condition of the driving scene, so that the purpose of optimizing the path following algorithm in the passenger parking function is achieved, the control precision in low-speed unmanned driving is improved to ensure the vehicle safety and the function reliability, and the use experience of a user can be improved.
The application provides a vehicle driving control method, which comprises the following steps: path planning is carried out to obtain a tracking path; acquiring a basic pre-aiming distance according to the current position information of the vehicle and the tracking path; acquiring a correction coefficient aiming at a basic pre-aiming distance, wherein the correction coefficient comprises at least one of a speed correction coefficient, a path curvature correction coefficient and a course angle correction coefficient; acquiring a target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance; and performing transverse driving control according to the target pre-aiming distance.
Optionally, the step of acquiring the basic pretightening distance according to the current position information of the vehicle and the tracking path includes: acquiring a tracking position point corresponding to the current position information of the vehicle on a tracking path; acquiring a transverse position deviation value according to the current position information of the vehicle and the tracking position point; and acquiring a basic pretightening distance corresponding to the transverse position deviation value from pretightening distance corresponding relation information, wherein the pretightening distance corresponding relation information comprises a corresponding relation between at least one transverse position deviation value and the basic pretightening distance.
Optionally, the step of obtaining the correction coefficient for the basic pretightening distance includes: acquiring a current vehicle speed, and acquiring a speed correction coefficient corresponding to the current vehicle speed from speed correction coefficient corresponding relation information, wherein the speed correction coefficient corresponding relation information indicates the corresponding relation between the vehicle speed and the speed correction coefficient; the step of obtaining the target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance comprises the following steps: and acquiring a first target pretightening distance according to the speed correction coefficient and the basic pretightening distance, wherein the speed correction coefficient and the basic pretightening distance are in a direct proportion relation.
Optionally, the step of obtaining the correction coefficient for the basic pretightening distance includes: determining an initial pre-aiming point on a tracking path according to the basic pre-aiming distance; acquiring a heading deviation angle according to the heading corresponding to the initial pre-aiming point and the advancing direction of the vehicle; acquiring a course angle correction coefficient corresponding to the course deviation angle and the transverse position deviation value from course angle correction coefficient corresponding relation information, wherein the course angle correction coefficient corresponding relation information indicates the corresponding relation among the transverse position deviation value, the course deviation angle and the course angle correction coefficient; the step of obtaining the target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance comprises the following steps: and acquiring a first target pre-aiming distance according to the course angle correction coefficient and the basic pre-aiming distance, wherein the course angle correction coefficient and the basic pre-aiming distance are in a direct proportion relation.
Optionally, the step of obtaining the correction coefficient for the basic pretightening distance includes: acquiring a path curvature average value of a tracking path; acquiring a curvature correction coefficient corresponding to the path curvature mean value and the transverse position deviation value from curvature correction coefficient corresponding relation information, wherein the curvature correction coefficient corresponding relation information indicates the corresponding relation among the transverse position deviation value, the path curvature mean value and the curvature correction coefficient; the step of obtaining the target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance comprises the following steps: and acquiring a first target pretightening distance according to the path curvature correction coefficient and the basic pretightening distance, wherein the path curvature correction coefficient and the basic pretightening distance are in a direct proportion relation.
Optionally, the step of obtaining the path curvature average value of the tracking path includes: determining an initial pre-aiming point on a tracking path according to the basic pre-aiming distance; and calculating a path curvature average value from the tracking position point to the initial pre-aiming point according to the tracking position point and the initial pre-aiming point on the tracking path.
Optionally, the step of acquiring the target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance includes: acquiring a target pre-aiming distance according to the first target pre-aiming distance and an optimization correction coefficient, wherein the first target pre-aiming distance and the optimization correction coefficient are in a direct proportion relation; the optimized correction coefficients are correction coefficients except for the correction coefficients corresponding to the first target pre-aiming distance.
Optionally, the step of performing lateral driving control according to the target pre-aiming distance includes: determining a pre-aiming point on a tracking path according to the target pre-aiming distance; acquiring a vehicle pre-aiming angle according to a coordinate system established based on a basic principle of a pure tracking algorithm and a pre-aiming point on a tracking path; substituting the target pre-aiming distance and the vehicle pre-aiming angle into a turning radius calculation formula to calculate the turning radius of the vehicle; calculating a steering wheel angle according to a steering wheel angle calculation formula corresponding to the vehicle and a vehicle turning radius; the turning system of the vehicle is controlled according to the steering wheel angle.
Optionally, the turning radius calculation formula includes:wherein R represents the turning radius of the vehicle, L d Representing a target pre-aiming distance, and alpha represents a vehicle pre-aiming angle; the steering wheel angle calculation formula includes: sta=α 1 ρ 5 +α 2 ρ 4 +α 3 ρ 3 +α 4 ρ 2 +α 5 ρ 1 +α 6 The method comprises the steps of carrying out a first treatment on the surface of the Wherein,wherein StA represents steering wheel angle, ρ represents turning curvature, α 1 、α 2 、α 3 、α 4 、α 5 、α 6 Are all formula coefficients, and the formula coefficients correspond to the model of the vehicle.
Optionally, the target pre-aiming distance is within a defined distance range, the defined distance range being 1 meter to 3.6 meters.
The application also provides a vehicle driving control device, which comprises a memory and a processor; the processor is configured to execute a computer program stored in the memory to implement the steps of the vehicle driving control method as described above.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the vehicle driving control method as described above.
The present application also provides a vehicle including the vehicle driving control apparatus as described above.
Advantageous effects
The application provides a vehicle driving control method, a vehicle driving control device, a vehicle and a computer readable storage medium, wherein the vehicle driving control method comprises the following steps: path planning is carried out to obtain a tracking path; acquiring a basic pre-aiming distance according to the current position information of the vehicle and the tracking path; acquiring a correction coefficient aiming at a basic pre-aiming distance, wherein the correction coefficient comprises at least one of a speed correction coefficient, a path curvature correction coefficient and a course angle correction coefficient; acquiring a target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance; and performing transverse driving control according to the target pre-aiming distance. Therefore, the method and the device can optimize the calculation parameters of the path following algorithm according to the detail conditions (such as the vehicle speed, the path curvature of the tracking path, the course angle deviation angle and the like) of the driving scene, so that the purpose of optimizing the path following algorithm in the passenger parking function is achieved, the control precision during low-speed unmanned driving is improved to ensure the vehicle safety and the functional reliability, and the use experience of a user can be improved. In addition, the path following algorithm can be optimized, a good calculation effect can be achieved with little calculation amount, so that under the environment of parking or fixed-point parking of low-speed automatic driving, the steady-state transverse deviation is controlled within a small range (for example, within +/-5 cm), the steady-state course angle deviation is controlled within a small range (for example, within +/-3 degrees), the vehicle can be well regulated to the tracking path even if the initial position of the vehicle deviates from the tracking path, and the convergence speed is high and the overshoot is small.
