CN113934200B - A path tracking control method and device for an unmanned vehicle - Google Patents
A path tracking control method and device for an unmanned vehicle Download PDFInfo
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- CN113934200B CN113934200B CN202010597370.3A CN202010597370A CN113934200B CN 113934200 B CN113934200 B CN 113934200B CN 202010597370 A CN202010597370 A CN 202010597370A CN 113934200 B CN113934200 B CN 113934200B
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Abstract
The invention provides a path tracking control method and a path tracking control device for an unmanned vehicle, which can respectively calculate steering wheel angles under different dimensions based on path information of a target path, attitude information of the vehicle and prediction information of the target path after the target path of the vehicle is acquired, and control the steering wheel angles of the vehicle based on the steering wheel angles to finish transverse control of the vehicle. Based on the method and the system, the full working condition and multiple scenes of the unmanned task can be dealt with, and the stability and the accuracy of path tracking are improved in the driving process of the unmanned vehicle, so that the safety performance of the unmanned vehicle is ensured.
Description
Technical Field
The invention relates to the technical field of whole vehicle control of unmanned vehicles, in particular to a path tracking control method and device of an unmanned vehicle.
Background
The unmanned technology is used as a hot spot direction of the current automobile technology development, and has profound effects on the development of the automobile industry and even national folks. The unmanned technology may revolutionize the travel mode of human beings and the production mode of industrial production in the future, but the unmanned technology is still in a rapid development period at present, and a plurality of technical problems still remain to be solved.
The prior unmanned system basically comprises a perception fusion layer, a planning decision layer, a vehicle control layer and a transverse and longitudinal related actuator layer which are formed by various sensors, wherein the vehicle control layer is connected with upper-layer instructions and actuators, and plays an important role in performance expression of an unmanned vehicle. In the vehicle control layer, the path tracking control technology directly influences the performance of the vehicle for tracking the target path when the vehicle is not driven, and the path tracking control technology tracks the target path through a certain control method, so that the path tracking control technology is a key technology for realizing stable running of the vehicle.
At present, due to the fact that certain stability problems exist in technologies such as environment sensing and planning decision making, certain stability problems exist in path information received by a vehicle control layer, and meanwhile, interaction delay exists in the interaction process with an actuator layer. Therefore, a stable path tracking control method is developed, the unmanned vehicle can stably track a target path in a complex road traffic environment, and the method is very important for the driving performance and safety of the unmanned vehicle.
Disclosure of Invention
In view of the above, the present invention provides a method and apparatus for controlling path tracking of an unmanned vehicle, which comprises the following steps:
a path-following control method of an unmanned vehicle, the method comprising:
Acquiring a target path of a vehicle;
calculating a first steering wheel angle of the vehicle based on path information of the target path, and calculating a second steering wheel angle of the vehicle based on attitude information of the vehicle, and calculating a third steering wheel angle of the vehicle based on predicted information of the target path;
And controlling the steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle and the third steering wheel angle so as to transversely control the vehicle.
Preferably, the calculating the first steering wheel angle of the vehicle based on the path information of the target path includes:
Selecting a first target point on the target path by utilizing the speed of the vehicle, and acquiring a first curve curvature of the first target point;
converting the curvature of the first curve into a wheel end corner of the vehicle through trigonometric function change;
And taking the steering wheel corner mapped by the vehicle wheel end corner as the first steering wheel corner according to a preset mapping relation.
Preferably, the method further comprises:
And correcting the direction characteristic of the curvature of the first curve.
Preferably, the calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle includes:
taking a point closest to the origin of the vehicle coordinate system on the target path as a second target point;
determining a lateral offset and a first lateral angle of the vehicle at the second target point;
acquiring a second curve curvature of the second target point, and calculating a first lateral acceleration of the vehicle by using the second curve curvature and the speed of the vehicle;
determining a first proportional control coefficient corresponding to the first lateral acceleration in a transverse offset dimension and a second proportional control coefficient corresponding to the first lateral acceleration in a transverse angle dimension;
Calculating a steering wheel angle in the lateral offset dimension from the first proportional control coefficient and the lateral offset, and calculating a steering wheel angle in the lateral angle dimension from the second proportional control coefficient and the first lateral angle;
And taking the superposition of the steering wheel angle in the transverse offset dimension and the steering wheel angle in the transverse angle dimension as the second steering wheel angle.
