CN110789530B - Four-wheel independent steering-independent driving vehicle trajectory tracking method and system - Google Patents
Four-wheel independent steering-independent driving vehicle trajectory tracking method and system Download PDFInfo
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Abstract
The invention provides a method and a system for tracking a track of a four-wheel independent steering-independent driving vehicle. The method comprises the following steps: selecting a point which simultaneously meets a forward detection distance constraint and a radial distance constraint on a target track as a forward detection point, wherein the radial distance constraint is a product between a radial distance coefficient and a transverse error, and the transverse error is a shortest distance between the target track and a vehicle body datum point; fitting an arc track passing through the forward probe point and the vehicle body datum point according to the current position relation between the forward probe point and the vehicle body, and calculating the radius of the arc track; calculating the angular speed of the vehicle body reference point according to the set vehicle speed and the radius of the circular arc track; and obtaining the rotating speed control quantity and the rotating angle control quantity of the wheels according to the angular speed and the linear speed at the vehicle body reference point so as to control the vehicle to travel along the target track. The method and the system improve the track tracking precision, the error convergence speed and the smoothness of the vehicle body in the tracking process.
Description
Technical Field
The invention relates to the technical field of vehicle automatic control, in particular to a method and a system for tracking a track of a four-wheel independent steering-independent driving vehicle.
Background
The vehicle track tracking means that a target track is given, a vehicle is controlled to quickly converge on the target track and move along the target track. Current trajectory tracking algorithms can be broadly divided into three categories: a model-based control algorithm, a feedback error-based control algorithm, and a geometry-based control algorithm. The control algorithm based on the model needs to establish an accurate vehicle kinematic model and a dynamic model, and considers the influence of the cornering power and the slip ratio of the tire on the track tracking performance. The control algorithm based on the feedback error does not need to establish a system model, a controlled system is regarded as a black box, and the controlled quantity is adjusted according to the feedback error, so that the system error tends to be zero. And calculating the corner control quantity according to the geometric relation between the vehicle body pose and the target track by a control algorithm based on the geometric relation, and controlling the vehicle to move along the target track. Generally, the difficulty of establishing accurate vehicle kinematics and dynamics models is high, and the vehicle models are all nonlinear, which leads to complex calculation of a model-based control algorithm and difficult application in an actual scene. The control algorithm based on the feedback error corrects the control quantity according to the feedback error, and the output control quantity of the system has delay, so that the real-time requirement of the track tracking is difficult to meet. The control algorithm based on the geometric relation calculates the corner control quantity according to the geometric relation between the vehicle body pose and the target track, is simple and easy to calculate, and is generally used for solving the problem of tracking the vehicle track.
Typical geometric relationship tracking algorithms include Pure Pursuit (Pure Pursuit) method, Vector Pursuit (Vector Pursuit) method, and Stanley method. And selecting a forward detection point on the target track according to the forward detection distance constraint by the pure tracking method. The forward detection distance constraint refers to the Euclidean distance between a vehicle body datum point and a forward detection point. And fitting an arc track which can be executed by the vehicle based on the position relation between the front probe point and the vehicle body reference point, and calculating the rotating speed and the corner control quantity of the vehicle according to the curvature information of the fitted arc to control the vehicle to move along the target track. The performance of the pure tracking method mainly depends on the selection of the forward detection point, and when the forward detection distance is too small, the vehicle body can vibrate inside and outside near the target track. When the forward-exploring distance is too large, the vehicle body cannot be well attached to the target track at the bend, so that the track tracking precision is reduced.
In a practical application scenario, the initial position of the vehicle is not necessarily on the target track, and an initial lateral error exists between the vehicle and the target track. The existing pure tracking method only considers the forward detection distance constraint when selecting the forward detection point on the target track. When the transverse error is large, a large yaw angular velocity can occur on the vehicle body, so that the vehicle body swings inside and outside near a target track, the error convergence time is long, and the track tracking error in the initial stage is large. In addition, the traditional pure tracking method usually adopts fixed forward-exploring distance constraint, and cannot automatically adapt to the curvature change of a target track, so that the phenomenon of 'curve trimming' can occur at a curve.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a four-wheel independent steering-independent driving vehicle track tracking method and system.