In addition, the pre-aiming distance can be adaptively adjusted according to the vehicle speed, the path curvature of the tracking path, the course angle deviation angle and the transverse deviation, so that the vehicle can quickly converge at different initial positions and at different angles, different road curvatures can be adapted, certain control precision is met, particularly, a good control effect is achieved under the condition of large initial deviation of the vehicle, and the defects that the pre-aiming distance is fixed when the initial deviation of the vehicle is large or the pre-aiming distance is adjusted only according to the vehicle speed in transverse control are overcome, such as easy overshoot, slow convergence speed, large steady state error and the like. The application can adapt to different roads, such as: straight line, right angle bend, little S bend, big S bend, the circular arc of different curvatures, dysmorphism bend etc. even the route that the driver opened at will also can follow steadily, and steady state deviation is less, and this application can converge fast and overshoot is less under the circumstances of big deviation. The method and the device not only can meet the parking function (passenger parking, full-automatic parking and semi-automatic parking), but also can meet the functions related to low-speed unmanned driving (such as autonomous wireless charging, unmanned park connection vehicle and unmanned park cleaning vehicle). Because the steering wheel angle and the front wheel angle have nonlinear relations, and the nonlinear relations of the steering wheel angles and the front wheel angles of different vehicle types are different, the relation between the steering wheel angle and the vehicle turning radius can be calibrated, so that a better steady-state following effect can be obtained. The method has the advantages of small code quantity, high operation efficiency, good embedment and low requirement on hardware.
The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments, as illustrated in the accompanying drawings.
Drawings
Fig. 1 is a flowchart of a vehicle driving control method provided in a first embodiment of the present application.
FIG. 2 is a first schematic illustration of a bicycle model provided in accordance with a first embodiment of the present application.
Fig. 3 is a correspondence diagram of basic pretightening distances provided in the first embodiment of the present application.
FIG. 4 is a second schematic view of a bicycle model provided in the first embodiment of the present application.
Fig. 5A is a diagram of a first simulation result of the position alignment according to the first embodiment of the present application.
Fig. 5B is a graph of simulation results of a first variation of the lateral error provided in the first embodiment of the present application.
Fig. 6A is a diagram of second simulation results of position alignment provided in the first embodiment of the present application.
Fig. 6B is a diagram of simulation results of a second variation of the lateral error provided by the first embodiment of the present application.
Fig. 7A is a diagram of third simulation results of position alignment according to the first embodiment of the present application.
Fig. 7B is a diagram of simulation results of a third variation of the lateral error provided in the first embodiment of the present application.
Fig. 8 is a correspondence diagram of the velocity correction coefficients provided in the first embodiment of the present application.
Fig. 9 is a correspondence diagram of curvature correction coefficients provided in the first embodiment of the present application.
Fig. 10A is a diagram showing simulation results of path tracking before curvature correction according to the first embodiment of the present application.
Fig. 10B is a graph of simulation results of lateral deviation variation before curvature correction provided in the first embodiment of the present application.
Fig. 11A is a graph of simulation results of the curvature corrected path tracking provided in the first embodiment of the present application.
Fig. 11B is a graph of simulation results of lateral deviation change after curvature correction provided in the first embodiment of the present application.
Fig. 12 is a correspondence chart of heading angle correction coefficients provided in the first embodiment of the present application.
Fig. 13A is a diagram of simulation results of a curve scene before course angle correction provided in the first embodiment of the present application.
Fig. 13B is a diagram showing simulation results of lateral deviation change before course angle correction provided in the first embodiment of the present application.
Fig. 14A is a diagram of simulation results of a curve scene after heading angle correction provided in the first embodiment of the present application.
Fig. 14B is a diagram showing simulation results of lateral deviation change after course angle correction provided in the first embodiment of the present application.
Fig. 15A is a diagram of simulation results of a small S curve scenario provided in the first embodiment of the present application.
Fig. 15B is a graph of simulation results of lateral deviation variation of a small S-bend scene provided in the first embodiment of the present application.
Fig. 16A is a diagram of simulation results of a right angle curve scenario provided in the first embodiment of the present application.
Fig. 16B is a diagram of simulation results of lateral deviation variation of a right angle curve scene provided in the first embodiment of the present application.
Fig. 17 is a comprehensive verification result diagram of a straight road scene provided in the first embodiment of the present application.
Fig. 18 is a diagram of the comprehensive verification result of the large S curve scene provided in the first embodiment of the present application.
Fig. 19 is a diagram of the comprehensive verification result of the small S curve scene provided in the first embodiment of the present application.
Fig. 20 is a diagram of the comprehensive verification result of the right angle curve scene provided in the first embodiment of the present application.
Fig. 21 is a diagram of a comprehensive verification result of a special-shaped curve scene provided in the first embodiment of the present application.
Fig. 22 is a schematic view of a lateral control module provided in the first embodiment of the present application.
Fig. 23 is a schematic structural view of a vehicle driving control device provided in a second embodiment of the present application.
Fig. 24 is a schematic view of a vehicle provided in a second embodiment of the present application.
Drawing vocabulary analysis:
current Point: tracking position points corresponding to the center of the rear axle of the vehicle;
Preview Point, preview Point;
preview Distance;
path, trace Path;
road curvature refers to the path curvature average value from the Current Point (Current Point) to the Preview Point (Preview Point);
lateral Deviation (or Lateral Deviation Error): lateral position deviation (distance of perpendicular to the path tracked by the center of the rear axle of the vehicle);
target Position: a target path for vehicle tracking;
real Position is the actual Position in the vehicle path tracking process;
distance error refers to the Distance of the perpendicular to the path traced by the center of the rear axle of the vehicle, see e in FIG. 2 y ；
Velocity: speed of the vehicle;
y Error: lateral positional deviation;
odemetry: a moving distance;
location Comparison, position comparison;
yaw Comparison, course angle Comparison;
yaw Error, heading angle deviation.
Embodiments of the invention
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the described embodiments are merely some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Embodiments of the present application are described in further detail below with reference to the accompanying drawings.
First embodiment:
for a clear description of the vehicle driving control method provided in the first embodiment of the present application, please refer to fig. 1 to 22.
The vehicle driving control method provided in the first embodiment of the present application includes:
and S11, path planning is carried out to acquire a tracking path.
In an alternative embodiment, in step S11, performing path planning to obtain a tracking path may include: and acquiring the current position information of the vehicle through a positioning module, and performing path planning to acquire a tracking path.
In an alternative embodiment, the positioning module may be dead reckoned using RTK differential positioning techniques and/or IMU to provide current location information (or real-time location information) of the vehicle and/or tracking paths, and it may provide the vehicle's abscissa and ordinate.