Preferably, the method further comprises:
under the condition that the running state of the vehicle meets a preset dynamic integral compensation condition, determining a compensated integral step length according to the first lateral acceleration;
compensating steering wheel rotation angles under the transverse offset dimension according to the integral step length;
Correspondingly, the step of summing the sum of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle includes:
and taking the superposition sum of the steering wheel angle compensated in the transverse offset dimension and the steering wheel angle in the transverse angle dimension as the second steering wheel angle.
Preferably, the calculating the third steering wheel angle of the vehicle based on the predicted information of the target path includes:
taking a point closest to the origin of the vehicle coordinate system on the target path as a third target point, and selecting a predicted point on the target path;
calculating the time interval from the third target point to the predicted point according to the speed of the vehicle;
respectively determining a second transverse angle of the vehicle at the third target point and a third transverse angle of the predicted point, and calculating the predicted yaw rate of the vehicle according to the second transverse angle, the third transverse angle and the time interval;
Acquiring a third curve curvature of the third target point, and calculating a second lateral acceleration of the vehicle by using the third curve curvature and the vehicle speed;
determining a third proportional control coefficient corresponding to the second lateral acceleration in the yaw rate dimension;
And acquiring the actual yaw rate of the vehicle, and calculating the third steering wheel angle according to the actual yaw rate, the third proportional control coefficient and the predicted yaw rate.
A path tracking control device for an unmanned vehicle, the device comprising:
The path acquisition module is used for acquiring a target path of the vehicle;
a steering wheel angle calculation module for calculating a first steering wheel angle of the vehicle based on path information of the target path, and calculating a second steering wheel angle of the vehicle based on attitude information of the vehicle, and calculating a third steering wheel angle of the vehicle based on predicted information of the target path;
And the transverse control module is used for controlling the steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle and the third steering wheel angle so as to transversely control the vehicle.
Preferably, the steering wheel angle calculation module for calculating a first steering wheel angle of the vehicle based on the path information of the target path is specifically configured to:
The method comprises the steps of selecting a first target point on a target path by utilizing the speed of a vehicle, obtaining first curve curvature of the first target point, converting the first curve curvature into a vehicle wheel end turning angle through trigonometric function change, and taking the steering wheel turning angle mapped by the vehicle wheel end turning angle as the first steering wheel turning angle according to a preset mapping relation.
Preferably, the steering wheel angle calculation module for calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle is specifically configured to:
The method comprises the steps of taking a point closest to an origin of a vehicle coordinate system on a target path as a second target point, determining lateral offset and a first lateral angle of the vehicle at the second target point, obtaining second curve curvature of the second target point, calculating first lateral acceleration of the vehicle by means of the second curve curvature and speed of the vehicle, determining a first proportional control coefficient corresponding to the first lateral acceleration in a lateral offset dimension and a second proportional control coefficient corresponding to the first lateral acceleration in a lateral angle dimension, calculating steering wheel rotation angle in the lateral offset dimension according to the first proportional control coefficient and the lateral offset, calculating steering wheel rotation angle in the lateral angle dimension according to the second proportional control coefficient and the first lateral angle, and taking superposition sum of steering wheel rotation angle in the lateral offset dimension and steering wheel rotation angle in the lateral angle dimension as the second steering wheel rotation angle.
Preferably, the steering wheel angle calculation module for calculating a third steering wheel angle of the vehicle based on the predicted information of the target path is specifically configured to:
The method comprises the steps of taking a point closest to an origin of a vehicle coordinate system on a target path as a third target point, selecting a predicted point on the target path, calculating a time interval from the third target point to the predicted point according to a speed of the vehicle, respectively determining a second transverse angle of the vehicle at the third target point and a third transverse angle of the predicted point, calculating a predicted yaw rate of the vehicle according to the second transverse angle, the third transverse angle and the time interval, obtaining a third curve curvature of the third target point, calculating a second lateral acceleration of the vehicle according to the third curve curvature and the speed, determining a third proportional control coefficient corresponding to the second lateral acceleration in a yaw rate dimension, obtaining an actual yaw rate of the vehicle, and calculating a third steering wheel corner according to the actual yaw rate, the third proportional control coefficient and the predicted yaw rate.
