CN113635920B - Weight self-adaptive transverse and longitudinal coupling tracking control method and system - Google Patents

Weight self-adaptive transverse and longitudinal coupling tracking control method and system Download PDF

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CN113635920B
CN113635920B CN202111093661.XA CN202111093661A CN113635920B CN 113635920 B CN113635920 B CN 113635920B CN 202111093661 A CN202111093661 A CN 202111093661A CN 113635920 B CN113635920 B CN 113635920B
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tracking
acceleration
weight
transverse
vehicle
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CN113635920A (en
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刘阳
田磊
贾敏
赵玉超
赵德赢
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China National Heavy Duty Truck Group Jinan Power Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0011—Planning or execution of driving tasks involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/107—Longitudinal acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/109—Lateral acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/53—Road markings, e.g. lane marker or crosswalk

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Abstract

The invention provides a weight self-adaptive transverse and longitudinal coupling tracking control method and a system, and relates to the technical field of automatic driving; determining the current absolute position of the controlled vehicle and the relative position of the controlled vehicle and the expected track curve; selecting a plurality of target points, generating a plurality of expected tracking velocity vectors by combining the current position, calculating the tracking error between a reference velocity vector and an actual velocity vector, and performing decision of a weight matrix according to the current curvature and the velocity through a weight self-adaptive module calculator; the acceleration decision module carries out acceleration decision by utilizing the velocity vector tracking error and the weight matrix to obtain the expected optimal longitudinal acceleration and the expected optimal transverse acceleration; the execution control module is used for controlling a steering wheel, an accelerator pedal and a brake pedal, the expected acceleration is tracked, and the purpose of transverse and longitudinal coupling tracking control is finally achieved.

