CN116700097A - Automatic driving vehicle control method and system based on pre-aiming control and vehicle - Google Patents

Automatic driving vehicle control method and system based on pre-aiming control and vehicle Download PDF

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Publication number
CN116700097A
CN116700097A CN202310766270.2A CN202310766270A CN116700097A CN 116700097 A CN116700097 A CN 116700097A CN 202310766270 A CN202310766270 A CN 202310766270A CN 116700097 A CN116700097 A CN 116700097A
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vehicle
path
obtaining
information
aiming
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阳志
肖川
文滔
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Chongqing Changan Automobile Co Ltd
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Chongqing Changan Automobile Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G05B19/0423—Input/output
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/25—Pc structure of the system
    • G05B2219/25257—Microcontroller

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The invention relates to an automatic driving vehicle control method and system based on pre-aiming control and a vehicle, wherein the method comprises the following steps: acquiring external environment information and vehicle body information and obtaining prediction information according to the external environment information; obtaining a decision signal according to the prediction information and the vehicle body information; obtaining a local path according to the decision signal; obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path; obtaining a steering wheel corner according to the pre-aiming distance and the transverse error of the pre-aiming point; and obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel rotation angle when the path tracking error is smaller than a preset threshold value, and performing feedback compensation on the steering wheel rotation angle when the path tracking error is larger than or equal to the preset threshold value. The invention can not only meet the real-time requirement when carrying out path tracking, but also carry out feedback compensation on steering angle, thereby improving the path tracking precision of the vehicle in a low-speed complex scene.

Description

Automatic driving vehicle control method and system based on pre-aiming control and vehicle
Technical Field
The invention relates to the technical field of automatic driving, in particular to an automatic driving vehicle control method and system based on pre-aiming control and a vehicle.
Background
An autonomous vehicle system is a complex system capable of automatically performing acceleration, braking, steering, following, waiting, and other various operations by sensing the surrounding environment and combining the own vehicle state information to finally reach a destination. In a complex scene of a garage and a parking lot, which require automatic driving vehicles to run at a low speed and have more accidental factors, the current automatic driving vehicle control method mainly comprises methods of PID control, model prediction control, pre-aiming control and the like. The PID (proportional integral derivative) control needs to ensure the stability of the state of the vehicle, and needs a lot of time and cost to repeatedly debug parameters, so that the calculation force required by the model predictive control is large, and the real-time tracking performance of the automatic driving vehicle can be affected.
For pre-aiming control, the tracking function of an automatic vehicle can be basically ensured, but when the path and the speed are continuously changed, the control precision is greatly influenced, so that the path tracking precision is reduced.
Accordingly, the prior art is still in need of improvement.
Disclosure of Invention
The invention aims to provide an automatic driving vehicle control method based on pre-aiming control, which solves the problem that in the prior art, when a pre-aiming control mode is adopted in a scene such as a garage and a parking lot where automatic driving vehicles are required to run at a low speed, the control precision is affected when the path and the speed are continuously changed, so that the tracking precision is reduced; another object of the present invention is to provide an autonomous vehicle control system; it is a further object of the present invention to provide a vehicle.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
an automatic driving vehicle control method based on pre-aiming control, comprising: acquiring external environment information and vehicle body information and obtaining prediction information according to the external environment information; the external environment information comprises obstacle information, parking space information and lane information, and the vehicle body information comprises vehicle speed information and positioning information; obtaining a decision signal according to the prediction information and the vehicle body information; obtaining a local path according to the decision signal; obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path; obtaining a steering wheel corner according to the pre-aiming distance and the transverse error of the pre-aiming point; and obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel rotation angle when the path tracking error is smaller than a preset threshold, and performing feedback compensation on the steering wheel rotation angle according to the path tracking error when the path tracking error is larger than or equal to the preset threshold.
According to the technical means, the external environment information and the vehicle body information are obtained, analysis processing is carried out according to the external environment information to obtain the prediction information, and then the prediction information and the vehicle body information are combined to judge the place where the prediction information and the vehicle body information are located so as to obtain the decision signal, so that the local path can be obtained through the decision signal. And obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path, obtaining a steering wheel corner according to the pre-aiming distance and the pre-aiming point transverse error, judging whether the path tracking error is smaller than a preset threshold value after obtaining the steering wheel corner, if so, completing automatic driving vehicle control according to the current steering wheel corner, otherwise, performing feedback compensation on the steering wheel corner according to the path tracking error, and then performing automatic driving vehicle control. Therefore, after the local path is obtained, the transverse error of the pretightening distance and the pretightening point is obtained according to the local path, the steering wheel corner is obtained through the pretightening distance and the transverse error of the pretightening point, and whether the path tracking error meets the requirement is further judged after the steering wheel corner is obtained, so that the real-time requirement can be met when the path tracking is carried out, feedback compensation can be carried out on the steering wheel corner, and the path tracking precision of the vehicle in a low-speed complex scene is improved.