The RTK differential positioning technology (RTK) is also called as carrier phase differential technology, and is a new and commonly used GPS measurement method, the previous static, quick static and dynamic measurement needs to be solved afterwards to obtain centimeter-level precision, while the RTK is a measurement method capable of obtaining centimeter-level positioning precision in Real time in the field, and can provide three-dimensional coordinates of an observation point in Real time and achieve centimeter-level high precision; the principle is the same as that of pseudo-range difference, and the reference station transmits the carrier observed quantity and station coordinate information to the subscriber station in real time through a data link; the user station receives the carrier phase of the GPS satellite and the carrier phase from the reference station, and forms a phase difference observation value for real-time processing, so that a centimeter-level positioning result can be given in real time; methods for implementing carrier phase differential GPS fall into two categories: the correction method and the difference method are that the former is the same as the pseudo-range difference, the reference station sends the carrier phase correction amount to the subscriber station to correct the carrier phase of the reference station, then the coordinate is solved, and the latter sends the carrier phase collected by the reference station to the subscriber station to solve the coordinate by the difference. The former is a quasi-RTK technique and the latter is a true RTK technique.
The IMU is generally called inertial measurement unit, namely an inertial measurement unit, generally comprises a gyroscope, an accelerator and an algorithm processing unit, and has important application value in navigation through measuring acceleration and rotation angle to obtain a motion track of an own body; i refer to a system combining a traditional IMU with an algorithm for fusing information such as a vehicle body and GPS as a generalized IMU for automatic driving. The GPS/IMU sensing system can help the autopilot to complete positioning by global positioning and inertial updating data at frequencies up to 100 Hz. GPS is a relatively accurate location sensor, but its update frequency is too low, only 10Hz, and insufficient to provide sufficiently real-time location updates. The IMU has the real-time property lacking in the GPS, and the update frequency of the IMU can reach 100Hz or higher. By integrating GPS with IMU, we can provide accurate and sufficiently real-time location updates for vehicle positioning. The GPS and IMU are combined, namely, the heading speed, the angular speed and the acceleration information of the IMU are fused, so that the precision and the anti-interference capability of the GPS are improved. Compared with the GPS, the IMU can provide not only some information but also complement navigation information, because the GPS only provides position information, and the IMU can also provide heading attitude information, which is information which is encountered in vehicle control and even the most basic vehicle control. Because the IMU can provide different angles, the change of the vehicle posture can be very sharply monitored in real time, and more complex road condition information can be accurately identified. The relative and absolute position deduction of the IMU is independent of any external equipment, and is a complete system like a black box in an airplane. Because the IMU does not require any external signals, it can be mounted in a hidden location such as an automobile chassis, thus avoiding electronic or mechanical attacks.
And S12, acquiring a basic pretightening distance according to the current position information of the vehicle and the tracking path.
In an alternative embodiment, in step S12, acquiring the basic pretightening distance according to the current position information of the vehicle and the tracking path may include: acquiring a tracking position point corresponding to the current position information of the vehicle on a tracking path; acquiring a transverse position deviation value according to the current position information of the vehicle and the tracking position point; and matching the basic pretighting distance corresponding to the transverse position deviation value.
In an alternative embodiment, the step of obtaining the lateral position deviation value according to the current position information of the vehicle and the tracking position point may include: based on the basic principle of a pure tracking algorithm, a coordinate system is established according to the current position information of the vehicle, the origin of the coordinate system corresponds to the center of a rear axle of the vehicle, the forward X-axis of the coordinate system is the advancing direction of the vehicle, and the Y-axis of the coordinate system is the transverse direction of the vehicle; and/or acquiring a transverse position deviation value according to the coordinate system and the tracking position point.
In an alternative implementation, the basic principles of the pure tracking algorithm in this example can be referred to in the article Myungwook Park, sangwoo Lee, and Wooyong Han. Development of Steering Control System for Autonomous Vehicle Using Geometry-Based Path Tracking Algorithm [ J ]. ETRI Journal,2015,37 (3): 617-625.
In one embodiment, based on the basic principle of the pure tracking algorithm, a coordinate system is established according to the current position information of the vehicle, and a lateral position deviation value is obtained according to the coordinate system and the tracking position point, for example, referring to fig. 2, the coordinate system is established by using the center of the rear axle (or called the center of the rear axle) of the vehicle, the forward direction is the forward X-axis, the lateral direction is the Y-axis, and the vehicle is simplified into a bicycle model, wherein T1 is the simplification of two rear wheels, and T2 is the simplification of two front wheels; obtaining the relative position of the tracking Path according to the global coordinate system (such as the left side of the whole parking lot or the coordinate at the Current position of the vehicle in the parking lot, not shown in the figure) provided by the positioning module and the coordinate system, thereby obtaining the tracking position Point Current Point corresponding to the center of the rear axle of the vehicle on the tracking Path, and obtaining the distance e from the center of the rear axle of the vehicle to the tracking position Point Current Point y (i.e., lateral position offset values).
In an alternative embodiment, the step of matching the basic pretighting distance corresponding to the lateral position deviation value may include: and acquiring a basic pretightening distance corresponding to the transverse position deviation value from the pretightening distance corresponding relation information. The pre-aiming distance corresponding relation information comprises a corresponding relation between at least one transverse position deviation value and a basic pre-aiming distance, and the pre-aiming distance corresponding relation information can be preset and stored by a user or a system according to actual requirements. The use of the pre-aiming distance correspondence information provided by the embodiment can ensure that the vehicle has no overshoot phenomenon as far as possible when the vehicle converges on the tracking path from a larger transverse position deviation value, and improve the stability of tracking the vehicle to the tracking path.
In an alternative embodiment, the pre-aiming distance correspondence information includes a correspondence between a lateral position deviation value and a basic pre-aiming distance, where the formula l=f (e y ) Representation (wherein l represents the basic pretightening distance, e y Representation ofLateral position deviation value). The pre-sight distance correspondence information is, for example, the correspondence shown in fig. 3, in which the smallest lateral position deviation value (Lateral Deviation, or simply e y ) The shortest basic pretightening Distance (pretightening Distance) is 1 meter when the horizontal position deviation value is 0 to 0.1 meter, and the longest basic pretightening Distance is about 2.7 meters when the horizontal position deviation value exceeds 0.5 meter.
In an alternative embodiment, referring to fig. 4, after the basic pretightening distance is obtained, an initial pretightening point P1 may be determined according to the basic pretightening distance, and an included angle (i.e., a heading deviation angle β) of a heading corresponding to the initial pretightening point P1 according to the advancing direction of the vehicle may be determined μ ) Determining the angle between the heading of the vehicle and the heading corresponding to the tracking position point (i.e. the initial heading deviation angle beta c )。
In an alternative embodiment, the setting principle of the pre-aiming distance correspondence information is that, because the pre-aiming distance plays a decisive role in controlling the effect of the pure tracking algorithm, if the lateral position deviation value of the vehicle is large, if the smaller pre-aiming distance is used, the vehicle can be quickly pulled back to the tracked path, but is easy to overshoot, if the excessive pre-aiming distance is used, the steady state error after stabilizing to the tracked path is larger, so that the proper pre-aiming distance needs to be matched according to the lateral position deviation, and the problems of overshoot and the larger steady state error after stabilizing to the tracked path are avoided.
