CN117465479A - Transverse control method for automatic driving vehicle - Google Patents

Transverse control method for automatic driving vehicle Download PDF

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Publication number
CN117465479A
CN117465479A CN202311291301.XA CN202311291301A CN117465479A CN 117465479 A CN117465479 A CN 117465479A CN 202311291301 A CN202311291301 A CN 202311291301A CN 117465479 A CN117465479 A CN 117465479A
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Prior art keywords
vehicle
state
vehicle speed
lane line
front wheel
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Pending
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CN202311291301.XA
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Chinese (zh)
Inventor
孙永厚
杨音文
刘夫云
邓聚才
王天明
郁宛
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Guilin University of Electronic Technology
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Guilin University of Electronic Technology
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Priority to CN202311291301.XA priority Critical patent/CN117465479A/en
Publication of CN117465479A publication Critical patent/CN117465479A/en
Pending legal-status Critical Current

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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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18145—Cornering
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62D—MOTOR VEHICLES; TRAILERS
    • B62D15/00—Steering not otherwise provided for
    • B62D15/02—Steering position indicators ; Steering position determination; Steering aids
    • B62D15/021—Determination of steering angle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62D—MOTOR VEHICLES; TRAILERS
    • B62D6/00—Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits
    • B62D6/002—Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits computing target steering angles for front or rear wheels
    • B62D6/003—Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits computing target steering angles for front or rear wheels in order to control vehicle yaw movement, i.e. around a vertical axis
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0031—Mathematical model of the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/53—Road markings, e.g. lane marker or crosswalk
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/20—Steering systems

Abstract

The invention relates to the technical field of automatic driving vehicle control, in particular to a transverse control method for an automatic driving vehicle. According to the invention, an offline table look-up mode is adopted, LQR feedback gain coefficients under different speeds are directly obtained from a vehicle speed feedback gain coefficient table through a table look-up method, a feedback front wheel rotation angle is determined by the LQR feedback gain coefficients and an error variable, a self-adaptive feedforward controller is adopted to determine a feedforward front wheel rotation angle, and an expected steering wheel rotation angle is obtained through the feedforward front wheel rotation angle and the feedback front wheel rotation angle, so that the transverse control of the vehicle is realized, the tracking precision is higher, and compared with a traditional control algorithm, the calculation speed is improved.