According to a first aspect of the present invention, a four-wheel independent steering-independent drive vehicle trajectory tracking method is provided. The method comprises the following steps:
selecting a point which simultaneously meets a forward detection distance constraint and a radial distance constraint on a target track as a forward detection point, wherein the radial distance constraint is a product between a radial distance coefficient and a transverse error, and the transverse error is a shortest distance between the target track and a vehicle body datum point;
fitting an arc track passing through the forward probe point and the vehicle body datum point according to the current position relation between the forward probe point and the vehicle body, and calculating the radius of the arc track;
calculating the angular speed of the vehicle body reference point according to the set vehicle speed and the radius of the circular arc track;
and obtaining the rotating speed control quantity and the rotating angle control quantity of the wheels according to the angular speed and the linear speed at the vehicle body reference point so as to control the vehicle to travel along the target track.
In some embodiments, the forward range constraint is dynamically adjusted to curvature information of the target trajectory.
In some embodiments, the forward range constraint is set according to the following steps:
selecting a vehicle body nearest path point with the shortest distance to a vehicle body reference point on the target track, and selecting a plurality of path points in front of the vehicle body nearest path point;
calculating curvature information of the nearest path point of the vehicle body and curvature information of the plurality of path points;
and dynamically adjusting the forward-exploring distance constraint according to the curvature information of the path points and the curvature information of the nearest path point of the vehicle body.
In some embodiments, the plurality of waypoints includes a waypoint 1.5m forward of the body closest waypoint and a waypoint 3m forward of the body closest waypoint.
In some embodiments, dynamically adjusting the lookahead distance constraint based on the curvature information for the plurality of waypoints and the curvature information for the closest waypoint of the body comprises:
constructing an incidence relation among curvature information of the path points, curvature information of the nearest path point of the vehicle body and the forward exploring distance constraint by using a fuzzy controller;
and outputting the forward detection distance constraint by utilizing the incidence relation in a reverse fuzzy mode to serve as a basis for selecting the forward detection point.
In some embodiments, the radial distance coefficient is preset to 0.6 or 0.9 or 1.2.
According to a second aspect of the present invention, a four-wheel independent steering-independent drive vehicle trajectory tracking system is provided. The system comprises:
the front probe selection module: the method comprises the steps of selecting a point on a target track, wherein the point simultaneously satisfies a forward distance constraint and a radial distance constraint as a forward probe point, and the radial distance constraint is a product between a radial distance coefficient and a transverse error;
the circular arc track calculation module: the system comprises a front probe point, a vehicle body datum point, a rear probe point, a front probe point, a rear probe point and a rear probe point, wherein the front probe point is used for detecting the front probe point;
an angular velocity calculation module: the device is used for calculating the angular speed of the vehicle body reference point according to the set vehicle speed and the radius of the circular arc track;
a steering control module: and the control unit is used for obtaining the rotating speed control quantity and the rotating angle control quantity of the wheel according to the angular speed and the linear speed at the vehicle body reference point so as to control the vehicle to travel along the target track.
In some embodiments, the forward probe point selection module is further configured to perform:
selecting a vehicle body nearest path point with the shortest distance to a vehicle body reference point on the target track, and selecting a plurality of path points in front of the vehicle body nearest path point;
calculating curvature information of the nearest path point of the vehicle body and curvature information of the plurality of path points;
and dynamically adjusting the forward-exploring distance constraint according to the curvature information of the path points and the curvature information of the nearest path point of the vehicle body.
Compared with the prior art, the invention has the advantages that: aiming at the problems of vehicle body yaw and 'curve trimming' in the track tracking process of the existing pure tracking method, the invention introduces radial distance constraint when selecting a front probe point, and effectively solves the problem of vehicle body yaw in the error convergence process of the vehicle body; aiming at the problem of curve trimming, the invention builds a forward detection distance self-adaptive fuzzy controller, dynamically adjusts the forward detection distance in a self-adaptive manner according to the curvature information of the target track, and ensures the tracking precision of the algorithm on the variable curvature track.