Experiments prove that the initial transverse position deviation value e y =1m, initial heading deviation angle β c When=0° (see initial heading deviation angle in fig. 4, which is the angle between the heading of the vehicle and the heading corresponding to the tracking position point), and the pre-aiming distance is 1m, the condition of overshoot (the overshoot of the vehicle lateral deviation value is about 0.3 m) can be found in fig. 5A, thus proving that the initial lateral position deviation e y When=1m, the pre-aiming distance (1 m) is not enough, resulting in overshoot, but referring to Matlab simulation result fig. 5B, it is found that the steady state error after stabilizing to the tracking path is higherSmall (within + -5 cm). In the subsequent experiments, under the condition of the deviation, the pretightening distance is gradually increased, and the experiments find that the overshoot phenomenon is improved, but when the pretightening distance is increased to a certain value in the condition, the steady state error after stabilizing to the tracking path starts to increase, for example, under the condition of the same deviation, after increasing the pretightening distance to 2m, the vehicle overshoot is smaller as seen in fig. 6A by referring to the result of the Carsim simulation, but the steady state error after stabilizing to the tracking path is larger as seen in fig. 6B by referring to the result of the Matlab simulation (for example, the steady state error is larger when the tracking path in fig. 6A has continuous curve road conditions).
After a large number of experiments prove that the influence of the pre-aiming distance on the transverse tracking error is found, when the transverse position deviation value is large, the pre-aiming distance is relatively far, and when the transverse position deviation value is small, the pre-aiming distance is relatively near, so that the purposes of reducing the overshoot of the vehicle and reducing the steady state error after stabilizing the tracking path can be achieved.
In an alternative embodiment, for example, an experiment is performed using the pre-aiming distance correspondence information corresponding to fig. 3, and the initial lateral position deviation value e y Set to 1m, initial heading deviation angle beta c Setting to 10 degrees, under the deviation condition, the selected initial pre-aiming distance is 2.7m, the condition that no overshoot occurs can be seen by referring to a Carsim simulation result diagram 7A, and the steady state error after the tracking path is stabilized can be seen to be very small by referring to a Matlab simulation result diagram 7B. Therefore, experimental data prove that the use of the pre-aiming distance corresponding relation information provided by the embodiment can ensure that the vehicle is prevented from overshooting as much as possible when the vehicle converges on the tracking path from a larger transverse position deviation value, and meanwhile, the steady-state error after the vehicle is stabilized on the tracking path is greatly reduced.
S13, acquiring a correction coefficient aiming at the basic pre-aiming distance, wherein the correction coefficient comprises at least one of a speed correction coefficient, a path curvature correction coefficient and a course angle correction coefficient.
In an alternative embodiment, in step S13, acquiring the correction system for the basic pretighted distance may include: acquiring a current vehicle speed, and acquiring a speed correction coefficient corresponding to the current vehicle speed from speed correction coefficient corresponding relation information (wherein the speed correction coefficient corresponding relation information indicates the corresponding relation between the vehicle speed and the speed correction coefficient); and/or, acquiring a path curvature mean value of the tracking path, and acquiring a curvature correction coefficient corresponding to the path curvature mean value and the acquired lateral position deviation value (wherein, the corresponding relation among the lateral position deviation value, the path curvature mean value and the curvature correction coefficient) from the curvature correction coefficient corresponding relation information; and/or determining an initial pre-aiming point on the tracking path according to the basic pre-aiming distance, acquiring a course deviation angle according to the advancing direction of the vehicle and the course corresponding to the initial pre-aiming point, and acquiring a course angle correction coefficient corresponding to the course deviation angle and the acquired transverse position deviation value from course angle correction coefficient corresponding relation information (wherein the course angle correction coefficient corresponding relation information indicates the corresponding relation of the transverse position deviation value, the course deviation angle and the course angle correction coefficient).
In an alternative embodiment, in the step of obtaining the current vehicle speed and obtaining the speed correction coefficient corresponding to the current vehicle speed from the speed correction coefficient correspondence information, the speed correction coefficient correspondence information includes a correspondence between the vehicle speed and the speed correction coefficient, and the relationship formula ψ may be used v =f (v) denotes (ψ) v Representing the speed correction factor, v representing the degree of vehicle).
In an alternative embodiment, the speed correction coefficient correspondence information may be set according to a principle that the speed correction coefficient ψ needs to be increased based on the basic pretightening distance because the pretightening distance should be correspondingly increased when the vehicle speed is increased due to the delay of the steering system v . Speed correction coefficient psi of vehicle speed in speed correction coefficient corresponding relation information v Referring to FIG. 8, when the vehicle speed is less than 2.5Km/h, no correction is required, and the speed correction coefficient ψ is the same as that of the vehicle speed v Set to 1; when the vehicle speed is greater than 2.5Km/h, the correction is needed, and a speed correction coefficient psi greater than 1 is selected v And (5) performing correction.
In an optional embodiment, in the step of obtaining a path curvature average value of the tracking path and obtaining a curvature correction coefficient corresponding to the path curvature average value and the obtained lateral position deviation value from curvature correction coefficient correspondence information, the curvature correction coefficient correspondence information includes correspondence between the lateral position deviation value, the path curvature average value and the curvature correction coefficient, and the relationship formula ψ may be used c ＝f(C a ，e y ) Representation (C) a Represent the path curvature mean value e y Represents the lateral position deviation value, ψ c Representing the curvature correction coefficient).
In an alternative embodiment, the setting principle of the curvature correction coefficient correspondence information may be that, in order to enable the initial vehicle position with a larger lateral position deviation value of the vehicle to quickly converge on the tracking path without excessive overshoot, the pretightening distance should be adjusted according to the curvature and the lateral position deviation value on the tracking path, the pretightening distance should be shorter when the curvature of the tracking path is small, so that the vehicle returns to the path as soon as possible, and the pretightening distance should be longer when the curvature of the tracking path is larger, so that the curvature correction coefficient ψ needs to be increased on the basis of the above C Since there is no need to have a certain relationship with the path curvature after the vehicle is stably tracked, the curvature correction coefficient ψ should be set after the vehicle is stably tracked C Is set to 1, and the path curvature C and the lateral position deviation value e can be obtained according to the characteristics y And coefficient psi C See fig. 9 for relationships.
In an optional embodiment, the step of obtaining the path curvature average value of the tracking path and obtaining the curvature correction coefficient corresponding to the path curvature average value and the obtained lateral position deviation value from the curvature correction coefficient correspondence information may include: determining an initial pre-aiming point on a tracking path according to the basic pre-aiming distance; and calculating the path curvature mean value from the tracking position point to the initial pre-aiming point according to the tracking position point and the initial pre-aiming point on the tracking path.
In an alternative embodiment, the step of calculating the path curvature average value from the tracking position point to the initial pre-aiming point according to the tracking position point and the initial pre-aiming point on the tracking path may include: acquiring the number of the position points from the tracking position point to the initial pre-aiming point on the tracking path and the curvature of each position point; and calculating a path curvature average value according to the number of the position points and the curvature of each position point through a curvature average value calculation formula (namely, the path curvature can be the path curvature average value from the tracking position point to the initial pre-aiming point).
In an alternative embodiment, the path curvature mean calculation formula includes:wherein C is 1 、C 2 ...C n Each represents the curvature of a certain position point on the path, and n represents the number of position points between the tracking position point and the initial pre-aiming point.