Description

Transverse control method for automatic driving vehicle
Technical Field
The invention relates to the technical field of automatic driving vehicle control, in particular to a transverse control method for an automatic driving vehicle.
Background
The world is entering an intelligent age, the automobile industry is developing at a high speed, the intelligent driving function is becoming popular, the running safety problem of vehicles is becoming more prominent, and the transverse control of the vehicles, namely lane keeping, is one of the most important functions of intelligent driving. The control effect of the control device can influence the comfort and stability of the whole vehicle.
In the existing transverse control technology, a pretightening control algorithm is more used, but the selection of pretightening points is more fuzzy; and the restriction of the dynamics of the vehicle is not considered, so that the control system is unstable when the vehicle is in a limit working condition, and the stable running of the vehicle is influenced. There are also some technologies that consider constraints of vehicle dynamics, such as LQR and MPC algorithms, where a conventional LQR algorithm needs to construct a licarpi equation to calculate its feedback matrix in an actual calculation process, and there is a certain amount of calculation.
Disclosure of Invention
The invention aims to provide a transverse control method for an automatic driving vehicle, which aims to solve the technical problems of high dependence on a high-performance controller and long calculation time consumption of the control algorithm of the conventional transverse control technology for automatic driving and ensure the transverse control precision and the running stability of the vehicle.
To achieve the above object, the present invention provides a lateral control method for an autonomous vehicle, comprising the steps of:
acquiring vehicle state information and lane line information, and determining lane center line information according to the lane line information;
determining an error variable of the vehicle from the vehicle state information and the lane centerline information;
establishing a two-degree-of-freedom dynamics model, and determining a state space equation by the two-degree-of-freedom dynamics model;
determining a vehicle speed feedback gain coefficient table by a state space equation and an LQR controller;
determining a feedback gain coefficient corresponding to the actual vehicle speed according to the vehicle speed and the feedback gain coefficient table, further solving a feedback front wheel corner, and obtaining the feedforward front wheel corner according to a state space equation, the vehicle speed and the curvature of the lane center line;
the desired steering wheel angle is determined by the feedforward front wheel angle and the feedback front wheel angle, and the transverse control of the vehicle is realized by controlling the steering wheel.
Optionally, the lane line information is obtained from the vehicle-mounted camera and comprises lane line quality Q, a distance C0 from the vehicle to the lane line, a yaw angle C1 of the vehicle and a road curvature C2, wherein the lane line quality Q is expressed as 1,2 and 3 from low to high, lane line center line information is output by the information of the left lane line and the right lane line, the lane line center line information is divided into 3 states according to different qualities of the left lane line and the right lane line, and the lane center line information is oriented differently in different states.
Optionally, when the left lane line quality Q_L is more than or equal to 2 and the right lane line quality Q_R is more than or equal to 2, the state 1 is set; when only Q_L is more than or equal to 2, the state is 2; when only Q_R is more than or equal to 2, the state is 3; when q_r, q_l are both less than 2, the driver is required to acquire the current vehicle state information:
in the case of the state 1, the state,
in the case of the state 2, the state,
in the case of the state 3, the state,
wherein the lane center line information includes a lateral deviation A of the lane center line 0 Course angle deviation A 1 And road curvature A 2 C0_l, c1_l, c2_l are left lane line information, c0_r, c1_r, c2_r are right lane line information.
Optionally, the error variable of the vehicle includes a lateral error y, a lateral error rate of changeCourse angle error->And course angle error rate +.>Wherein is shown as A 0 As the lateral error y, A 2 As heading angle error phi, the lateral error rate of changeCourse angle error rate +.>V in x And W is r The vehicle speed and yaw rate, respectively, are vehicle state information, and k is road curvature.
Optionally, the two-degree-of-freedom dynamics model is obtained by simplifying a two-wheel model for a vehicle model, and the expression is:
in the method, in the process of the invention,for the lateral acceleration of the vehicle, +.>For yaw angle of vehicleAcceleration, m is the mass of the vehicle, C αf 、C αr The rigidity is the cornering stiffness of the front wheel and the rear wheel respectively, I is the rotational inertia of the vehicle body around the z axis, a is the distance from the front axis to the mass center, and b is the distance from the rear axis to the mass center.
Optionally, the feedback gain coefficient in the vehicle speed feedback gain coefficient table is related to the vehicle speed, different vehicle speeds correspond to different feedback gain coefficients, and the vehicle speed feedback gain coefficient table is off-line calculation, so that the actual calculation time is not occupied.
Optionally, the obtaining process of the vehicle speed feedback gain coefficient table specifically includes that the self-defined vehicle speed value is set to be 1-50 m/s, the vehicle speed step length is set to be 0.1, the value of a defined variable i is set to be 1-500, the cycle calculation is carried out for 500 times by combining lqr functions in a computer, the vehicle speed in each cycle calculation is set to be 0.1 x i, and after the cycle is finished, the vehicle speed feedback gain coefficient table with the vehicle speed within the range of 1-50 m/s can be obtained, and the table size is 500X4.
Optionally, the lateral control of the vehicle is achieved by controlling the steering wheel angle, where the desired steering wheel angle is determined by the front wheel angle and the steering ratio coefficient, θ=j×δ, where δ is the final front wheel angle, θ is the desired steering wheel angle, and j is the steering ratio coefficient.