Drawings
The invention is illustrated and described only by way of example and not by way of limitation in the scope of the invention as set forth in the following drawings, in which:
FIG. 1 is a flow chart of a four-wheel independent steering-independent drive vehicle trajectory tracking method according to one embodiment of the present invention;
FIG. 2 is an overall architecture diagram of a vehicle trajectory tracking method implementing an embodiment of the present invention;
FIG. 3 is a schematic diagram of a four-wheel independent steering-independent drive vehicle kinematics model according to one embodiment of the present invention;
FIG. 4 is a schematic vehicle body yaw;
FIG. 5 is a schematic diagram of a vehicle trajectory tracking method according to one embodiment of the present invention;
FIG. 6 is a diagram of a waypoint curvature information membership function according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions, design methods, and advantages of the present invention more apparent, the present invention will be further described in detail by specific embodiments with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not as a limitation. Thus, other examples of the exemplary embodiments may have different values.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
The vehicle track tracking method provided by the invention is a self-adaptive pure tracking method under the constraint of radial distance, can realize track tracking of four-wheel independent steering-independent driving unmanned ground vehicles, and considers the constraint of forward detection distance and the constraint of radial distance when selecting forward detection points. In this context, a radial distance constraint is defined as the distance between the closest waypoint to the body on the target trajectory and the forward probe point. The radial distance constraint is introduced to solve the problem of internal and external swing of the car body when the transverse error is large. In addition, aiming at the problem of 'curve trimming', the invention builds a forward detection distance self-adaptive fuzzy controller, and dynamically adjusts the forward detection distance in a self-adaptive manner according to the curvature information of the target track, thereby ensuring the tracking precision at the curve.
Referring to fig. 1, a vehicle trajectory tracking method according to an embodiment of the present invention includes: step S110, selecting a point which simultaneously meets a forward detection distance constraint and a radial distance constraint on a target track as a forward detection point; step S120, fitting an arc track passing through the front probe point and the vehicle body datum point according to the current position relation between the front probe point and the vehicle body, and calculating the radius of the arc track; step S130, calculating the angular speed of the vehicle body reference point according to the set vehicle speed and the radius of the circular arc track; and step S140, obtaining the rotating speed control quantity and the rotating angle control quantity of the wheel according to the angular speed and the linear speed at the vehicle body reference point so as to control the vehicle to travel along the target track. This is described in detail below with reference to fig. 2 to 6.
Fig. 2 is an overall architecture of the technical solution of the present invention, in which a laser radar is used to acquire environmental information, a SLAM module outputs pose information of a vehicle based on point cloud data, and a target track outputs curvature information. The track tracking method calculates the curvature of a fitting track in the current control period based on the pose information and the curvature information, and the motion decomposition module calculates the wheel rotating speed and the corner control quantity according to the output curvature information to control the whole vehicle to advance to the target track. For example, the laser radar provides real-time pose information of the vehicle, the target track is discrete path points, and cubic spline curve interpolation is performed on the path points, so that curvature information of the target track can be approximated. And calculating the vehicle track in the current control according to the geometric relation between the vehicle body pose and the target track, performing motion decomposition based on the established vehicle kinematics model, and calculating the rotating speed and the turning angle control quantity of the wheels. In practical application, the control quantity CAN be transmitted to the vehicle control unit through the CAN line, and the vehicle control unit controls the vehicle to move along the target track.
In the embodiment of the invention, based on the ackermann steering principle, a kinematic model of a four-wheel independent steering-independent drive vehicle shown in fig. 3 is built. The instantaneous steering of the vehicle is preset on the extension of the central axis of the vehicle. In addition, by selecting the geometric center of the chassis of the vehicle body as a reference point, the relationship between the rotating speed and the rotating angle of the wheel and the speed and the angular speed at the reference point can be deduced:
in the formulae (1) to (5) < alpha >, < alpha >iIs the steering angle of the ith wheel, omega is the angular velocity at the reference point of the vehicle body, viThe rotation speed of the ith wheel, L is the vehicle wheel base, and B is the vehicle wheel base. The pure tracking method can calculate a passing forward probe point and a vehicle body baseThe trajectory of the alignment points, R is the radius of the fitted trajectory, V is the velocity at the body reference point, which is the geometric center of the body.