The invention provides a path tracking control method and a path tracking control device for an unmanned vehicle, which can respectively calculate steering wheel angles under different dimensions based on path information of a target path, attitude information of the vehicle and prediction information of the target path after the target path of the vehicle is acquired, and control the steering wheel angles of the vehicle based on the steering wheel angles to finish transverse control of the vehicle. Based on the method and the system, the full working condition and multiple scenes of the unmanned task can be dealt with, and the stability and the accuracy of path tracking are improved in the driving process of the unmanned vehicle, so that the safety performance of the unmanned vehicle is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a method flowchart of a path tracking control method for an unmanned vehicle according to an embodiment of the present invention;
FIG. 2 is an example of a target path provided by an embodiment of the present invention;
FIG. 3 is a flowchart of another method of the path tracking control method of the unmanned vehicle according to the embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating calculation of curve curvature to vehicle wheel end rotation angle according to an embodiment of the present invention;
FIG. 5 is a flowchart of another method of the path tracking control method of the unmanned vehicle according to the embodiment of the present invention;
FIG. 6 is a flowchart of a method of controlling path tracking of an unmanned vehicle according to an embodiment of the present invention;
Fig. 7 is a schematic structural diagram of a path tracking control device for an unmanned vehicle according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
The path tracking control method of the unmanned vehicle, which is provided by the invention, can be suitable for any vehicle with an unmanned function, and is particularly applied to a vehicle control layer, wherein the vehicle control layer receives a target path issued by a planning decision layer, calculates steering wheel corners (namely steering system control quantity) of the vehicle during real-time path tracking through a certain control method, and issues the steering system to an actuator layer for transverse control. Therefore, the path tracking control method directly influences the performance of the unmanned vehicle when the unmanned vehicle performs the tasks such as line patrol, parking and lane change.
Referring to fig. 1, the method for controlling path tracking of an unmanned vehicle according to the embodiment of the present invention includes the following steps:
s10, acquiring a target path of the vehicle.
In the embodiment of the invention, the planning decision layer comprehensively perceives the fusion information of the fusion layer to generate the target path of the vehicle, and the target path is transmitted to the vehicle control layer in a fitting curve mode. Specifically, the target path may be a global path or a local path, which is not limited in this embodiment.
The global path refers to a vehicle running path generated by relying on a camera or a high-precision map, and is sent to a downstream module after being processed by a sensing fusion layer, and the local path refers to a local path generated by a planning decision layer on the basis of the global path when the vehicle approaches the global path or performs tasks such as lane changing, detouring and obstacle avoidance in an automatic driving process.
The fitted curve is a two-dimensional curve of the target path in the vehicle coordinate system, with the center point of the vehicle rear axle as the origin of coordinates, and the vehicle rear axle direction and the vehicle forward direction as the transverse and longitudinal axes of coordinates. Fig. 2 is an example of a target path.
The method includes calculating a first steering wheel angle of the vehicle based on path information of a target path, calculating a second steering wheel angle of the vehicle based on posture information of the vehicle, and calculating a third steering wheel angle of the vehicle based on predicted information of the target path S20.
In the control strategy based on the path information, the vehicle control layer extracts the curvature characteristic of the curve of the target path under the vehicle coordinate system, and finally maps the curve to the steering wheel corner of the unmanned vehicle.
In a specific implementation process, the "calculating the first steering wheel angle of the vehicle based on the path information of the target path" in step S20 may include the following steps, where the method flowchart is shown in fig. 3:
s2011, selecting a first target point on a target path by utilizing the speed of the vehicle, and acquiring a first curve curvature of the first target point.
In the embodiment of the invention, considering that the steering system has a certain response delay time to the corner command issued by the vehicle control layer, when the first target point is selected, the product of the response delay time and the current speed of the vehicle is taken as the distance between the target point and the origin of coordinates, so that the corresponding point is selected from the target path as the first target point based on the distance.