Further, the step of obtaining the local path according to the decision signal includes: when the vehicle is in the normal cruising state, the previous section of the current global path is intercepted to be used as a local path, and when the vehicle is in the abnormal cruising state, emergency danger avoiding is carried out.
According to the technical means, in the running process of the vehicle, the cruising state is judged first, if the vehicle is in the normal cruising state, the previous section of the current global path is normally intercepted to be used as the local path, and if the vehicle is detected to be in the abnormal state, the operations such as braking, following, stopping and getting rid of poverty are performed, so that the driving safety is improved.
Further, the step of judging whether the vehicle is in a normal cruising state currently, if so, intercepting a previous section of the current global path as a local path, and if not, carrying out emergency risk avoidance comprises the following steps:
when the vehicle is in straight line running, intercepting a section of global path in front of the current position of the vehicle as a local path;
when the vehicle is in a low-speed scene, intercepting a previous section of a current global path of the vehicle as a local path; the low-speed scene comprises a meeting scene and a winding obstacle scene.
According to the technical means, when the vehicle is detected to be in a normal running state and the vehicle is in a straight running state, namely, no obstacle is present and low-speed running is not needed, then a section of global path in front of the current position of the vehicle is taken as a local path, and when the vehicle needs to meet a vehicle, detours the obstacle and other scenes, the previous section of the current global path of the vehicle is taken as the local path, so that the path tracking precision of the low-speed scene is improved.
Further, the step of obtaining the transverse error of the pretightening distance and the pretightening point according to the vehicle body information and the local path includes:
performing coordinate transformation on the local path to obtain a vehicle absolute coordinate system;
obtaining a vehicle coordinate system according to the positioning information and the vehicle absolute coordinate system;
and according to the vehicle speed information and the curvature information of the previous section of route of the vehicle coordinate system, carrying out weight proportion distribution to obtain a pre-aiming distance and a pre-aiming point transverse error.
According to the technical means, based on the obtained local path, the transverse error of the pre-aiming distance and the pre-aiming point is calculated by combining the vehicle speed information, so that reference data is provided for adjusting the steering wheel angle.
Further, the step of obtaining the transverse error of the pretightening distance and the pretightening point according to the vehicle speed information and the local path further comprises the following steps:
and filtering the transverse errors of the pre-aiming distance and the pre-aiming point.
According to the technical means, the higher or lower error value can be filtered through filtering the transverse error of the pre-aiming point, so that the steering wheel angle cannot be adjusted to be too large in fluctuation, and steering wheel shake can be prevented.
Further, the step of obtaining the steering wheel angle according to the transverse error between the pre-aiming distance and the pre-aiming point comprises the following steps:
obtaining a wheel corner of the vehicle according to the transverse error of the pre-aiming distance and the pre-aiming point;
obtaining a steering wheel corner according to the wheel corner of the vehicle and the vehicle transmission ratio;
and carrying out filtering treatment on the steering wheel angle.
According to the technical means, the steering wheel angle of the vehicle can be further obtained through the transverse error of the pre-aiming distance and the pre-aiming point, and the steering wheel angle is subjected to filtering treatment, so that steering wheel shake can be further prevented, and steering wheel control is smoother.
Further, the step of obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel angle when the path tracking error is smaller than a preset threshold, and performing feedback compensation on the steering wheel angle according to the path tracking error when the path tracking error is greater than or equal to the preset threshold comprises the following steps:
if the path tracking error is smaller than the preset threshold value, feeding back the steering wheel angle to an executing mechanism of the vehicle to complete automatic driving vehicle control;
and if the path tracking error is greater than or equal to the preset threshold value, carrying out feedback compensation calculation according to the path tracking error, and compensating the steering wheel angle according to the obtained compensation angle.
According to the technical means, after the steering wheel angle is obtained, whether the path tracking error meets the threshold requirement is further judged, if not, feedback compensation is carried out on the steering wheel angle until the steering wheel angle meets the requirement, and therefore the path tracking control precision can be improved.
An autonomous vehicle control system based on pre-sighting control, comprising:
the acquisition module is used for acquiring external environment information and vehicle body information and obtaining prediction information according to the external environment information;
the prediction and decision module is used for obtaining a decision signal according to the prediction information and the vehicle body information;
the planning module is used for obtaining a local path according to the decision signal;
the control module is used for obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path, obtaining a steering wheel corner according to the pre-aiming distance and the transverse error, obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel corner when the path tracking error is smaller than a preset threshold value, and performing feedback compensation on the steering wheel corner according to the path tracking error when the path tracking error is greater than or equal to the preset threshold value.