The existing pure tracking method selects the forward detection point and only considers the forward detection distance constraint. The specific algorithm flow comprises the following steps: calculating whether the distance between the path point and the vehicle body reference point is greater than the forward detection distance constraint or not from the path point closest to the vehicle body until the path point with the straight-line distance greater than the forward detection distance from the vehicle body reference point is found, and setting the path point as the forward detection point; fitting an arc track passing through the forward probe point and the vehicle body datum point according to the current position relation between the forward probe point and the vehicle body, and calculating the radius of the arc track; setting the motion speed of the vehicle in advance, and calculating the angular speed according to the vehicle speed and the radius of the circular arc track; based on the established kinematic model, the angular speed and the linear speed at the reference point of the vehicle body can be decomposed into the rotating speed and the rotating angle control quantity of the wheels.
When the lateral error is large, the vehicle body can have large yaw in the existing pure tracking method, so that the vehicle body can swing inside and outside near a target track, as shown in fig. 4. The reason for the large-amplitude yaw of the vehicle body is that the radial distance of the front probe point is insufficient, the vehicle must converge on the target track within the limited radial distance, and therefore the existing pure tracking algorithm can control the vehicle body to travel to the target track at a large yaw velocity. The larger yaw rate can help the lateral error to converge quickly, but due to the large yaw rate, the lateral error will grow reversely after converging to near zero, resulting in the vehicle body swinging in and out near the target trajectory.
The embodiment of the invention introduces the radial distance constraint L on the basis of the pure tracking methodrThe radial distance constraint is set to a radial distance coefficient KrThe product with the lateral error d (i.e. L)r＝KrD). The radial distance constraint is embodied in the selection of the forward probe point, and the traditional pure tracking method only has forward probe distance constraint when the forward probe point is selected. According to the embodiment of the invention, the radial distance constraint is introduced into the selection of the forward probe point, and the forward probe point needs to simultaneously meet the forward probe distance constraint and the radial distance constraint.
In one embodiment, the radial distance coefficient may be set empirically, for example, to 0.6, 0.9, 1.2, etc., and after setting the radial distance coefficient, the radial distance constraint may be calculated to select the forward probe point.
As shown in fig. 5, the radial distance is defined herein as the distance between the closest waypoint, which is the closest point on the target trajectory to the vehicle body reference point, and the forward probe point, and the lateral error is the distance between the vehicle body reference point and the closest waypoint. When a forward probe point is selected on a target track, the candidate path point can be the forward probe point only if the forward probe distance constraint and the radial distance constraint are met at the same time.
In one embodiment, the foreshortening distance constraint is set to be a fixed value, however, considering that the fixed foreshortening distance cannot meet the requirement of the variable-curvature track on the foreshortening distance, preferably, at a curve with a larger curvature, a relatively small foreshortening distance is set to ensure the track tracking accuracy, at a straight line section with a smaller curvature, a relatively larger foreshortening distance is set, and the foreshortening distance constraint is dynamically set by adapting to curvature information, so that the smoothness of the movement of the vehicle body is improved.
Further, the method is used for obtaining the corresponding relation between the curvature information of the target track and the forward detection distance and realizing the forward detection distance constraint self-adaptive dynamic adjustment. The embodiment of the invention builds the fuzzy controller, the input quantity of the fuzzy controller is the curvature information of the nearest path point of the vehicle body, the path point at 1.5m in front of the vehicle body (namely the front of the nearest path point of the vehicle body on the target track) and the path point at 3m in front of the vehicle body, and the output quantity is the real-time forward-exploring distance constraint. The input section of curvature information is [0m ]-1，0.4m-1]The fuzzy domain is three intervals, namely small, middle and large, and the membership function is shown in fig. 6. The range of the advancing distance output by the fuzzy controller is 0.6m and 1.5m]The association between the input and output of the fuzzy controller (or inference rule) can be obtained from real vehicle test. For example, the set fuzzy controller inference rules are as shown in table 1 below:
table 1: fuzzy controller inference rules
| Inference rule sequence number | Nearest path point curvature | Curvature at 1.5m ahead | Front 3m curvature | Distance of forward probe |
| 1 | Small | Small | Small | Big (a) |
| 2 | Small | Small | In | In |
| 3 | Small | Small | Big (a) | In |
| 4 | Small | In | / | In |
| 5 | Big (a) | / | / | |
| 6 | In | Small | / | In |
| 7 | In | In | / | In |
| 8 | In | Big (a) | / | Small |
Based on the above table 1, the forward distance constraint can be obtained by an anti-fuzzy method, the forward distance constraint adopts a weighted average calculation method, and the probability of curvature membership and fuzzy quantity of the current path point, the position 1.5m ahead and the position 3m ahead can be known according to the membership function. The forward detection distance ambiguity quantity is small, and the real values corresponding to the medium and large are 0.6m, 1.2m and 1.5 m. For example, the formula for calculating the forward range anti-blur is:
wherein u isAiThe i-th inference rule membership u of the curvature at the nearest path pointBiMembership degree u of ith inference rule of curvature of 1.5mCiThe i-th inference rule membership degree of the curvature at 3m is shown. ZiAnd advancing the distance value for the ith inference rule.