In addition, in embodiments of the present invention, the curve curvature has directional characteristics and numerical characteristics, wherein the directional characteristics correspond to left and right turns of the steering system. Therefore, the embodiment of the invention can also correct the direction characteristic of the curvature of the first curve. Specifically, a plurality of points, such as ten points, located in the front-rear direction of the first target point may be selected on the target path, and the direction feature with the largest proportion may be selected as the direction feature of the first curve curvature.
And S2012, converting the curvature of the first curve into the wheel end rotation angle of the vehicle through trigonometric function change.
In the embodiment of the invention, the theory of pre-aiming tracking is referred to, the thought of arc drawing of the unmanned vehicle in the path tracking process is referred to, and the first curve curvature is converted into the wheel end rotation angle of the vehicle through trigonometric function change, so that the wheel end rotation angle is used as the feedforward control quantity of the whole vehicle path tracking control method, and the effective separation and the efficient utilization of path information are realized.
See the graph of curve curvature to vehicle wheel end rotation calculation shown in fig. 4. Based on the arc drawing concept, the vehicle can travel along a path with a fixed curvature when the wheel end rotation angle of the vehicle is at a fixed angle. When the vehicle is in a tracking path, the vehicle is assumed to run according to a curve curvature, and the wheel end rotation angle of the vehicle under the curvature can be calculated, so that the relation between the curve curvature and the wheel end rotation angle of the vehicle is approximately obtained as shown in a trigonometric function relation in the figure.
S2013, taking the steering wheel angle mapped by the vehicle wheel end angle as a first steering wheel angle according to a preset mapping relation.
In the embodiment of the invention, the mapping relation between the wheel end rotation angle of the vehicle and the steering wheel rotation angle can be set based on priori knowledge, and the steering wheel rotation angles corresponding to different wheel end rotation angles of the vehicle are recorded.
In addition, in the embodiment of the invention, the control strategy based on the gesture information is that the gesture information of the unmanned vehicle is extracted and effectively utilized. When the unmanned vehicle performs path tracking control, the target path issued by the upper layer of the unmanned system is mapped to the vehicle coordinate system. The vehicle coordinate system is a coordinate system having a center of a rear axle of the vehicle as a coordinate origin and an axle as an XY axis.
In the vehicle coordinate system, the coordinate equation of the target path in the coordinate system is combined, and the posture information of the vehicle at each moment can be calculated, wherein the posture information comprises the distance (namely transverse offset) between the center point of the rear axle of the vehicle and the nearest point of the target path, and the included angle (namely transverse angle) between the advancing direction of the vehicle and the tangential direction of the target path.
The control strategy based on the attitude information consists of two parts, namely lateral offset and lateral angle feedback control. Firstly, a feature extraction function is designed to extract the transverse offset and the transverse angle of the vehicle relative to the target path under the vehicle coordinate system. And then design control application strategies:
For the lateral offset, the relative distance relation between the vehicle and the target path is represented, but because the signal transmission from the unmanned system planning decision layer to the vehicle control layer or from the vehicle control layer to the actuator layer has time delay, corresponding consideration needs to be made when designing a control method taking the lateral offset as a feedback quantity.
For the application strategy of the transverse offset, the method mainly applies the application strategy of the transverse offset to the proportional control loop by combining the vehicle speed and the curve curvature design related parameters, meanwhile, the performance of the vehicle during high-speed running is sensitive to steering adjustment, and a limiting unit output by the proportional loop is designed from the aspect of system control safety, so that the oscillation phenomenon of overlarge adjustment of the transverse offset abnormality of the steering system caused by other factors under each vehicle speed is avoided.
For the lateral angle, which characterizes the relative angular relationship between the vehicle and the target path, the control strategy is more sensitive to the overall control result. The transverse angle is calculated according to a coordinate equation of a target path under a vehicle coordinate system, and distortion to a certain extent exists from a curve fitting process to an angle calculating process, but the transverse angle is an important control quantity. Therefore, when designing a control method using the lateral angle as a feedback amount, it is used as an auxiliary adjustment control amount of the lateral shift control result. The control method based on the vehicle attitude information is formed by the combined action of the control method and the control method, and the feedforward control based on the path information is assisted, so that the unmanned vehicle can finish stable and accurate tracking of the target path in most scenes.