Description

Weight self-adaptive transverse and longitudinal coupling tracking control method and system
Technical Field
The invention relates to the technical field of automatic driving, in particular to a weight self-adaptive transverse and longitudinal coupling tracking control method and system.
Background
The tracking of speed and path is a function which must be realized by the automatic driving automobile in road driving, and directly influences the performance and driving safety of the automatic driving automobile. The transverse and longitudinal coupling tracking control of automatic driving is a technology for keeping integrated control of automatic cruise control and lane centering, and can improve the capability of processing complex road conditions of an automatic driving automobile.
In the traditional path tracking, a single-point preview method is mostly adopted, and a preview point is selected from a reference path and is adjusted according to the running state of a vehicle. With the development and the progress of an automatic driving technology, the related research of transverse path tracking through multi-point preview is gradually increased, and the method adjusts the number and the weight of the preview points according to road information and the driving state of a vehicle, can improve the transverse tracking precision of the vehicle, and improves the driving comfort, the safety and the like.
In the prior art, CN 110001637A discloses a multi-point tracking-based automatic-driving-vehicle path tracking control device and a control method, which can select course angles and positions of a plurality of preview points for tracking, and finally sum up and output each front-wheel steering angle according to weight. However, the method can only perform transverse path tracking control, cannot consider the coupling effect of longitudinal motion and transverse motion when the vehicle speed changes, and cannot perform adaptive adjustment because the weighting factors of the plurality of preview points are the same.
Chinese patent CN 109515440A discloses a variable weight multi-point preview track tracking method based on vehicle speed, which averagely divides the optimal and small distances and the longest preview distance into three points, and weights the preview distance on the basis of fixed weight. The method only considers the working condition of transverse tracking, and the basis of the change of the weight is the vehicle speed, so that the self-adaptive adjustment can not be carried out under the working conditions of different curvatures.
Chinese patent CN 109214127A discloses a multi-point sighting method and a multi-point sighting device and target path tracking method thereof, which sets three measuring points and calculates the lateral deviation and the ideal yaw angular velocity, and obtains the ideal steering wheel angle of the vehicle according to a predetermined coefficient. The weight coefficient of the multipoint preview cannot be adjusted in a self-adaptive manner, and is essentially an averaging process of a plurality of preview point parameters.
Disclosure of Invention
The invention provides a weight self-adaptive transverse and longitudinal coupling tracking control method for realizing the purpose of transverse and longitudinal coupling tracking control, which comprises the following steps:
the method comprises the following steps: obtaining lane line information of a current driving road of a vehicle, and fitting the lane line information into an identifiable path function; collecting the current running state of the vehicle;
step two: the speed vector generator obtains a plurality of speed vectors according to the path function fitted in the step one and the current running state of the vehicle, and the speed vectors all point to the tracking target point by the current position point;
step three: the weight self-adaptive calculator calculates a weight factor according to the curvature of each target point and obtains a weight factor matrix;
step four: calculating a velocity tracking error matrix between all the expected velocity vectors and the current velocity vector by a tracking error calculator;
step five: the optimal acceleration decision maker carries out acceleration decision by taking the minimized error as a control target according to the weight coefficient matrix and the speed tracking error matrix to obtain the optimal longitudinal acceleration and the optimal transverse acceleration of the vehicle;
step six: and the expected optimal longitudinal acceleration and transverse acceleration are obtained for tracking by controlling the steering wheel angle, the opening of an acceleration pedal and the opening of a brake pedal.
It should be further noted that, in the first step, the lane line information includes a function fitted to the lane line and a curvature of the target point.
It should be further noted that, in the second step,
the speed vector generator obtains a plurality of target point positions in the expected tracking path through the target vehicle speed U and the preview time T, and forms a plurality of reference speed vectors V ref Calculated according to the following formula:
Figure BDA0003268252430000031
wherein, V ref,i Refers to the ith reference velocity vector; x and Y are current position information of the vehicle, and the target vehicle speed U is a scalar;
X ref,i ,Y ref,i for a desired tracking path with a preview time of T i The tracking target point of time is calculated by the following formula:
Figure BDA0003268252430000032
Y ref,i ＝f(X ref,i )
wherein f (x) is an expected track function, and the longitudinal coordinate is input to obtain the transverse coordinate of the point in the path;
Figure BDA0003268252430000033
and β is the yaw angle and centroid slip angle of the vehicle; v x ，V y Respectively, the longitudinal speed and the transverse speed of the vehicle currently running.
It should be further noted that, in the third step,
the curvature of the weight adaptive calculator is calculated as follows:
ρ i ＝g(X ref,i )
wherein g (x) is an expected track curvature calculated by an expected track function;
the weight factor matrix Q is
Figure BDA0003268252430000034
The weight factor matrix Q is a positive definite matrix and satisfies
Figure BDA0003268252430000035
It should be further noted that, in the third step,
the weight factor calculation method of the weight adaptive calculator is as follows:
Figure BDA0003268252430000041
it should be further noted that, in the fourth step,
expected velocity vector V calculated by tracking error calculator ref,i And a velocity tracking error matrix between the current velocity vectors V, calculated by:
Figure BDA0003268252430000042
it should be further noted that, in the fifth step,
the optimal acceleration decision maker solves with the minimized error as a target, and the calculation formula is as follows:
minJ＝min(EQE T +ARA T )
wherein, A = [ a = x a y ]The longitudinal acceleration and the lateral acceleration are respectively expressed, and R is a weight coefficient of the acceleration.
It should be further noted that, in the fifth step,
the solving method of the minimized error includes, but is not limited to, a partial derivative method of extremum calculation by a multivariate function, a control method aiming at J being 0, a particle swarm optimization, and a genetic algorithm.
It is further noted that the method of tracking in step six includes, but is not limited to, proportional-integral-derivative control, sliding mode control, and optimal control method.