In an alternative embodiment, taking a right angle curved path tracked by a vehicle as an example, the convergence distances before and after the curvature correction are compared, for example, the vehicle lateral control is performed with the same vehicle initial lateral position deviation value and the same vehicle speed, the convergence speed after the curvature correction is faster according to the simulation result of the path tracking before the curvature correction fig. 10A and the simulation result of the path tracking after the curvature correction fig. 11A, the convergence speed after the curvature correction is faster according to the simulation result of the lateral deviation change before the curvature correction fig. 10B and the simulation result of the lateral deviation change before the curvature correction fig. 11B, the convergence distances before the curvature correction are all stabilized when the mileage is about 7.5m, the convergence distances after the curvature correction are all stabilized when the mileage is about 5.5m, and the convergence distance after the curvature correction is shorter than the convergence distance before the curvature correction by about 2m, so that the stable path tracking after the curvature correction is faster.
In an alternative embodiment, an initial pre-aiming point is determined according to the basic pre-aiming distance, a heading deviation angle is obtained according to the advancing direction of the vehicle and the heading corresponding to the initial pre-aiming point, and a heading angle correction system is usedIn the step of obtaining the heading angle correction coefficient corresponding to the heading deviation angle and the obtained lateral position deviation value in the number correspondence information, the corresponding relationship information of the heading angle correction coefficient includes the correspondence relationship of the lateral position deviation value, the heading deviation angle and the heading angle correction coefficient, and the relationship formula ψ can be used a ＝f(β p ，e y ) Representation (wherein e y Representing the lateral position deviation value, beta p Represents heading deviation angle, psi a Representing the heading angle correction factor). Fig. 12 may be referred to as a map corresponding to the heading angle correction coefficient correspondence information.
In an alternative embodiment, the course angle correction factor correspondence information setting principle may be that since the starting position of the vehicle is sometimes at a curve, when the course angle of the vehicle deviates from the course angle of the pre-aiming point on the path by a deviation beta μ Overshoot easily occurs when the speed is too large, so that the course angle correction coefficient needs to be set for debugging so as to avoid course angle deviation beta μ Overshoot occurs when it is too large. Taking a right angle bend as an example, referring to a curve simulation result FIG. 13A, the lateral position deviation is (13, 1), and the initial heading deviation angle beta c Respectively [10, -10,5, -5,0 ]]As a result of the simulation, the lateral position deviation changes in FIG. 13B, and overshoot appears in all the working conditions. These conditions are mainly due to the heading deviation angle beta formed by the heading of the vehicle, the heading of which corresponds to the initial pre-aiming point p The excessive result is that, in order to enable the vehicle to stably converge and not overshoot at different initial deviations (different initial lateral position deviations, different initial heading deviation angles) and at different curvatures of the adjacent points of the tracked path, the heading angle correction coefficient psi is increased a The heading angle correction coefficient psi a Not only the heading deviation angle beta corresponding to the initial pre-aiming point p It is also related to whether the vehicle is inside or outside a curve, the heading deviation angle beta corresponding to the initial pre-aiming point at the inside of the curve p The larger the vehicle pre-aiming distance is, so that the vehicle turns in advance and is not over-adjusted, and the initial pre-aiming point corresponds to the outside of the curveHeading deviation angle beta of (2) μ The larger the vehicle pre-aiming distance should be, the smaller so that the vehicle converges on the tracked path as soon as possible. Because the vehicle does not need to be stably tracked according to the heading deviation angle beta corresponding to the initial pre-aiming point p Adjusting the pretightening distance, wherein the heading angle correction coefficient psi is a Should be set to 1, deriving beta based on the above characteristics p 、e y 、ψ a Relationship diagram 12. Wherein, the heading deviation angle beta corresponding to the initial pre-aiming point p Depending on whether the vehicle is inside or outside the curve, and whether the vehicle heading angle is positive or negative with respect to the pre-aiming heading angle.
As can be seen from the graphs of the vehicle control effects before correction, referring to fig. 13A and 13B, and the vehicle control effects after correction, referring to fig. 14A and 15B, the overshoot before correction is up to more than 10cm but less than 20cm, and the overshoot after correction is less than 5cm, so that the control requirements of industry desiring to realize the steady-state lateral deviation within ±5cm can be satisfied.
S14, acquiring a target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance.
In a first alternative embodiment, in step S14, obtaining the target pretightening distance according to the correction coefficient and the basic pretightening distance may include: and acquiring a first target pre-aiming distance according to the speed correction coefficient and the basic pre-aiming distance, wherein the speed correction coefficient and the basic pre-aiming distance are in a direct proportion relation. Wherein the first target pre-aiming distance acquiring formula is as follows: l (L) d ′＝ψ v l; wherein L is d ' denotes a first target pre-aiming distance, ψ v Indicating a velocity correction factor, and l indicating a basic pretightening distance.
In a second alternative embodiment, in step S14, acquiring the target pretighted distance according to the correction coefficient and the basic pretighted distance may include: and acquiring a first target pre-aiming distance according to the course angle correction coefficient and the basic pre-aiming distance, wherein the course angle correction coefficient and the basic pre-aiming distance are in a direct proportion relation. Wherein the first target pre-aiming distance acquiring formula is as follows: l (L) d ′＝ψ a l; wherein L is d ' denotes a first target pre-aiming distance, ψ a And the heading angle correction coefficient is represented, and l represents the basic pretightening distance.
In a third alternative embodiment, in step S14, obtaining the target pretightening distance according to the correction coefficient and the basic pretightening distance may include: and acquiring a first target pre-aiming distance according to the path curvature correction coefficient and the basic pre-aiming distance, wherein the path curvature correction coefficient and the basic pre-aiming distance are in a direct proportion relation. Wherein the first target pre-aiming distance acquiring formula is as follows: l (L) d ′＝ψ C l; wherein L is d ' denotes a first target pre-aiming distance, ψ C The path curvature correction coefficient is represented, and l represents the basic pretightening distance.
In an alternative embodiment, in step S14, obtaining the target pretightening distance according to the correction coefficient and the basic pretightening distance may include: acquiring a target pre-aiming distance according to the first target pre-aiming distance and an optimization correction coefficient, wherein the first target pre-aiming distance and the optimization correction coefficient are in a direct proportion relation; the optimized correction coefficients are correction coefficients except for the correction coefficients corresponding to the first target pre-aiming distance. For example, the first target pretighted distance acquisition formula is L d ′＝ψ v l, wherein, ψ v To modify the coefficients, the optimized modification coefficients may include ψ C 、ψ a Therefore, the pretighted distance correction formula includes: l (L) d ＝ψ C L d ', or L d ＝ψ a L d ', or L d ＝ψ c ψ a L d ′。
In a fourth alternative embodiment, in step S14, acquiring the target pretighted distance according to the correction coefficient and the basic pretighted distance may include: substituting the speed correction coefficient, the path curvature correction coefficient, the course angle correction coefficient and the basic pretightening distance into a pretightening distance correction formula to obtain a target pretightening distance; pretarget distance correctionThe formula includes: l (L) d ＝ψ v ψ C ψ a l; wherein L is d Represents the target pre-aiming distance, psi v Representing the velocity correction factor, ψ C Represents the path curvature correction coefficient, ψ a And the heading angle correction coefficient is represented, and l represents the basic pretightening distance.