According to the technical means, the external environment information and the vehicle body information are firstly acquired through the acquisition module, then the prediction and decision module analyzes and processes according to the external environment information to obtain the prediction information, and then the prediction information and the vehicle body information are combined to judge the place where the prediction information and the vehicle body information are located to obtain the decision signal, so that the local path can be obtained through the decision signal. And the control module obtains a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path, obtains a steering wheel corner according to the pre-aiming distance and the pre-aiming point transverse error, judges whether the path tracking error is smaller than a preset threshold after obtaining the steering wheel corner, feeds back the current steering wheel corner to an actuating mechanism of the vehicle if the path tracking error is smaller than the preset threshold, completes automatic driving vehicle control, updates the vehicle body information to the acquisition module through the actuating mechanism, otherwise feeds back compensation to the steering wheel corner and then carries out automatic driving vehicle control. Therefore, after the local path is obtained, the transverse error of the pretightening distance and the pretightening point is obtained according to the local path, the steering wheel corner is obtained through the pretightening distance and the transverse error of the pretightening point, and whether the path tracking error meets the requirement is further judged after the steering wheel corner is obtained, so that the real-time requirement can be met when the path tracking is carried out, feedback compensation can be carried out on the steering wheel corner, and the path tracking precision of the vehicle in a low-speed complex scene is improved.
Further, the planning module includes:
and the judging unit is used for intercepting the previous section of the current global path as a local path when the vehicle is in the normal cruising state currently, and carrying out emergency danger avoidance when the vehicle is in the abnormal cruising state currently.
Further, the control module includes:
the conversion unit is used for carrying out coordinate conversion on the local path to obtain a vehicle absolute coordinate system, and obtaining a vehicle self coordinate system according to the positioning information and the vehicle absolute coordinate system;
the first calculation unit is used for carrying out weight proportion distribution according to the vehicle speed information and the curvature information of the previous section of route of the vehicle coordinate system to obtain a pre-aiming distance and a pre-aiming point transverse error;
the first filtering unit is used for filtering the transverse errors of the pre-aiming distance and the pre-aiming point;
the second calculation unit is used for obtaining a wheel corner of the vehicle according to the pre-aiming distance and the transverse error of the pre-aiming point, obtaining a steering wheel corner according to the wheel corner of the vehicle and the vehicle transmission ratio, obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel corner when the path tracking error is smaller than a preset threshold value, performing feedback compensation calculation according to the path tracking error when the path tracking error is greater than or equal to the preset threshold value, and compensating the steering wheel corner according to the obtained compensation angle;
and the second filtering unit is used for carrying out filtering treatment on the steering wheel angle.
A vehicle comprising a memory and a processor, the memory storing a computer program which when executed implements the steps of the method of controlling an autonomous vehicle based on pre-sighting control as described above.
A computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of the method of controlling an autonomous vehicle based on pre-sighting control as described above.
The invention has the beneficial effects that:
according to the invention, after the local path is obtained, the transverse error of the pretightening distance and the pretightening point is obtained according to the local path, the steering wheel corner is obtained through the pretightening distance and the transverse error of the pretightening point, and whether the path tracking error meets the requirement is further judged after the steering wheel corner is obtained, and when the path tracking is carried out, the real-time requirement can be met, and the feedback compensation can be carried out on the steering wheel corner, so that the path tracking precision of the vehicle in a low-speed complex scene is improved;
according to the invention, the steering wheel steering angle is adjusted without fluctuation too much by filtering the pre-aiming distance and the transverse error of the pre-aiming point, so that steering wheel shake can be prevented, and steering wheel shake can be further prevented by filtering the steering wheel steering angle, so that steering wheel control is smoother.
Drawings
Fig. 1 is a flowchart of an automatic driving vehicle control method based on pre-aiming control of the present invention.
FIG. 2 is a flow chart of overall control logic of an autonomous vehicle control method based on pre-sighting control in the present invention.
Fig. 3 is a schematic block diagram of an autonomous vehicle control system based on pre-sighting control in the present invention.
100, an acquisition module; 200. a prediction and decision module; 300. a planning module; 400. a control module; 500. an actuator.
Detailed Description
Further advantages and effects of the present invention will become readily apparent to those skilled in the art from the disclosure herein, by referring to the accompanying drawings and the preferred embodiments. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be understood that the preferred embodiments are presented by way of illustration only and not by way of limitation.
The embodiment provides an automatic driving vehicle control method based on pre-aiming control, as shown in fig. 1, which comprises the following steps:
s100, acquiring external environment information and vehicle body information, and acquiring prediction information according to the external environment information; the external environment information comprises obstacle information, parking space information and lane information, and the vehicle body information comprises vehicle speed information.