The invention also provides a weight self-adaptive transverse and longitudinal coupling tracking control system, which comprises: the system comprises an environment sensing module, a state sensing module, a transverse and longitudinal coupling tracking control module and an execution control module;
the transverse and longitudinal coupling tracking control module comprises: a velocity vector generator, a tracking error calculator, a weight self-adaptive calculator and an optimal acceleration decision maker;
the environment perception module and the state perception module are respectively connected with the transverse and longitudinal coupling tracking control module, and the transverse and longitudinal coupling tracking control module is connected with the execution control module;
the environment perception module obtains the lane line information of the current driving road of the vehicle through a camera and fits the lane line information into a recognizable path function; the state sensing module acquires the current running state of the vehicle;
the speed vector generator obtains a plurality of speed vectors according to the path function fitted by the environment sensing module and the current running state of the vehicle, and the speed vectors all point to the tracking target point by the current position point;
the weight self-adaptive calculator calculates a weight factor according to the curvature of each target point and obtains a weight factor matrix;
a tracking error calculator calculates a velocity tracking error matrix between all the expected velocity vectors and the current velocity vector;
the optimal acceleration decision device is used for carrying out acceleration decision by taking the minimized error as a control target according to the weight coefficient matrix and the speed tracking error matrix to obtain the optimal longitudinal acceleration and the optimal transverse acceleration of the vehicle;
and the execution control module is used for obtaining the expected optimal longitudinal acceleration and transverse acceleration for tracking by controlling the steering wheel angle, the opening of an acceleration pedal and the opening of a brake pedal.
According to the technical scheme, the invention has the following advantages:
the method comprises the steps that the environmental perception module is used for collecting and acquiring lane line information in a road in the driving direction of a vehicle to form a tracking track curve; determining the current absolute position of the controlled vehicle and the relative position of the controlled vehicle and the expected track curve through a positioning module; selecting a plurality of target points by the transverse and longitudinal coupling tracking control module, generating a plurality of speed vectors expected to be tracked by combining the current position, calculating the tracking error between the reference speed vector and the actual speed vector, and making a weight matrix decision according to the current curvature and the speed by the weight adaptive module calculator; the acceleration decision module carries out acceleration decision by utilizing the velocity vector tracking error and the weight matrix to obtain the expected optimal longitudinal acceleration and the expected optimal transverse acceleration; the execution control module is used for controlling a steering wheel, an accelerator pedal and a brake pedal, the expected acceleration is tracked, and the purpose of transverse and longitudinal coupling tracking control is finally achieved.
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In order to more clearly illustrate the technical solution of the present invention, the drawings required to be used in the description will be briefly introduced below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of a weight adaptive transverse and longitudinal coupling tracking control system;
FIG. 2 is a flow chart of a weight adaptive transversal and longitudinal coupling tracking control method;
FIG. 3 is a diagram of multiple reference velocity vectors;
FIG. 4 is a schematic diagram of algorithm path tracking comparison.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The units and algorithm steps of each example described in the embodiments disclosed in the method and system for weight adaptive cross-longitudinal coupling tracking control according to the present invention can be implemented by electronic hardware, computer software, or a combination of both, and in the above description, the components and steps of each example have been generally described in terms of functions in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The block diagram shown in the figure of the weight adaptive transverse and longitudinal coupling tracking control method and system provided by the invention is only a functional entity and does not necessarily correspond to a physically independent entity. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
In the weight adaptive transversal and longitudinal coupling tracking control method and system provided by the invention, it should be understood that the disclosed system, apparatus and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
The invention provides a weight self-adaptive transverse and longitudinal coupling tracking control system, as shown in fig. 1, the system comprises: the system comprises an environment perception module (1), a state perception module (2), a transverse and longitudinal coupling tracking control module (3) and an execution control module (4);
the transverse and longitudinal coupling tracking control module (3) comprises: a velocity vector generator (3.1), a tracking error calculator (3.2), a weight self-adaptive calculator (3.3) and an optimal acceleration decision maker (3.4);
the environment perception module (1) and the state perception module (2) are respectively connected with the transverse and longitudinal coupling tracking control module (3), and the transverse and longitudinal coupling tracking control module (3) is connected with the execution control module (4);
the environment perception module (1) obtains lane line information of a current driving road of a vehicle through a camera and fits the lane line information into a recognizable path function; the state sensing module (2) collects the current running state of the vehicle;
the speed vector generator (3.1) obtains a plurality of speed vectors according to the path function fitted by the environment sensing module (1) and the current running state of the vehicle, and the speed vectors all point to the tracking target point from the current position point;
a weight adaptive calculator (3.3) calculates a weight factor according to the curvature of each target point and obtains a weight factor matrix;
a tracking error calculator (3.2) calculates a velocity tracking error matrix between all the desired velocity vectors and the current velocity vector;
the optimal acceleration decision device (3.4) is used for carrying out acceleration decision by taking the minimized error as a control target according to the weight coefficient matrix and the speed tracking error matrix to obtain the optimal longitudinal acceleration and the optimal transverse acceleration of the vehicle;
and the execution control module (4) is used for obtaining the expected optimal longitudinal acceleration and lateral acceleration for tracking by controlling the steering wheel angle, the accelerator pedal opening and the brake pedal opening.