For the application strategy of the transverse angle, the related parameters are designed by combining the vehicle speed and the curve curvature to be applied to the proportional control ring, and a limiting unit of the output of the proportional control ring is designed from the aspect of system control safety, so that the phenomenon of oscillation of excessive adjustment of the deviation angle abnormality of the steering system caused by other factors at each vehicle speed is avoided.
Through extraction and application of the lateral offset and the lateral angle vehicle attitude information, stable and accurate tracking of the target path of the unmanned vehicle in most driving environments is ensured.
In a specific implementation process, the "calculate the second steering wheel angle of the vehicle based on the posture information of the vehicle" in step S20 may include the following steps, where a method flowchart is shown in fig. 5:
S2021 takes a point closest to the origin of the vehicle coordinate system on the target path as the second target point.
In the embodiment of the invention, a search function is designed to search a point closest to the origin of the own vehicle coordinate system of the vehicle, namely the center point of the rear axle of the vehicle, on the target path as a second target point.
S2022, determining the lateral offset and the first lateral angle of the vehicle at the second target point.
In the embodiment of the invention, the distance between the second target point and the origin of the coordinate system of the vehicle is used as the transverse offset of the vehicle, and the direction of the second target point is defined. And (3) making a tangent line of the curve on the second target point, and taking an included angle formed by the tangent line and the vehicle advancing direction as a transverse angle, and defining the direction of the transverse angle. With continued reference to fig. 2, the target path start point in fig. 2 may be taken as a second target point, whose lateral offset and lateral angle are shown.
S2023, acquiring a second curve curvature of the second target point, and calculating first lateral acceleration of the vehicle by using the second curve curvature and the speed of the vehicle.
In the embodiment of the invention, the first lateral acceleration is equal to the product of the square of the current speed of the vehicle and the curvature of the second curve.
S2024, determining a first proportional control coefficient corresponding to the first lateral acceleration in the lateral offset dimension, and a second proportional control coefficient corresponding to the first lateral acceleration in the lateral angular dimension.
In the embodiment of the invention, because the lateral acceleration represents the lateral stability in the running process of the vehicle, when the first proportional control coefficient in the lateral offset dimension and the second proportional control coefficient in the lateral angle dimension are designed, the basic principle of the design is that the larger the first lateral acceleration is, the smaller the proportional control coefficient is, so that the phenomenon that the vehicle outputs a larger corner control amount when the lateral stability is poor to aggravate the lateral instability state is avoided.
And S2025, calculating the steering wheel angle in the transverse offset dimension according to the first proportional control coefficient and the transverse offset, and calculating the steering wheel angle in the transverse angle dimension according to the second proportional control coefficient and the first transverse angle.
In the embodiment of the invention, the feedback control target based on the lateral offset is to control the feedback control target to tend to 0, so that the vehicle can accurately track the target path, and therefore the proportional link output value, namely the steering wheel rotation angle=the first proportional control coefficient in the lateral offset dimension, is subjected to lateral offset.
Accordingly, the feedback control target based on the transverse angle in the embodiment of the invention also controls the feedback control target to tend to 0, so that the vehicle can accurately track the target path, and therefore the proportional link output value, namely the steering wheel angle in the transverse angle dimension=the second proportional control coefficient, is equal to the first transverse angle.
In addition, since the steering wheel angle in the transverse offset dimension and the steering wheel angle in the transverse angle dimension are calculated according to the target path, and the target path has the occasional instability, the invention can limit the upper limit, the lower limit and the change slope of the output (the steering wheel angle in the transverse offset dimension and the steering wheel angle in the transverse angle dimension) of the comparative example link, and reduce the influence of the occasional instability state of the track.
S2026, adding the superposition of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle.
On the basis, for the application strategy of the transverse offset, the method considers the curve curvature of the target path and the related control parameters under the vehicle speed, and designs a real-time dynamic integral compensation method for more accurately adjusting the vehicle position, and the influence of different path curvatures and the vehicle speed is also considered.