In an alternative embodiment, the target pretighted distance obtained by the pretighted distance correction formula is within a limited distance range, and the limited distance range is 1 m to 3.6 m. The target pre-aiming distance obtained by the pre-aiming distance correction formula is within a limited distance range, so that the vehicle can be stably tracked to a tracking path when being transversely controlled, and the phenomenon of overshoot is almost avoided when the vehicle is converged to the tracking path.
And S15, performing transverse driving control according to the target pre-aiming distance.
In an alternative embodiment, in step S15, the lateral driving control according to the target pre-aiming distance may include: and performing transverse driving control according to the first target pre-aiming distance or the target pre-aiming distance obtained by optimizing the first target pre-aiming distance.
In an alternative embodiment, in step S15, the lateral driving control according to the target pre-aiming distance may include: determining a pre-aiming point on a tracking path according to the target pre-aiming distance; acquiring a vehicle pre-aiming angle according to a coordinate system established based on a basic principle of a pure tracking algorithm and a pre-aiming point on a tracking path (for example, acquiring the vehicle pre-aiming angle according to an origin of the coordinate system and the pre-aiming point on a forward X-axis tracking path); substituting the target pre-aiming distance and the vehicle pre-aiming angle into a turning radius calculation formula to calculate the turning radius of the vehicle; calculating a steering wheel angle according to a steering wheel angle calculation formula corresponding to the vehicle and a vehicle turning radius; the turning system of the vehicle is controlled according to the steering wheel angle.
In an alternative embodiment, the turning radius calculation formula includes:wherein R represents the turning radius of the vehicle, L d Representing a target pre-aiming distance, and alpha represents a vehicle pre-aiming angle; the steering wheel angle calculation formula includes: sta=α 1 ρ 5 +α 2 ρ 4 +α 3 ρ 3 +α 4 ρ 2 +α 5 ρ 1 +α 6 The method comprises the steps of carrying out a first treatment on the surface of the Wherein,wherein StA represents steering wheel angle, ρ represents turning curvature, α 1 、α 2 、α 3 、α 4 、α 5 、α 6 Are all formula coefficients, and the formula coefficients correspond to the model of the vehicle. Equation coefficients with the model of the vehicle, e.g. X model, alpha 1 38102.13, alpha 2 813.06, alpha 3 Is-10202.81, alpha 4 Is-39.63, alpha 5 2472.84, alpha 6 Is-0.29.
In an alternative implementation manner, after the vehicle driving control method provided by the embodiment is applied to a vehicle, referring to fig. 15A and 15B, when the tracking path is a small S curve path, the vehicle can stably converge at different initial position deviations, different initial heading deviation angles and different road curvatures, and almost no overshoot is achieved, so that the control requirement of industry desire to control the steady-state lateral deviation within ±5cm and the steady-state heading angle deviation within ±3° ismet. Referring to fig. 16A and 16B, when the tracking path is a right angle curve path, the vehicle can be stably converged at different initial position deviations, different initial heading deviation angles and different road curvatures, and almost no overshoot is achieved, so that the control requirement for the industry desiring to control the steady-state lateral deviation within ±5cm and the steady-state heading angle deviation within ±3° is met.
After the vehicle driving control method provided by the embodiment is applied to a vehicle, the vehicle is verified on a straight road, a large S curve, a small S curve, a right angle curve and a special curve. As can be seen from fig. 17, fig. 18, fig. 19, fig. 20, and fig. 21, respectively, for the real vehicle verification result of the straight road, the real vehicle verification result of the large S curve, the real vehicle verification result of the small S curve, the real vehicle verification result of the right angle curve, and the real vehicle verification result of the special-shaped curve, respectively, the initial deviation is different on the straight road, the large S curve, the small S curve, the right angle curve, or the special-shaped curve, the lateral position error is less than ±5cm after stable tracking, and the course angle deviation is within ±3°. Therefore, after the vehicle driving control method provided by the embodiment is applied to a vehicle, the vehicle driving control method can adapt to different roads and different initial deviations, ensure that the transverse position errors after stable tracking are smaller than +/-5 cm, and the course angle deviation is within +/-3 degrees, so that the control requirement of industry desiring is met.
In an alternative implementation manner, the vehicle driving control method provided in this embodiment may be applied to a lateral control module in a vehicle, and optionally, the lateral control module may perform steps S12 to S15. Referring to fig. 22, a lateral control module acquires information such as a tracking path, current position information of a vehicle, a vehicle speed and the like, performs lateral position deviation calculation, curvature calculation and vehicle course angle calculation, matches a basic pretightening distance and a correction coefficient thereof according to the calculation results, obtains a target pretightening distance to realize self-priming distance, transmits the obtained target pretightening distance to a pure tracking unit in the lateral control module, calculates control parameters (such as steering wheel angle information) through the pure tracking unit, and sends the control parameters to an actuator of the vehicle to realize lateral driving control.
The vehicle driving control method provided in the first embodiment of the present application includes: and S11, path planning is carried out to acquire a tracking path. And S12, acquiring a basic pretightening distance according to the current position information of the vehicle and the tracking path. S13, acquiring a correction coefficient aiming at the basic pre-aiming distance, wherein the correction coefficient comprises at least one of a speed correction coefficient, a path curvature correction coefficient and a course angle correction coefficient. S14, acquiring a target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance. And S15, performing transverse driving control according to the target pre-aiming distance. Therefore, the vehicle driving control method provided in the first embodiment of the application can optimize the calculation parameters of the path following algorithm according to the details of the driving scene (such as the vehicle speed, the path curvature of the tracking path, the course angle deviation angle and the like), so as to achieve the purpose of optimizing the path following algorithm in the passenger parking function, improve the control precision during low-speed unmanned driving to ensure the safety of the vehicle and the reliability of the function, and further improve the use experience of the user. In addition, the vehicle driving control method provided in the first embodiment of the application can optimize the path following algorithm, and achieve a good calculation effect with a small calculation amount, so that in an environment where parking is performed or fixed-point parking is performed in low-speed automatic driving, the steady-state lateral deviation is controlled within a small range (for example, within ±5 cm), the steady-state course angle deviation is controlled within a small range (for example, within ±3°), and the vehicle can be well adjusted to the tracking path even if the starting position of the vehicle deviates from the tracking path by a large amount, and the convergence speed is high and the overshoot is small.