In this embodiment, the external environment information is obtained through an acquisition module of the vehicle, where the acquisition module includes various sensors and radars on the vehicle, such as a camera, an ultrasonic radar, a millimeter wave radar, a laser radar, and the like, and may be used to sense obstacle information, parking space information, and lane information such as a sign line, a lane line, and the like in a current scene of the vehicle. The body information mainly comprises various state information of the body and the chassis, such as vehicle speed information, brake information, current positioning information, vehicle state information and the like, and the body information can be given to a planning module of the vehicle to realize transverse and longitudinal control of the vehicle. Referring to fig. 2, after the vehicle turns on a low-speed (15 km/h) scene cruise function, external environment information and vehicle own information are acquired.
And S200, obtaining a decision signal according to the prediction information and the vehicle body information.
Referring to fig. 2, in this embodiment, after obtaining the sensing information fed back by the obtaining module, the prediction and decision module of the vehicle analyzes the obstacle (the obstacle may be a person, an automobile, a motorcycle, a cone, etc.) to obtain an attribute of the obstacle, where the attribute of the obstacle includes a position, an orientation, a dynamic and static attribute, etc., and predicts a subsequent situation according to a state of the obstacle to obtain part of scene information after a period of time, that is, prediction information. And then judging the current environment according to the prediction information and the vehicle body information, and outputting a decision signal to a planning module of the vehicle according to a judgment result, wherein the decision signal can directly influence the planning path and the tracking path of the vehicle, so that the riding comfort is improved.
S300, obtaining a local path according to the decision signal.
Referring to fig. 2, in this embodiment, after receiving the decision signal, the decision module of the vehicle obtains a local path to be tracked according to the decision signal (i.e. the current scene state of the vehicle), where the local path is a path to be tracked when the vehicle is in a low-speed scene such as a meeting, a winding obstacle, etc.
S400, obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path.
Referring to fig. 2, in this embodiment, after obtaining a local path to be tracked, a control module of a vehicle obtains a coordinate system of the vehicle according to the local path, and then calculates to obtain a pre-aiming distance and a transverse error of a pre-aiming point according to positioning information of the vehicle and curvature information of a previous path of the coordinate system of the vehicle.
The pretightening distance is related to the vehicle speed information and the curvature of the local path, the transverse error at the closest point of the pretightening distance is the transverse error of the pretightening point, namely the transverse error of the pretightening distance and the pretightening point, and the pretightening distance is equal to the product of the vehicle speed coefficient and the vehicle speed minus the product of the coefficient of pretightening curvature and the pretightening curvature, namely the pretightening distance = the vehicle speed coefficient, the vehicle speed and the coefficient of pretightening curvature.
S500, obtaining the steering wheel angle according to the pre-aiming distance and the transverse error of the pre-aiming point.
Referring to fig. 2, in this embodiment, after the lateral error between the pre-aiming distance and the pre-aiming point is obtained, the wheel angle of the vehicle is obtained according to the lateral error between the pre-aiming distance and the pre-aiming point, and then the steering wheel angle is obtained according to the wheel angle.
And S600, obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel rotation angle when the path tracking error is smaller than a preset threshold, and performing feedback compensation on the steering wheel rotation angle according to the path tracking error when the path tracking error is larger than or equal to the preset threshold.
Referring to fig. 2, in this embodiment, the preset threshold is an empirical value, and is generally set between 1 cm and 20 cm, for example, may be set to 1 cm, 10 cm, or 20 cm. The path tracking error refers to a lateral error between a vehicle position (positioning information of the vehicle, that is, origin of coordinates) and a local path point (pre-aiming point) closest to the origin in the vehicle coordinate system, for example, if the pre-aiming point closest to the origin in the vehicle coordinate system is (0.1, 0.2), the path tracking error of the vehicle is-0.1. After the steering wheel angle is obtained, whether the path tracking error of the vehicle is smaller than the preset threshold value is judged, if the path tracking error is smaller than the preset threshold value, the current steering wheel angle information is given to an executing mechanism of the vehicle, and the executing mechanism completes automatic driving vehicle control according to the steering wheel angle, the vehicle speed information, the braking information and other control information. If the current position and the tracking path error are larger than or equal to the preset threshold, compensating the steering wheel rotation angle until the current position and the tracking path error meet the requirement of the preset threshold, and executing the automatic driving function of the vehicle by the compensated steering wheel rotation angle and combining control information such as vehicle speed information, braking information and the like.