Specifically, on the basis of the path tracking control method of the unmanned vehicle shown in fig. 5, the method further comprises the following steps:
under the condition that the running state of the vehicle accords with a preset dynamic integral compensation condition, determining a compensated integral step length according to the first lateral acceleration;
correspondingly, step S2026 specifically comprises summing the sum of the steering wheel angle compensated in the lateral offset dimension and the steering wheel angle in the lateral angular dimension as the second steering wheel angle.
In the embodiment of the invention, the response of the steering system between vehicles has static deviation, the difference between the vehicles needs to be eliminated when dynamic integral compensation is designed, and the influence of the scene needs to be eliminated when the vehicles stably run in the scenes such as larger crosswind. Therefore, the invention adjusts the output steering wheel angle in real time according to the change of the transverse offset in the running process of the vehicle.
The dynamic integral compensation condition comprises that the mark bit of the intelligent driving state is yes, the transverse offset is larger than a preset compensation critical value, the transverse offset is continuously increased in a plurality of calculation periods, and the mark bit of the lane change state is no.
Furthermore, the basic principle of design is that the larger the first lateral acceleration, the smaller the integration step is, when designing the integration step of the dynamic integration compensation, so that unnecessary adjustments in unstable states of the vehicle are avoided.
It should be noted that, when the running state of the vehicle does not meet the preset dynamic integral compensation condition, the dynamic integral compensation is exited, and the integral step before exiting is maintained as the reference of the subsequent compensation.
In addition, in the embodiment of the invention, the control strategy based on the prediction information considers that the two parts are control methods designed based on the current real-time information, whether based on the path information or the vehicle body posture information. However, in the driving process of the unmanned vehicle, on one hand, due to the time delay of the acquisition, calculation and control links of the real-time information, on the other hand, due to the fact that atypical driving scenes such as sudden sharp-curve changes on straight roads, irregular curve road driving and the like are required to be faced in the driving process, the control requirements are difficult to be well covered by a control strategy based on the real-time information, and therefore the relevant information of the driving of the vehicle needs to be predicted, extracted and utilized.
In order to improve the driving stability of an unmanned vehicle in road traffic environments such as abrupt curvature change, future roads and vehicle information of the vehicle driving need to be extracted and utilized based on the prediction thought. The yaw rate of the vehicle in the running process represents the transverse movement stability of the vehicle, when the unmanned vehicle runs on paths such as curvature abrupt change, the change of future road information needs to be predicted in advance so as to adopt corresponding control optimization strategies, and the control strategies of the first two parts based on the current position path and the attitude information of the vehicle are difficult to completely cover the path tracking requirements. Therefore, on the basis of the two control strategies, the control strategy based on the prediction information is designed, so that the driving stability of the unmanned vehicle can be improved.
In the driving process of the unmanned vehicle, the predicted vehicle reaches the predicted position point after a period of time from the current position point, and the yaw angle change of the vehicle is predicted based on the predicted position point, namely, the predicted yaw rate is obtained. In combination with the predicted yaw rate and the actual yaw rate of the current position point of the vehicle, a control method based on the predicted information is designed, namely, the difference value between the predicted yaw rate and the actual yaw rate is used as a control quantity to adjust the real-time position of the vehicle. Therefore, the unmanned vehicle can further help to improve the stability and the accuracy of tracking when the unmanned vehicle performs path tracking on roads with variable curvatures and the like.
In a specific implementation process, the "calculating the third steering wheel angle of the vehicle based on the prediction information of the target path" in step S20 may include the following steps, where a method flowchart is shown in fig. 6:
S2031, taking a point closest to the origin of the vehicle coordinate system on the target path as a third target point, and selecting a predicted point on the target path.
In the embodiment of the invention, a search function is designed to search a point closest to the origin of the own vehicle coordinate system of the vehicle, namely the center point of the rear axle of the vehicle, on the target path as a third target point. The predicted point is a point with a certain distance from the third target point on the target path, the distance is preset, and the distance is proportional to the current speed of the vehicle.
With continued reference to fig. 2, the target path start point in fig. 2 may be the third target point, the lateral angle of which is shown, and the predicted point in fig. 2 is located between the target path start point and the target path end point, the lateral angle of which is shown.