In addition, the vehicle driving control method provided by the first embodiment of the application can adaptively adjust the pre-aiming distance according to the vehicle speed, the path curvature of the tracking path, the course angle deviation angle and the transverse deviation, so that the vehicle can quickly converge at different initial positions and at different angles, can adapt to different road curvatures, and can meet certain control precision, particularly has good control effect under the condition of large initial deviation of the vehicle, and solves the defects of fixed pre-aiming distance or pre-aiming distance adjusted only according to the vehicle speed in transverse control, such as easy overshoot, slow convergence speed, large steady state error and the like when the initial deviation of the vehicle is large. The vehicle driving control method provided in the first embodiment can be applied to different roads, for example: straight line, right angle bend, little S bend, big S bend, the circular arc of different curvatures, dysmorphism bend etc. even the route that the driver was opened at will also can follow steadily, and steady state deviation is less, and the vehicle driving control method that applies for the first embodiment to provide can converge fast and overshoot less under the circumstances of big deviation. The vehicle driving control method provided in the first embodiment of the application not only can satisfy parking functions (e.g., passenger parking, full-automatic parking, semi-automatic parking) but also can satisfy functions related to low-speed unmanned operation (e.g., autonomous wireless charging, unmanned park connection vehicle, unmanned park sweeper). Because the steering wheel angle and the front wheel angle have nonlinear relations, and the nonlinear relations of the steering wheel angles and the front wheel angles of different vehicle types are different, the vehicle driving control method provided by the first embodiment of the application can obtain more accurate relations by calibrating the relations between the steering wheel angles and the vehicle turning radii, and thus, better steady-state following effects can be obtained. The vehicle driving control method provided in the first embodiment has the advantages of small code amount, high operation efficiency, good embedment and low requirement on hardware when being executed by a computer.
Second embodiment:
fig. 23 is a schematic structural view of a vehicle driving control device provided in a second embodiment of the present application. For a clear description of the vehicle driving control apparatus 1 provided in the second embodiment of the present application, please refer to fig. 23.
The vehicle driving control apparatus 1 provided in the second embodiment of the present application includes: a processor a101 and a memory a201, wherein the processor a101 is configured to execute a computer program A6 stored in the memory a201 to implement the steps of the vehicle driving control method as described in the first embodiment.
In an embodiment, the vehicle driving control apparatus 1 provided in this embodiment may include at least one processor a101 and at least one memory a201. Wherein the at least one processor a101 may be referred to as a processing unit A1 and the at least one memory a201 may be referred to as a storage unit A2. Specifically, the storage unit A2 stores a computer program A6 that, when executed by the processing unit A1, causes the vehicle driving control apparatus 1 provided by the present embodiment to implement the steps of the vehicle driving control method as described in the first embodiment, for example, S11 shown in fig. 1, to perform path planning to acquire a tracking path; s12, acquiring a basic pre-aiming distance according to the current position information of the vehicle and a tracking path; s13, acquiring a correction coefficient aiming at a basic pre-aiming distance, wherein the correction coefficient comprises at least one of a speed correction coefficient, a path curvature correction coefficient and a course angle correction coefficient; s14, acquiring a target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance; and S15, performing transverse driving control according to the target pre-aiming distance.
In an embodiment, the vehicle driving control apparatus 1 provided in the present embodiment may include a plurality of memories a201 (simply referred to as a storage unit A2).
The storage unit A2 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Wherein the nonvolatile Memory may be Read Only Memory (ROM), programmable Read Only Memory (PROM, programmable Read-Only Memory), erasable programmable Read Only Memory (EPROM, erasable Programmable Read-Only Memory), electrically erasable programmable Read Only Memory (EEPROM, electrically Erasable Programmable Read-Only Memory), magnetic random access Memory (FRAM, ferromagnetic random access Memory), flash Memory (Flash Memory), magnetic surface Memory, optical disk, or compact disk-Read Only Memory (CD-ROM, compact Disc Read-Only Memory); the magnetic surface memory may be a disk memory or a tape memory. The volatile memory may be random access memory (RAM, random Access Memory), which acts as external cache memory. By way of example, and not limitation, many forms of RAM are available, such as static random access memory (SRAM, static Random Access Memory), synchronous static random access memory (SSRAM, synchronous Static Random Access Memory), dynamic random access memory (DRAM, dynamic Random Access Memory), synchronous dynamic random access memory (SDRAM, synchronous Dynamic Random Access Memory), double data rate synchronous dynamic random access memory (ddr SDRAM, double Data Rate Synchronous Dynamic Random Access Memory), enhanced synchronous dynamic random access memory (ESDRAM, enhanced Synchronous Dynamic Random Access Memory), synchronous link dynamic random access memory (SLDRAM, syncLink Dynamic Random Access Memory), direct memory bus random access memory (DRRAM, direct Rambus Random Access Memory). The memory cell A2 described in the embodiments of the present application is intended to comprise, without being limited to, these and any other suitable types of memory.
In an embodiment, the vehicle driving control apparatus 1 further includes a bus connecting different components (e.g., the processor a101 and the memory a201, etc.).
In an embodiment, the vehicle driving control apparatus 1 in the present embodiment may further include a communication interface (e.g., I/O interface A3) that may be used to communicate with an external device.
In an implementation manner, the terminal 1 provided in this embodiment may further include a communication device A5.
The vehicle driving control device 1 provided in the second embodiment of the present application includes a memory a101 and a processor a201, where the processor a101 is configured to execute a computer program A6 stored in the memory a201 to implement the steps of the vehicle driving control method described in the first embodiment, so that the vehicle driving control device 1 provided in this embodiment can optimize the calculation parameters of the path following algorithm according to the details of the driving scenario, thereby implementing the purpose of optimizing the path following algorithm in the proxy parking function, improving the control precision during low-speed unmanned driving to ensure the vehicle safety and the reliability of the function, and further improving the use experience of the user.
The second embodiment of the present application also provides a computer-readable storage medium storing a computer program A6, which when executed by the processor a101, implements steps of the vehicle driving control method as in the first embodiment, such as steps S11 to S15 shown in fig. 1.
In an implementation, the computer readable storage medium provided by the present embodiment may include any entity or device capable of carrying computer program code, a recording medium, e.g., ROM, RAM, magnetic discs, optical discs, flash memories, etc.
According to the computer program A6 stored in the computer readable storage medium, when being executed by the processor A101, the computer program A6 can optimize calculation parameters of the path following algorithm according to the detail condition of a driving scene, so that the purpose of optimizing the path following algorithm in the passenger parking function is achieved, the control precision of low-speed unmanned driving is improved to ensure the safety of vehicle use and the reliability of functions, and the use experience of a user can be improved.
The second embodiment of the application further provides a vehicle, see fig. 24, where the vehicle includes the vehicle classroom control device or the transverse control module as described above, so that the vehicle provided by the second embodiment of the application can optimize the calculation parameters of the path following algorithm according to the detail condition of the driving scene, thereby realizing the purpose of optimizing the path following algorithm in the passenger parking function, improving the control precision of the low-speed unmanned vehicle to ensure the safety of the vehicle and the reliability of the function, and further improving the use experience of the user.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the element defined by the phrase "comprising one … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element, and furthermore, elements having the same name in different embodiments of the present application may have the same meaning or may have different meanings, a particular meaning of which is to be determined by its interpretation in this particular embodiment or by further combining the context of this particular embodiment.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context. Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including" specify the presence of stated features, steps, operations, elements, components, items, categories, and/or groups, but do not preclude the presence, presence or addition of one or more other features, steps, operations, elements, components, items, categories, and/or groups. The terms "or" and/or "as used herein are to be construed as inclusive, or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a, A is as follows; b, a step of preparing a composite material; c, performing operation; a and B; a and C; b and C; A. b and C). An exception to this definition will occur only when a combination of elements, functions, steps or operations are in some way inherently mutually exclusive.