In this embodiment, the external environment information and the vehicle body information are obtained, analysis processing is performed according to the external environment information to obtain prediction information, and then the prediction information and the vehicle body information are combined to judge the location of the prediction information and the vehicle body information to obtain a decision signal, so that a local path can be obtained through the decision signal. And obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path, obtaining a steering wheel corner according to the pre-aiming distance and the pre-aiming point transverse error, judging whether the path tracking error is smaller than a preset threshold value after obtaining the steering wheel corner, if so, completing automatic driving vehicle control according to the current steering wheel corner, otherwise, performing feedback compensation on the steering wheel corner, and then performing automatic driving vehicle control. Therefore, after the local path is obtained, the transverse error of the pretightening distance and the pretightening point is obtained according to the local path, the steering wheel corner is obtained through the pretightening distance and the transverse error of the pretightening point, and whether the path tracking error meets the requirement is further judged after the steering wheel corner is obtained, so that the real-time requirement can be met when the path tracking is carried out, feedback compensation can be carried out on the steering wheel corner, and the path tracking precision of the vehicle in a low-speed complex scene is improved.
In some embodiments, the step of deriving the local path from the decision signal comprises the sub-steps of:
s310, when the vehicle is in the normal cruising state currently, a previous section of the current global path is intercepted to be used as a local path, and when the vehicle is in the abnormal cruising state currently, emergency danger avoidance is carried out.
Referring to fig. 2, in this embodiment, during the running process of the vehicle, the cruising state is firstly determined, if the vehicle is in a normal cruising state, the previous section of the current global path is normally intercepted as a local path, if the vehicle is detected to be in an abnormal state, operations such as braking, following, parking, getting rid of trapping and the like are performed, for example, if a pedestrian moving at a distance of several meters in front of the vehicle or the vehicle needs to decelerate or park and avoid, and if the vehicle meeting at a roadside needs to make a detour and the like, so as to improve driving safety.
In some embodiments, when the vehicle is currently in the normal cruising state, the step of intercepting the previous segment of the current global path as the local path, and when the vehicle is currently in the abnormal cruising state, the step of taking the emergency risk avoidance includes the sub-steps of:
s311, when the vehicle is in straight line running, intercepting a section of global path in front of the current position of the vehicle as a local path;
s312, when the vehicle is in a low-speed scene, intercepting a previous section of a current global path of the vehicle as a local path; the low-speed scene comprises a meeting scene and a winding obstacle scene.
In this embodiment, when it is detected that the vehicle is in a normal driving state and the vehicle is traveling in a straight line, that is, when there is no obstacle and low-speed driving is not required, then a section of global path in front of the current position of the vehicle is taken as a local path, and when the vehicle needs to meet a vehicle, bypass the obstacle and other scenes, a previous section of the current global path of the vehicle is taken as the local path, so as to improve the path tracking accuracy of the low-speed scene.
In some embodiments, the step of obtaining the lateral error of the pre-aiming distance and the pre-aiming point according to the vehicle body information and the local path includes the sub-steps of:
s410, carrying out coordinate transformation on the local path to obtain a vehicle absolute coordinate system;
s420, obtaining a vehicle coordinate system according to the positioning information and the vehicle absolute coordinate system;
and S430, carrying out weight proportion distribution according to the vehicle speed information and the curvature information of the previous section of route of the vehicle coordinate system to obtain a pre-aiming distance and a pre-aiming point transverse error.
In this embodiment, the present invention performs coordinate conversion based on the obtained local path to obtain a vehicle absolute coordinate system, and then converts the vehicle absolute coordinate system into a vehicle own coordinate system according to the parking space information of the vehicle and the vehicle absolute coordinate system, and the conversion principle is as follows:
let the current point of the vehicle be: (x, y, head), wherein head is azimuth, x is abscissa, y-ordinate; the local path points are: (X, Y), X is the abscissa and Y is the ordinate. Then, the local path point in the vehicle body coordinate system is converted to (M, N), wherein:
M=(X-x)*cos[(heading-90)/(180*pi)]+(Y-y)*sin[(heading-90)/(180*pi)] ；
wherein pi= 3.1415926;
N=(Y-y)*cos[(heading-90)/(180*pi)]-(X-x)*sin[(heading-90)/(180*pi)]。
the pretightening distance is related to the vehicle speed and the curvature of the local path, wherein the pretightening distance=the vehicle speed coefficient, the vehicle speed-the coefficient of pretightening curvature and the pretightening curvature are related, and then the transverse error of the pretightening distance and the pretightening point can be calculated by combining the vehicle speed information. It should be noted that, the weight ratio of the pretightening distance of the vehicle is set according to the running condition of the vehicle, for example, when the vehicle runs on a straight road, a larger pretightening distance is required, the vehicle speed coefficient may be set to 2, when the vehicle is on a curve, a smaller pretightening distance is required, and the coefficient of pretightening curvature to be subtracted may be set to 30.
In some embodiments, the step of obtaining the lateral error of the pretightening distance and the pretightening point according to the vehicle speed information and the local path further comprises the steps of:
s440, filtering the pre-aiming distance and the transverse error of the pre-aiming point.