S2032, calculating a time interval from the third target point to the predicted point according to the vehicle speed of the vehicle.
In the embodiment of the invention, the time interval from the third target point to the predicted point is equal to the value obtained by dividing the distance from the third target point to the predicted point in the target path by the current speed of the vehicle.
S2033, determining a second lateral angle of the vehicle at the third target point and a third lateral angle of the predicted point, respectively, and calculating a predicted yaw rate of the vehicle according to the second lateral angle, the third lateral angle, and the time interval.
The predicted yaw rate is a conceptual yaw rate of the vehicle and is not a predicted yaw rate at the point.
In the embodiment of the present invention, the predicted yaw rate= (third lateral angle-second lateral angle)/time interval.
S2034, a third curve curvature of the third target point is acquired, and a second lateral acceleration of the vehicle is calculated using the third curve curvature and the vehicle speed.
In an embodiment of the invention, the second lateral acceleration is equal to a product of a square of a current vehicle speed and a curvature of the third curve.
S2035, determining a third proportional control coefficient corresponding to the second lateral acceleration in the yaw-rate dimension.
In the embodiment of the invention, because the lateral acceleration represents the lateral stability in the running process of the vehicle, when the third proportional control coefficient under the transverse swing angular velocity dimension is designed, the basic principle of the design is that the larger the second lateral acceleration is, the smaller the proportional control coefficient is, so that the phenomenon that the lateral instability state is aggravated due to the fact that the vehicle outputs a larger corner control amount when the lateral stability is poor is avoided.
S2036, acquiring an actual yaw rate of the vehicle, and calculating a third steering wheel angle from the actual yaw rate, the third proportional control coefficient, and the predicted yaw rate.
In the embodiment of the present invention, the third steering wheel angle= (predicted yaw rate-actual yaw rate) ×the third proportional control coefficient.
Through the combined action of the three control strategies, the unmanned vehicle can stably and accurately track the target path of the unmanned system when the unmanned vehicle performs the tasks of line patrol, parking, lane change and the like, and plays an important role in improving the driving safety of the unmanned vehicle.
S30, controlling a steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle and the third steering wheel angle so as to transversely control the vehicle.
In the embodiment of the invention, the superposition of the first steering wheel angle, the second steering wheel angle and the third steering wheel angle can be used as the actual steering wheel angle for controlling the steering wheel of the vehicle, so that the actual steering wheel angle is issued to the steering system of the actuator layer, and the vehicle is transversely controlled.
According to the path tracking control method for the unmanned vehicle, after the target path of the vehicle is obtained, steering wheel angles in different dimensions can be calculated respectively based on the path information of the target path, the posture information of the vehicle and the prediction information of the target path, and the steering wheel angles of the vehicle are controlled based on the steering wheel angles, so that transverse control of the vehicle is completed. Based on the method and the system, the full working condition and multiple scenes of the unmanned task can be dealt with, and the stability and the accuracy of path tracking are improved in the driving process of the unmanned vehicle, so that the safety performance of the unmanned vehicle is ensured.
Based on the method for controlling path tracking of the unmanned vehicle provided by the embodiment, the embodiment of the invention correspondingly provides a device for executing the method for controlling path tracking of the unmanned vehicle, and a schematic structural diagram of the device is shown in fig. 7, including:
the path acquisition module 10 is used for acquiring a target path of the vehicle.
The steering wheel angle calculation module 20 is used for calculating a first steering wheel angle of the vehicle based on the path information of the target path, calculating a second steering wheel angle of the vehicle based on the attitude information of the vehicle, and calculating a third steering wheel angle of the vehicle based on the prediction information of the target path.
The lateral control module 30 is configured to control a steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle, and the third steering wheel angle, so as to control the vehicle laterally.
Optionally, the steering wheel angle calculation module 20 for calculating a first steering wheel angle of the vehicle based on the path information of the target path is specifically configured to:
The method comprises the steps of selecting a first target point on a target path by utilizing the speed of a vehicle, obtaining first curve curvature of the first target point, converting the first curve curvature into a wheel end turning angle of the vehicle through trigonometric function change, and taking the turning angle of a steering wheel mapped by the wheel end turning angle of the vehicle as a first steering wheel turning angle according to a preset mapping relation.