For example, the current waypoint curvature is 0.12m-1The curvature at the front 1.5m is 0.28m-1The curvature at the front 3m position was 0.35m-1. The membership function can calculate the small of the track curvature at the nearest path point, and the membership of the large fuzzy quantity is 0.8, 0.4 and 0. The curvature of the track at the front 1.5m is small, and the membership degree of the large fuzzy quantity is 0, 0.6 and 0.8. The curvature of the track at 3m ahead is small, the membership degree of the large fuzzy quantity is 0, 0, 1, then:
La＝(0.8×0.6×1.2+0.4×0.6×1.2+0.4×0.8×0.6)/(0.8×0.6+0.4×0.6+0.4×0.8)＝1.015m。
the other terms not listed in the above La calculation are because there is a fuzzy amount with a degree of membership of 0.
In conclusion, the forward detection distance constraint of the embodiment of the invention ensures the accuracy of track tracking, the radial distance constraint ensures the smoothness of the movement of the vehicle body, and the forward detection distance constraint is dynamically and adaptively adjusted according to curvature information to ensure the precision of track tracking.
Accordingly, the present invention also provides a four-wheel independent steering-independent drive vehicle trajectory tracking system for implementing one or more aspects of the above method. For example, the system includes: the forward probe point selection module is used for selecting a point which simultaneously meets forward probe distance constraint and radial distance constraint on the target track as a forward probe point; the arc track calculation module is used for fitting an arc track passing through the front probe point and the vehicle body datum point according to the current position relation between the front probe point and the vehicle body and calculating the radius of the arc track; the angular velocity calculation module is used for calculating the angular velocity at the vehicle body reference point according to the set vehicle speed and the arc track radius; and the steering control module is used for obtaining the rotating speed control quantity and the rotating angle control quantity of the wheels according to the angular speed and the linear speed at the vehicle body reference point so as to control the vehicle to travel along the target track.
In order to verify the feasibility of the technical scheme, the practical vehicle test is carried out in an experimental field. Two sets of experiments for tracking a linear target track and a curved target track are set. The performance difference between the existing pure tracking method and the method provided by the invention is compared. In a tracking experiment of a linear target track, an initial transverse error is set to be 1.5m, a vehicle speed is set to be 0.6m/s, wherein the average transverse error of the existing pure tracking method is 0.23m, the time of a vehicle body converging to the target track is 15.3s, and the maximum wheel steering angle in the track tracking process is 56.9 degrees, while the average transverse error of the technical scheme provided by the invention is 0.209m, the time of the vehicle body converging to the target track is 7.5s, and the maximum vehicle steering angle is 30.2 degrees. In a curve target track tracking experiment, an initial transverse error is set to be 1m, the vehicle speed is 0.6m/s, the average transverse error of a traditional pure tracking method is 0.121m, and the average transverse error of the technical scheme provided by the invention is 0.085 m. The experimental result shows that the track tracking precision, the error convergence speed and the smoothness of the vehicle body in the tracking process are all higher than those of the existing pure tracking method.
It should be noted that, although the steps are described in a specific order, the steps are not necessarily performed in the specific order, and in fact, some of the steps may be performed concurrently or even in a changed order as long as the required functions are achieved.
The present invention may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for causing a processor to implement various aspects of the present invention.