In this embodiment, after the pre-aiming distance and the pre-aiming point transverse error are obtained, a filtering device with higher computing power may be used to perform first-order low-pass filtering so as to filter out the higher or lower pre-aiming point transverse error, so that the steering wheel angle adjustment cannot fluctuate too much, steering wheel shake is prevented, and steering wheel control is smoother.
Further, the step of obtaining the steering wheel angle according to the transverse error of the pretightening distance and the pretightening point comprises the following substeps:
s510, obtaining a wheel corner of the vehicle according to the pre-aiming distance and the transverse error of the pre-aiming point;
s520, obtaining a steering wheel corner according to the wheel corner of the vehicle and the vehicle transmission ratio;
s530, filtering the steering wheel angle.
In this embodiment, the wheel angle of the vehicle is calculated by the lateral error between the pretightening distance and the pretightening point, and is obtained by the wheel angle formula, as follows:
tireang=atan (2 x WheelBase (LatErr/lookahead dis), wherein,
TireAng is the wheel angle, in rad, wheelBase is the WheelBase, in m, lookahead dis is the pretightening distance, in m, latErr is the pretightening point lateral error, in m, atan represents the inverse trigonometric function, pi= 3.1415926.
After obtaining the wheel angle TireAng, the steering wheel angle SteerAng can be obtained by a steering wheel angle formula:
SteerAng = TireAng * K*180/pi。
after the steering wheel corner is obtained, the steering wheel corner is subjected to filtering treatment, so that steering wheel shake can be further prevented, and steering wheel control is smoother.
In some embodiments, the step of obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel angle when the path tracking error is smaller than a preset threshold, and performing feedback compensation on the steering wheel angle according to the path tracking error when the path tracking error is greater than or equal to the preset threshold comprises the following substeps:
s610, if the path tracking error is smaller than the preset threshold, feeding back the steering wheel angle to an executing mechanism of the vehicle to complete automatic driving vehicle control;
and S620, if the path tracking error is greater than or equal to the preset threshold, performing feedback compensation calculation according to the path tracking error, and compensating the steering wheel angle according to the obtained compensation angle.
In this embodiment, after obtaining the steering wheel angle, it is further determined whether the path tracking error meets the threshold requirement, if so, the current steering wheel angle is fed back to the actuator, and if not, feedback compensation is performed on the steering wheel angle until the steering wheel angle meets the requirement, so that the path tracking control accuracy can be improved. In one implementation, a PI (proportional integral) algorithm is used to compensate for the steering angle of the steering wheel according to the current path tracking error and the vehicle transmission ratio, and the specific calculation formula is:
combineangle= (kp_ followanror+ki_ int_laterr) K; wherein, compensation angle represents the compensation angle of feedback, kp represents the P term coefficient, ki represents the I term coefficient, followaner represents the current tracking error, int_LatError represents the error integral amount, and K represents the vehicle rotation ratio.
The embodiment also provides an autopilot vehicle control system based on pretighting control, as shown in fig. 3, which includes: the system comprises an acquisition module 100, a prediction and decision module 200, a planning module 300 and a control module 400. The acquiring module 100 is configured to acquire external environment information and vehicle body information and obtain prediction information according to the external environment information; the prediction and decision module 200 is configured to obtain a decision signal according to the prediction information and the vehicle body information; the planning module 300 is configured to obtain a local path according to the decision signal; the control module 400 is configured to obtain a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path, obtain a steering wheel corner according to the pre-aiming distance and the transverse error, and obtain a path tracking error according to the vehicle body information and the local path, complete automatic driving vehicle control according to the current steering wheel corner when the path tracking error is smaller than a preset threshold, and perform feedback compensation on the steering wheel corner according to the path tracking error when the path tracking error is greater than or equal to the preset threshold.
In this embodiment, the obtaining module 100 obtains the external environment information and the vehicle body information, and then the prediction and decision module 200 performs analysis processing according to the external environment information to obtain the prediction information, and then combines the prediction information and the vehicle body information to determine the location to obtain the decision signal to the planning module 300, so that the local path can be obtained through the decision signal. And the control module 400 obtains a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path, obtains a steering wheel corner according to the pre-aiming distance and the pre-aiming point transverse error, judges whether the path tracking error is smaller than a preset threshold after obtaining the steering wheel corner, feeds back the current steering wheel corner to the execution mechanism 500 if yes, completes automatic driving vehicle control, updates the vehicle body information to the acquisition module 100 through the execution mechanism 500, otherwise, performs feedback compensation on the steering wheel corner until the path tracking error meets the requirement, and then performs automatic driving vehicle control. Therefore, after the local path is obtained, the transverse error of the pretightening distance and the pretightening point is obtained according to the local path, the steering wheel corner is obtained through the pretightening distance and the transverse error of the pretightening point, and whether the path tracking error meets the requirement is further judged after the steering wheel corner is obtained, so that the real-time requirement can be met when the path tracking is carried out, feedback compensation can be carried out on the steering wheel corner, and the path tracking precision of the vehicle in a low-speed complex scene is improved.