Optionally, the steering wheel angle calculation module 20 is further configured to:
the directional characteristic of the curvature of the first curve is corrected.
Optionally, the steering wheel angle calculation module 20 is configured to calculate the second steering wheel angle of the vehicle based on the posture information of the vehicle, specifically configured to:
The method comprises the steps of taking a point closest to an origin of a vehicle coordinate system on a target path as a second target point, determining lateral offset and a first lateral angle of the vehicle at the second target point, obtaining second curve curvature of the second target point, calculating first lateral acceleration of the vehicle by using the second curve curvature and speed of the vehicle, determining a first proportional control coefficient corresponding to the first lateral acceleration in a lateral offset dimension and a second proportional control coefficient corresponding to the first lateral acceleration in a lateral angle dimension, calculating steering wheel rotation angle in the lateral offset dimension according to the first proportional control coefficient and the lateral offset, calculating steering wheel rotation angle in the lateral angle dimension according to the second proportional control coefficient and the first lateral angle, and taking superposition sum of the steering wheel rotation angle in the lateral offset dimension and the steering wheel rotation angle in the lateral angle dimension as the second steering wheel rotation angle.
Optionally, the steering wheel angle calculation module 20 is further configured to:
under the condition that the running state of the vehicle accords with a preset dynamic integral compensation condition, determining a compensated integral step length according to the first lateral acceleration;
Accordingly, the steering wheel angle calculation module 20 is configured to sum the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle, and specifically is configured to:
And taking the superposition of the steering wheel angle compensated in the transverse offset dimension and the steering wheel angle in the transverse angle dimension as a second steering wheel angle.
Optionally, the steering wheel angle calculation module 20 is configured to calculate a third steering wheel angle of the vehicle based on the predicted information of the target path, and specifically is configured to:
The method comprises the steps of taking a point closest to an origin of a vehicle coordinate system on a target path as a third target point, selecting a predicted point on the target path, calculating a time interval from the third target point to the predicted point according to a speed of the vehicle, respectively determining a second transverse angle of the vehicle at the third target point and a third transverse angle of the predicted point, calculating a predicted yaw rate of the vehicle according to the second transverse angle, the third transverse angle and the time interval, obtaining a third curve curvature of the third target point, calculating a second lateral acceleration of the vehicle by using the third curve curvature and the speed, determining a third proportional control coefficient corresponding to the second lateral acceleration in a yaw rate dimension, obtaining an actual yaw rate of the vehicle, and calculating a third steering wheel corner according to the actual yaw rate, the third proportional control coefficient and the predicted yaw rate.
According to the path tracking control device for the unmanned vehicle, after the target path of the vehicle is acquired, steering wheel angles in different dimensions can be calculated respectively based on the path information of the target path, the posture information of the vehicle and the prediction information of the target path, and the steering wheel angles of the vehicle are controlled based on the steering wheel angles, so that transverse control of the vehicle is completed. Based on the method and the system, the full working condition and multiple scenes of the unmanned task can be dealt with, and the stability and the accuracy of path tracking are improved in the driving process of the unmanned vehicle, so that the safety performance of the unmanned vehicle is ensured.
The foregoing describes the method and apparatus for controlling path tracking of an unmanned vehicle according to the present invention in detail, and specific examples are provided herein to illustrate the principles and embodiments of the invention, and the above description of the examples is only for aiding in understanding the method and core concept of the invention, and meanwhile, to those skilled in the art, according to the concept of the invention, there are variations in the specific embodiments and application ranges, so the disclosure should not be construed as limiting the invention.
It should be noted that, in the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described as different from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
It is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include, or is intended to include, elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
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| CN116001908A (en) * | 2022-12-05 | 2023-04-25 | 宁波均胜智能汽车技术研究院有限公司 | Vehicle transverse control method and system, vehicle and readable storage medium |
| CN116215661B (en) * | 2023-01-31 | 2024-10-25 | 广汽埃安新能源汽车股份有限公司 | Parking control method and device for vehicle, vehicle and electronic equipment |
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