Compared with single-point preview, the system of the invention has better control stability and tracking precision, and needs less calculation requirements compared with model prediction control.
Based on the above system, the present invention further provides a weight adaptive transversal and longitudinal coupling tracking control method, as shown in fig. 2, the method includes:
s101: obtaining lane line information of a current driving road of a vehicle, and fitting the lane line information into an identifiable path function; collecting the current running state of the vehicle; the current driving state of the vehicle includes the current longitudinal and lateral positions, the longitudinal and lateral vehicle speeds, the yaw angle, and the yaw rate.
And the lane line information in the step one comprises a function fitted by the lane line and the curvature of a target point.
S102: the speed vector generator obtains a plurality of speed vectors according to the path function fitted in the step one and the current running state of the vehicle, and the speed vectors all point to the tracking target point by the current position point;
the coordinates of the path points selected in this embodiment may be obtained by looking up a table:
statistical table of path characteristic points
Figure BDA0003268252430000081
Considering the controlled vehicle as particles with weight, ignoring the yaw motion of the vehicle, the motion of the vehicle particles can be described by a dual integral model:
Figure BDA0003268252430000082
Figure BDA0003268252430000083
wherein X = [ X, y] T ,V＝[v x ,v y ] T ,A＝[a x ,a y ] T Respectively, the lateral longitudinal displacement, the velocity and the acceleration of the vehicle.
The speed vector generator obtains a plurality of target point positions in the expected tracking path through the target vehicle speed U and the preview time T, and forms a plurality of reference speed vectors V according to the position information in the figure 3 ref Calculated according to the following formula:
Figure BDA0003268252430000091
wherein, V ref,i Refers to the ith reference velocity vector; x and Y are current position information of the vehicle, and the target vehicle speed U is a scalar;
X ref,i ,Y ref,i for a desired tracking path the preview time is T i The tracking target point of time is calculated by the following formula:
Figure BDA0003268252430000092
Y ref,i ＝f(X ref,i )
wherein f (x) is an expected track function, and the longitudinal coordinate is input to obtain the transverse coordinate of the point in the path;
Figure BDA0003268252430000093
and β is the yaw angle and the centroid slip angle of the vehicle; v x ，V y Respectively, the longitudinal vehicle speed and the transverse vehicle speed of the current running vehicle.
S103: the weight self-adaptive calculator calculates a weight factor according to the curvature of each target point and obtains a weight factor matrix;
the weight factor adaptive method according to the present invention may include a method of considering curvature, and the larger the curvature of the point, the larger the weight coefficient.
The curvature of the weight adaptive calculator is calculated as follows:
ρ i ＝g(X ref,i )
wherein g (x) is the curvature of the expected track calculated by the expected track function;
the weight factor matrix Q is
Figure BDA0003268252430000101
The weight factor matrix Q is a positive definite matrix and satisfies
Figure BDA0003268252430000102
The weight factor calculation method of the weight adaptive calculator of the invention is as follows:
Figure BDA0003268252430000103
it is obvious that
Figure BDA0003268252430000104
n is the total number of reference velocity vectors, which is selected to be 3 in this particular embodiment.
S104: calculating a velocity tracking error matrix between all the expected velocity vectors and the current velocity vector by a tracking error calculator;
in the present invention, the desired velocity vector V calculated by the tracking error calculator ref,i And a velocity tracking error matrix between the current velocity vectors V, calculated by:
Figure BDA0003268252430000105
s105: the optimal acceleration decision-making device takes the minimized error as a control target to carry out acceleration decision-making according to the weight coefficient matrix and the speed tracking error matrix so as to obtain the optimal longitudinal acceleration and the optimal transverse acceleration of the vehicle;
the optimal acceleration decision-making device solves by taking the minimized error as a target, and the calculation formula is as follows:
minJ＝min(EQE T +ARA T )
wherein, A = [ a ] x a y ]The longitudinal acceleration and the lateral acceleration are respectively expressed, and R is a weight coefficient of the acceleration.
The solving method of the minimized error includes, but is not limited to, a partial derivative method of extremum calculation by a multivariate function, a control method aiming at J being 0, a particle swarm optimization, and a genetic algorithm.
S106: and the expected optimal longitudinal acceleration and transverse acceleration are obtained for tracking by controlling the steering wheel angle, the opening of an acceleration pedal and the opening of a brake pedal.
The tracking method includes and is not limited to proportional-integral-derivative control, sliding mode control and optimal control method.
FIG. 4 is a comparison of the proposed method of the present invention with common single-point predictive and model predictive control algorithms, respectively. The curvature change of the vehicle is large, and the verification result shows that the method has better control stability and tracking precision compared with single-point preview, needs less calculation requirements compared with model prediction control, and improves the data processing efficiency.
The method comprises the steps that the environmental perception module is used for collecting and acquiring lane line information in a road in the driving direction of a vehicle to form a tracking track curve; determining the current absolute position of the controlled vehicle and the relative position of the controlled vehicle and the expected track curve through a positioning module; selecting a plurality of target points by the transverse and longitudinal coupling tracking control module, generating a plurality of speed vectors expected to be tracked by combining the current position, calculating the tracking error between the reference speed vector and the actual speed vector, and making a weight matrix decision according to the current curvature and the speed by the weight adaptive module calculator; the acceleration decision module carries out acceleration decision by utilizing the velocity vector tracking error and the weight matrix to obtain the expected optimal longitudinal acceleration and transverse acceleration; and the execution control module is used for controlling a steering wheel, an accelerator pedal and a brake pedal, tracking the expected acceleration and finally realizing the purpose of transverse and longitudinal coupling tracking control.
The weight adaptive cross-longitudinal coupling tracking control method and system provided by the present invention are the units and algorithm steps of each example described in connection with the embodiments disclosed herein, and can be implemented in electronic hardware, computer software, or a combination of both, and in the above description, the components and steps of each example have been generally described in terms of function in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
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.