In some embodiments, the planning module 300 includes: and the judging unit is used for judging whether the vehicle is in a normal cruising state currently, if so, intercepting the previous section of the current global path as a local path, and if not, carrying out emergency risk avoidance.
In some embodiments, the control module 400 includes: the device comprises a conversion unit, a first calculation unit, a first filtering unit, a second calculation unit and a second filtering unit. The conversion unit is used for carrying out coordinate conversion on the local path to obtain a vehicle absolute coordinate system, and obtaining a vehicle self coordinate system according to the positioning information and the vehicle absolute coordinate system; the first calculation unit is used for carrying out weight proportion distribution according to the vehicle speed information and the curvature information of the previous section of route of the vehicle coordinate system to obtain a pre-aiming distance and a pre-aiming point transverse error; the first filtering unit is used for filtering the pre-aiming distance and the transverse error of the pre-aiming point; the second calculation unit is used for obtaining a wheel corner of the vehicle according to the pre-aiming distance and the transverse error of the pre-aiming point, obtaining a steering wheel corner according to the wheel corner of the vehicle and the vehicle transmission ratio, obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel corner when the path tracking error is smaller than a preset threshold value, and performing feedback compensation on the steering wheel corner according to the path tracking error when the path tracking error is greater than or equal to the preset threshold value; the second filtering unit is used for carrying out filtering processing on the steering wheel angle.
The present embodiment also provides a vehicle including a memory and a processor, the memory storing a computer program, the processor implementing the steps in the following method when executing the computer program:
s100, acquiring external environment information and vehicle body information and obtaining prediction information according to the external environment information; the external environment information comprises barrier information, parking space information and lane information, and the vehicle body information comprises vehicle speed information;
s200, a decision signal is obtained according to the prediction information and the vehicle body information;
s300, obtaining a local path according to the decision signal;
s400, obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path;
s500, obtaining a steering wheel corner according to the pre-aiming distance and the transverse error of the pre-aiming point;
and S600, obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel rotation angle when the path tracking error is smaller than a preset threshold, and performing feedback compensation on the steering wheel rotation angle according to the path tracking error when the path tracking error is larger than or equal to the preset threshold.
The present embodiment also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method of:
s100, acquiring external environment information and vehicle body information and obtaining prediction information according to the external environment information; the external environment information comprises barrier information, parking space information and lane information, and the vehicle body information comprises vehicle speed information;
s200, a decision signal is obtained according to the prediction information and the vehicle body information;
s300, obtaining a local path according to the decision signal;
s400, obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path;
s500, obtaining a steering wheel corner according to the pre-aiming distance and the transverse error of the pre-aiming point;
and S600, obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel rotation angle when the path tracking error is smaller than a preset threshold, and performing feedback compensation on the steering wheel rotation angle according to the path tracking error when the path tracking error is larger than or equal to the preset threshold.
The memory may in some embodiments be an internal storage unit of the vehicle, such as a memory of the vehicle. The memory may in other embodiments also be an external storage device of the vehicle, such as a plug-in type usb disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the vehicle. Further, the memory may also include both an internal storage unit and an external storage device of the vehicle. The memory is used for storing application software installed on the vehicle and various data, such as program codes for installing the vehicle and the like. The memory may also be used to temporarily store data that has been output or is to be output. The processor may in some embodiments be a central processing unit (Central Processing Unit, CPU), microprocessor or other data processing chip for executing program code or processing data stored in the memory. The computer readable storage medium may be a memory, a magnetic disk, an optical disk, or the like.
According to the invention, after the local path is obtained, the transverse error of the pretightening distance and the pretightening point is obtained according to the local path, the steering wheel corner is obtained through the pretightening distance and the transverse error of the pretightening point, and whether the path tracking error meets the requirement is further judged after the steering wheel corner is obtained, so that the real-time requirement can be met when the path tracking is carried out, the feedback compensation can be carried out on the steering wheel corner, and the path tracking precision of the vehicle in a low-speed complex scene is improved. In addition, the invention carries out filtering treatment on the pre-aiming distance and the transverse error of the pre-aiming point, so that the steering wheel angle can not be adjusted to be too large in fluctuation, further steering wheel shake can be prevented, and the steering wheel angle can be further prevented from being filtered, and steering wheel control is smoother.
The above embodiments are merely preferred embodiments for fully explaining the present invention, and the scope of the present invention is not limited thereto. Equivalent substitutions and modifications will occur to those skilled in the art based on the present invention, and are intended to be within the scope of the present invention.