It should be understood that, although the steps in the flowcharts in the embodiments of the present application are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily occurring in sequence, but may be performed alternately or alternately with other steps or at least a portion of the other steps or stages.
The foregoing description of the preferred embodiment of the present invention is provided for the purpose of illustration only, and is not intended to limit the invention to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Claims (13)

  1. A vehicle driving control method, characterized by comprising:
    path planning is carried out to obtain a tracking path;
    acquiring a basic pre-aiming distance according to the current position information of the vehicle and the tracking path;
    Acquiring a correction coefficient aiming at the basic pre-aiming distance, wherein the correction coefficient comprises at least one of a speed correction coefficient, a path curvature correction coefficient and a course angle correction coefficient;
    acquiring a target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance;
    and performing transverse driving control according to the target pre-aiming distance.
  2. The vehicle driving control method according to claim 1, wherein the step of acquiring a basic pretightening distance from the vehicle current position information and the tracking path includes:
    acquiring a tracking position point corresponding to the current position information of the vehicle on the tracking path;
    acquiring a transverse position deviation value according to the current position information of the vehicle and the tracking position point;
    and acquiring the basic pretightening distance corresponding to the transverse position deviation value from pretightening distance corresponding relation information, wherein the pretightening distance corresponding relation information comprises the corresponding relation between at least one transverse position deviation value and the basic pretightening distance.
  3. The vehicle driving control method according to claim 2, characterized in that the step of obtaining the correction coefficient for the basic pretighted distance includes:
    Acquiring a current vehicle speed, and acquiring a speed correction coefficient corresponding to the current vehicle speed from speed correction coefficient corresponding relation information, wherein the speed correction coefficient corresponding relation information indicates the corresponding relation between the vehicle speed and the speed correction coefficient;
    the step of obtaining the target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance comprises the following steps:
    and acquiring a first target pre-aiming distance according to the speed correction coefficient and the basic pre-aiming distance, wherein the speed correction coefficient and the basic pre-aiming distance are in a direct proportion relation.
  4. The vehicle driving control method according to claim 2, characterized in that the step of obtaining the correction coefficient for the basic pretighted distance includes:
    determining an initial pretightening point on the tracking path according to the basic pretightening distance;
    acquiring a heading deviation angle according to the advancing direction of the vehicle and the heading corresponding to the initial pre-aiming point;
    acquiring the course angle correction coefficient corresponding to the course deviation angle and the transverse position deviation value from course angle correction coefficient corresponding relation information, wherein the course angle correction coefficient corresponding relation information indicates the corresponding relation among the transverse position deviation value, the course deviation angle and the course angle correction coefficient;
    The step of obtaining the target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance comprises the following steps:
    and acquiring a first target pre-aiming distance according to the course angle correction coefficient and the basic pre-aiming distance, wherein the course angle correction coefficient and the basic pre-aiming distance are in a direct proportion relation.
  5. The vehicle driving control method according to claim 2, characterized in that the step of obtaining the correction coefficient for the basic pretighted distance includes:
    acquiring a path curvature average value of the tracking path;
    acquiring the curvature correction coefficient corresponding to the path curvature mean value and the transverse position deviation value from curvature correction coefficient corresponding relation information, wherein the curvature correction coefficient corresponding relation information indicates the corresponding relation among the transverse position deviation value, the path curvature mean value and the curvature correction coefficient;
    the step of obtaining the target pre-aiming distance according to the correction coefficient and the basic pre-aiming distance comprises the following steps:
    and acquiring a first target pre-aiming distance according to the path curvature correction coefficient and the basic pre-aiming distance, wherein the path curvature correction coefficient and the basic pre-aiming distance are in a direct proportion relation.
  6. The vehicle driving control method according to claim 5, characterized in that the step of obtaining the path curvature average value of the tracking path includes:
    determining an initial pretightening point on the tracking path according to the basic pretightening distance;
    and calculating the path curvature average value from the tracking position point to the initial pre-aiming point according to the tracking position point and the initial pre-aiming point on the tracking path.
  7. The vehicle driving control method according to any one of claims 3 to 6, characterized in that the step of acquiring a target pre-aiming distance from the correction coefficient and the basic pre-aiming distance includes:
    acquiring the target pre-aiming distance according to the first target pre-aiming distance and an optimization correction coefficient, wherein the first target pre-aiming distance and the optimization correction coefficient are in a proportional relationship;
    the optimized correction coefficient is a correction coefficient except for a correction coefficient corresponding to the first target pre-aiming distance.
  8. The vehicle driving control method according to claim 1, wherein the step of performing lateral driving control in accordance with the target pre-aiming distance includes:
    Determining a pretightening point on the tracking path according to the target pretightening distance;
    acquiring a vehicle pre-aiming angle according to a coordinate system established based on a basic principle of a pure tracking algorithm and the pre-aiming point on the tracking path;
    substituting the target pre-aiming distance and the vehicle pre-aiming angle into a turning radius calculation formula to calculate the turning radius of the vehicle;
    calculating a steering wheel angle according to the vehicle turning radius and a steering wheel angle corresponding to the vehicle;
    and controlling a turning system of the vehicle according to the steering wheel angle.
  9. The vehicle driving control method according to claim 8, characterized in that the turning radius calculation formula includes:
    wherein R represents the turning radius of the vehicle, L d Representing the target pre-aiming distance, wherein alpha represents the pre-aiming angle of the vehicle;
    the steering wheel angle calculation formula includes:
    StA＝α 1 ρ 5 +α 2 ρ 4 +α 3 ρ 3 +α 4 ρ 2 +α 5 ρ 1 +α 6 ；
    wherein,
    wherein StA represents the steering wheel angle, ρ represents the turning curvature, α 1 、α 2 、α 3 、α 4 、α 5 、α 6 Are formula coefficients corresponding to the model of the vehicle.
  10. The vehicle driving control method according to claim 1, characterized in that the target pre-aiming distance is within a defined distance range of 1 meter to 3.6 meters.
  11. A vehicle driving control apparatus, characterized by comprising a memory and a processor;
    the processor is configured to execute a computer program stored in the memory to implement the steps of the vehicle driving control method according to any one of claims 1 to 10.
  12. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the vehicle driving control method according to any one of claims 1 to 10.
  13. A vehicle characterized in that the vehicle includes the vehicle driving control apparatus according to claim 11.
CN202180072808.9A 2021-01-28 2021-01-28 Vehicle driving control method and device, vehicle and storage medium Pending CN116457259A (en)

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CN115179935A (en) * 2022-09-13 2022-10-14 毫末智行科技有限公司 Path tracking method and device, electronic equipment and storage medium
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