Claims (10)

1. A weight adaptive transverse and longitudinal coupling tracking control method is characterized by comprising the following steps:
the method comprises the following steps: acquiring lane line information of a current driving road of a vehicle, and fitting the lane line information into an identifiable path function; collecting the current running state of the vehicle;
step two: the speed vector generator obtains a plurality of speed vectors according to the path function fitted in the step one and the current running state of the vehicle, and the speed vectors all point to the tracking target point by the current position point;
step three: the weight self-adaptive calculator calculates a weight factor according to the curvature of each target point and obtains a weight factor matrix;
step four: calculating a velocity tracking error matrix between all the expected velocity vectors and the current velocity vector by a tracking error calculator;
step five: the optimal acceleration decision-making device takes the minimized error as a control target to carry out acceleration decision-making according to the weight coefficient matrix and the speed tracking error matrix so as to obtain the optimal longitudinal acceleration and the optimal transverse acceleration of the vehicle;
step six: and the expected optimal longitudinal acceleration and transverse acceleration are obtained for tracking by controlling the steering wheel angle, the opening of an acceleration pedal and the opening of a brake pedal.
2. The weight adaptive transversal-longitudinal coupling tracking control method according to claim 1,
in the first step, the lane line information includes a lane line fitting function and a target point curvature.
3. The weight adaptive transversal-longitudinal coupling tracking control method according to claim 1,
in the second step, the first step is carried out,
the speed vector generator obtains a plurality of target point positions in the expected tracking path through the target vehicle speed U and the preview time T, and forms a plurality of reference speed vectors V ref Calculated according to the following formula:
Figure FDA0003964052650000021
wherein, V ref,i Refers to the ith reference velocity vector; x and Y are current position information of the vehicle, and the target vehicle speed U is a scalar;
X ref,i ,Y ref,i for a desired tracking path the preview time is T i The tracking target point of time is calculated by the following formula:
Figure FDA0003964052650000022
Y ref,i ＝f(X ref,i )
wherein f (x) is an expected track function, and the longitudinal coordinate is input to obtain the transverse coordinate of the point in the path;
Figure FDA0003964052650000023
and β is the yaw angle and the centroid slip angle of the vehicle; v x ，V y Respectively, the longitudinal speed and the transverse speed of the vehicle currently running.
4. The weight adaptive transversal-longitudinal coupling tracking control method according to claim 3, characterized in that in step three,
the curvature of the weight adaptive calculator is calculated as follows:
ρ i ＝g(X ref,i )
wherein g (x) is the curvature of the expected track calculated by the expected track function;
the weight factor matrix Q is
Figure FDA0003964052650000024
The weight factor matrix Q is a positive definite matrix and satisfies
Figure FDA0003964052650000025
5. The weight adaptive transversal-longitudinal coupling tracking control method according to claim 4, wherein in step three,
the weight factor calculation method of the weight adaptive calculator is as follows:
Figure FDA0003964052650000031
6. the weight adaptive transversal-longitudinal coupling tracking control method according to claim 1, wherein in step four,
the expected velocity vector V calculated by the tracking error calculator ref,i And a velocity tracking error matrix between the current velocity vectors V, calculated by:
Figure FDA0003964052650000032
7. the weight adaptive transversal-longitudinal coupling tracking control method according to claim 1, wherein in step five,
the optimal acceleration decision maker solves with the minimized error as a target, and the calculation formula is as follows:
min J＝min(EQE T +ARA T )
wherein, A = [ a ] x a y ]The longitudinal acceleration and the lateral acceleration are respectively expressed, and R is a weight coefficient of the acceleration.
8. The weight adaptive transversal-longitudinal coupling tracking control method according to claim 1, wherein in step five,
the solving method of the minimized error includes, but is not limited to, a partial derivative method of extremum calculation by a multivariate function, a control method aiming at J being 0, a particle swarm optimization, and a genetic algorithm.
9. The method for weight adaptive transverse and longitudinal coupling tracking control according to claim 1, wherein the tracking method in the sixth step includes, but is not limited to, proportional-integral-derivative control, sliding mode control, and optimal control method.
10. A weight adaptive transversal and longitudinal coupling tracking control system, characterized in that the system adopts the weight adaptive transversal and longitudinal coupling tracking control method as claimed in any one of claims 1 to 9;
the system comprises: the system comprises an environment perception module (1), a state perception module (2), a transverse and longitudinal coupling tracking control module (3) and an execution control module (4);
the transverse and longitudinal coupling tracking control module (3) comprises: a velocity vector generator (3.1), a tracking error calculator (3.2), a weight self-adaptive calculator (3.3) and an optimal acceleration decision maker (3.4);
the environment perception module (1) and the state perception module (2) are respectively connected with the transverse and longitudinal coupling tracking control module (3), and the transverse and longitudinal coupling tracking control module (3) is connected with the execution control module (4);
the environment perception module (1) obtains lane line information of a current driving road of a vehicle through a camera and fits the lane line information into a recognizable path function; the state sensing module (2) collects the current running state of the vehicle;
the speed vector generator (3.1) obtains a plurality of speed vectors according to the path function fitted by the environment sensing module (1) and the current running state of the vehicle, and the speed vectors all point to the tracking target point from the current position point;
a weight adaptive calculator (3.3) calculates a weight factor according to the curvature of each target point and obtains a weight factor matrix;
a tracking error calculator (3.2) calculates a velocity tracking error matrix between all the desired velocity vectors and the current velocity vector;
the optimal acceleration decision device (3.4) is used for carrying out acceleration decision by taking the minimized error as a control target according to the weight coefficient matrix and the speed tracking error matrix to obtain the optimal longitudinal acceleration and the optimal transverse acceleration of the vehicle;
and the execution control module (4) is used for obtaining the expected optimal longitudinal acceleration and lateral acceleration for tracking by controlling the steering wheel angle, the accelerator pedal opening and the brake pedal opening.
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CN114590274B (en) * 2022-03-25 2023-03-24 奥特酷智能科技(南京)有限公司 Path planning method for driving assistance system and driving assistance system
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CN114906173B (en) * 2022-06-30 2023-07-21 电子科技大学 Automatic driving decision method based on two-point pre-aiming driver model