Claims (10)

1. An automatic driving vehicle control method based on pre-aiming control, which is characterized by comprising the following steps:
acquiring external environment information and vehicle body information, and acquiring prediction information according to the external environment information; the external environment information comprises obstacle information, parking space information and lane information, and the vehicle body information comprises vehicle speed information and positioning information;
obtaining a decision signal according to the prediction information and the vehicle body information;
obtaining a local path according to the decision signal;
obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path;
obtaining a steering wheel corner according to the pre-aiming distance and the transverse error of the pre-aiming point;
and obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel rotation angle when the path tracking error is smaller than a preset threshold, and performing feedback compensation on the steering wheel rotation angle according to the path tracking error when the path tracking error is larger than or equal to the preset threshold.
2. The method for controlling an automatically driven vehicle based on pre-sighting control of claim 1, wherein the step of obtaining the local path according to the decision signal includes:
when the vehicle is in the normal cruising state, the previous section of the current global path is intercepted to be used as a local path, and when the vehicle is in the abnormal cruising state, emergency danger avoiding is carried out.
3. The method for controlling an automatically driven vehicle based on pre-aiming control according to claim 2, wherein the step of intercepting a previous segment of the current global path as a local path when the vehicle is currently in a normal cruising state, and performing emergency avoidance when the vehicle is currently in an abnormal cruising state comprises:
when the vehicle is in straight line running, intercepting a section of global path in front of the current position of the vehicle as a local path;
when the vehicle is in a low-speed scene, intercepting a previous section of a current global path of the vehicle as a local path; the low-speed scene comprises a meeting scene and a winding obstacle scene.
4. The method for controlling an automatically driven vehicle based on pre-aiming control according to claim 3, wherein the step of obtaining a pre-aiming distance and a pre-aiming point lateral error from the vehicle body information and the local path comprises:
performing coordinate transformation on the local path to obtain a vehicle absolute coordinate system;
obtaining a vehicle coordinate system according to the positioning information and the vehicle absolute coordinate system;
and according to the vehicle speed information and the curvature information of the previous section of route of the vehicle coordinate system, carrying out weight proportion distribution to obtain a pre-aiming distance and a pre-aiming point transverse error.
5. The method for controlling an automatically driven vehicle based on pre-aiming control according to claim 4, wherein the step of obtaining a pre-aiming distance and a pre-aiming point lateral error from the vehicle speed information and the local path further comprises:
and filtering the transverse errors of the pre-aiming distance and the pre-aiming point.
6. The method for controlling an automatically driven vehicle based on pre-aiming control according to claim 2, wherein the step of obtaining a steering wheel angle according to the lateral error between the pre-aiming distance and the pre-aiming point comprises:
obtaining a wheel corner of the vehicle according to the transverse error of the pre-aiming distance and the pre-aiming point;
obtaining a steering wheel corner according to the wheel corner of the vehicle and the vehicle transmission ratio;
and carrying out filtering treatment on the steering wheel angle.
7. The method for controlling an automatically driven vehicle based on pre-aiming control according to claim 4, wherein the step of obtaining a path tracking error according to the vehicle body information and the local path, completing the automatically driven vehicle control according to the current steering wheel angle when the path tracking error is smaller than a preset threshold value, and performing feedback compensation on the steering wheel angle according to the path tracking error when the path tracking error is greater than or equal to the preset threshold value comprises:
if the path tracking error is smaller than the preset threshold value, feeding back the steering wheel angle to an executing mechanism of the vehicle to complete automatic driving vehicle control;
and if the path tracking error is greater than or equal to the preset threshold value, carrying out feedback compensation calculation according to the path tracking error, and compensating the steering wheel angle according to the obtained compensation angle.
8. An autonomous vehicle control system based on pre-sighting control, comprising:
the acquisition module is used for acquiring external environment information and vehicle body information and obtaining prediction information according to the external environment information;
the prediction and decision module is used for obtaining a decision signal according to the prediction information and the vehicle body information;
the planning module is used for obtaining a local path according to the decision signal;
the control module is used for obtaining a pre-aiming distance and a pre-aiming point transverse error according to the vehicle body information and the local path, obtaining a steering wheel corner according to the pre-aiming distance and the transverse error, obtaining a path tracking error according to the vehicle body information and the local path, completing automatic driving vehicle control according to the current steering wheel corner when the path tracking error is smaller than a preset threshold value, and performing feedback compensation on the steering wheel corner according to the path tracking error when the path tracking error is greater than or equal to the preset threshold value.
9. A vehicle comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method for controlling an autonomous vehicle based on pre-sighting control as claimed in any one of claims 1-7.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the pre-aiming control based autonomous vehicle control method as claimed in any of claims 1-7.
CN202310766270.2A 2023-06-27 2023-06-27 Automatic driving vehicle control method and system based on pre-aiming control and vehicle Pending CN116700097A (en)

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