The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may include, for example, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (7)
1. A four-wheel independent steering-independent driving vehicle track tracking method comprises the following steps:
selecting a point which simultaneously meets a forward detection distance constraint and a radial distance constraint on a target track as a forward detection point, wherein the radial distance constraint is a product between a radial distance coefficient and a transverse error, and the transverse error is a shortest distance between the target track and a vehicle body datum point;
fitting an arc track passing through the forward probe point and the vehicle body datum point according to the current position relation between the forward probe point and the vehicle body, and calculating the radius of the arc track;
calculating the angular speed of the vehicle body reference point according to the set vehicle speed and the radius of the circular arc track;
obtaining a rotating speed control quantity and a rotating angle control quantity of wheels according to the angular speed and the linear speed at the vehicle body reference point so as to control the vehicle to travel along the target track;
wherein the forward sounding distance constraint is set according to the following steps:
selecting a vehicle body nearest path point with the shortest distance to a vehicle body reference point on the target track, and selecting a plurality of path points in front of the vehicle body nearest path point;
calculating curvature information of the nearest path point of the vehicle body and curvature information of the plurality of path points;
dynamically adjusting the foreshortening distance constraint according to the curvature information of the path points and the curvature information of the nearest path point of the vehicle body, comprising: constructing an incidence relation among curvature information of the path points, curvature information of the nearest path point of the vehicle body and the forward exploring distance constraint by using a fuzzy controller; and outputting the forward detection distance constraint by utilizing the incidence relation in a reverse fuzzy mode to serve as a basis for selecting the forward detection point.
2. A four-wheel independent steering-independent drive vehicle trajectory tracking method according to claim 1, wherein the forward exploring distance constraint is dynamically adjusted to curvature information of the target trajectory.
3. The four-wheel independent steering-independent drive vehicle trajectory tracking method according to claim 1, wherein the plurality of waypoints includes a waypoint 1.5m ahead of the nearest waypoint of the vehicle body and a waypoint 3m ahead of the nearest waypoint of the vehicle body.
4. A four-wheel independent steering-independent drive vehicle trajectory tracking method according to claim 1, wherein the radial distance coefficient is preset to 0.6 or 0.9 or 1.2.
5. A four-wheel independent steering-independent drive vehicle trajectory tracking system, comprising:
the front probe selection module: the method comprises the steps of selecting a point on a target track, wherein the point simultaneously satisfies a forward distance constraint and a radial distance constraint as a forward probe point, and the radial distance constraint is a product between a radial distance coefficient and a transverse error;
the circular arc track calculation module: the system comprises a front probe point, a vehicle body datum point, a rear probe point, a front probe point, a rear probe point and a rear probe point, wherein the front probe point is used for detecting the front probe point;
an angular velocity calculation module: the device is used for calculating the angular speed of the vehicle body reference point according to the set vehicle speed and the radius of the circular arc track;
a steering control module: the control device is used for obtaining the rotating speed control quantity and the rotating angle control quantity of the wheels according to the angular speed and the linear speed at the vehicle body reference point so as to control the vehicle to travel along the target track;
wherein the forward probe point selection module is further configured to perform:
selecting a vehicle body nearest path point with the shortest distance to a vehicle body reference point on the target track, and selecting a plurality of path points in front of the vehicle body nearest path point;
calculating curvature information of the nearest path point of the vehicle body and curvature information of the plurality of path points;
dynamically adjusting the foreshortening distance constraint according to the curvature information of the path points and the curvature information of the nearest path point of the vehicle body, comprising: constructing an incidence relation among curvature information of the path points, curvature information of the nearest path point of the vehicle body and the forward exploring distance constraint by using a fuzzy controller; and outputting the forward detection distance constraint by utilizing the incidence relation in a reverse fuzzy mode to serve as a basis for selecting the forward detection point.
6. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
7. A computer device comprising a memory and a processor, on which memory a computer program is stored which is executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 4 when executing the program.
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| CN113548038B (en) * | 2020-04-22 | 2024-03-01 | 广州汽车集团股份有限公司 | Parking curvature control method and system, control equipment and storage medium |
| CN112230651A (en) * | 2020-07-06 | 2021-01-15 | 湖南工业大学 | Distributed unmanned vehicle path tracking control method based on hierarchical control theory |
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