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103754224A (en) * 2014-01-24 2014-04-30 清华大学 Vehicle multi-target coordinating lane changing assisting adaptive cruise control method
CN107521496A (en) * 2017-09-08 2017-12-29 吉林大学 A kind of transverse and longitudinal of vehicle coordinates control track follow-up control method
CN109144076A (en) * 2018-10-31 2019-01-04 吉林大学 A kind of more vehicle transverse and longitudinals coupling cooperative control system and control method
CN111427260A (en) * 2019-01-10 2020-07-17 广州汽车集团股份有限公司 Control method, device, controller and system for vehicle path tracking and vehicle
CN112937580A (en) * 2019-11-25 2021-06-11 郑州宇通客车股份有限公司 Target path tracking method and device
CN113085858A (en) * 2021-04-27 2021-07-09 湖北文理学院 Vehicle speed tracking control method, device, equipment and storage medium

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210094569A1 (en) * 2019-09-27 2021-04-01 Honda Motor Co., Ltd. System and method for providing accurate trajectory following for automated vehicles in dynamic environments

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103754224A (en) * 2014-01-24 2014-04-30 清华大学 Vehicle multi-target coordinating lane changing assisting adaptive cruise control method
CN107521496A (en) * 2017-09-08 2017-12-29 吉林大学 A kind of transverse and longitudinal of vehicle coordinates control track follow-up control method
CN109144076A (en) * 2018-10-31 2019-01-04 吉林大学 A kind of more vehicle transverse and longitudinals coupling cooperative control system and control method
CN111427260A (en) * 2019-01-10 2020-07-17 广州汽车集团股份有限公司 Control method, device, controller and system for vehicle path tracking and vehicle
CN112937580A (en) * 2019-11-25 2021-06-11 郑州宇通客车股份有限公司 Target path tracking method and device
CN113085858A (en) * 2021-04-27 2021-07-09 湖北文理学院 Vehicle speed tracking control method, device, equipment and storage medium

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