The invention provides a transverse control method for an automatic driving vehicle, which comprises the steps of obtaining vehicle state information and lane line information, determining lane central line information, determining vehicle error variables based on the vehicle state information and the lane central line information, wherein the error variables comprise transverse errors, transverse error change rates, course angle errors and course angle error change rates, determining a desired steering wheel angle of the vehicle according to the error variables, and further transversely controlling the vehicle. According to the invention, an offline table look-up mode is adopted, LQR feedback gain coefficients under different speeds are directly obtained from a vehicle speed feedback gain coefficient table through a table look-up method, a feedback front wheel rotation angle is determined by the LQR feedback gain coefficients and an error variable, a self-adaptive feedforward controller is adopted to determine a feedforward front wheel rotation angle, and an expected steering wheel rotation angle is obtained through the feedforward front wheel rotation angle and the feedback front wheel rotation angle, so that the transverse control of the vehicle is realized, the tracking precision is higher, and compared with a traditional control algorithm, the calculation speed is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of the steps of a lateral control method for an autonomous vehicle according to the present invention.
FIG. 2 is a schematic diagram of a linear two-degree-of-freedom model of the vehicle of the present invention.
FIG. 3 is a schematic diagram of a desired steering wheel angle calculation process according to the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention.
Referring to fig. 1, the present invention provides a lateral control method for an autonomous vehicle, comprising the steps of:
s1: acquiring vehicle state information and lane line information, and determining lane center line information according to the lane line information;
s2: determining an error variable of the vehicle from the vehicle state information and the lane centerline information;
s3: establishing a two-degree-of-freedom dynamics model, and determining a state space equation by the two-degree-of-freedom dynamics model;
s4: determining a vehicle speed feedback gain coefficient table by a state space equation and an LQR controller;
s5: determining a feedback gain coefficient corresponding to the actual vehicle speed according to the vehicle speed and the feedback gain coefficient table, further solving a feedback front wheel corner, and obtaining the feedforward front wheel corner according to a state space equation, the vehicle speed and the curvature of the lane center line;
s6: the desired steering wheel angle is determined by the feedforward front wheel angle and the feedback front wheel angle, and the transverse control of the vehicle is realized by controlling the steering wheel.
Further, the following is further described in connection with the specific implementation steps:
in step S1, the state information of the vehicle may be acquired through a vehicle body CAN bus, such as a vehicle speed Vx and a yaw rate Wr; lane line information is obtained from an onboard camera, such as lane line quality Q, distance from the vehicle to the lane line C0, yaw angle of the vehicle C1, road curvature C2.
The quality Q of the lane lines output by the sensor is 1,2 and 3, the quality of the lane lines is expressed from low to high, the information of the lane center lines can be output by the information of the left lane line and the right lane line, the information of the lane center lines is divided into 3 states according to the different quality of the left lane line and the right lane line, and the information orientation of the lane center lines is different under the different states.
Different lane line types are divided according to the lane line quality. The lane line quality output by the sensor is divided into 1,2 and 3 from low to high, the quality of the lane line is represented, and when the left lane line quality (Q_L) is more than or equal to 2 and the right lane line quality (Q_R) is more than or equal to 2, the state is 1; when only Q_L is more than or equal to 2, the state is 2; when only Q_R is more than or equal to 2, the state is 3; when q_r, q_l are both less than 2, the driver's current vehicle state is required.
In the case of the state 1, the state,
in the case of the state 2, the state,A 1 ＝C1_L,/>
in the case of the state 3, the state,A 1 ＝C1_R，/>
in the above equation, A0, A1, A2 are the lateral deviation, heading angle deviation, and road curvature of the lane center line, respectively, as the lane center line information; c0_l, c1_l, c2_l are left lane line information, c0_r, c1_r, c2_r are right lane line information.
Step S2: determining error variables of the vehicle according to the vehicle state information and the lane central line information, wherein the error variables comprise transverse errors, transverse error change rates, course angle errors and course angle error change rates; taking A0 as a transverse error y and A2 as a heading angle error phi.
Rate of change of lateral errorDetermined by the speed and heading angle error, +.>
Course angle error rate of changeDetermined by yaw rate, vehicle speed and road curvature +.>Where k is the road curvature.
Step S3: and establishing a two-degree-of-freedom dynamics model, and determining a state space equation by the two-degree-of-freedom dynamics model. Specifically, the invention obtains a two-wheel vehicle model through simplifying the vehicle model; the linear two-degree-of-freedom model of the vehicle is shown in FIG. 2, G is the centroid of the vehicle, β is the centroid slip angle, δ is the front wheel steering angle, α f Is the front wheel slip angle alpha r For the rear wheel slip angle, L is the wheelbase, a is the distance from the front axle to the mass center, b is the distance from the rear axle to the mass centerDistance of heart, fy f 、Fy r Is a side reaction force facing the front and rear wheels.
From fig. 2, a system of equations can be derived:
ma y ＝Fy f cosδ+Fy r ；
the two-degree-of-freedom dynamics model can be obtained after the deduction and simplification of the above formula:
wherein,for the lateral acceleration of the vehicle, +.>The yaw acceleration of the vehicle, m is the mass of the vehicle, C αf 、C αr The rigidity of the front wheel and the rear wheel is respectively cornering, and I is the rotational inertia of the vehicle body around the z axis.
Further, a vehicle lateral control model is determined from the two-degree-of-freedom model:
where k is the road curvature, the system state variables will be defined asThe vehicle lateral control model is expressed by the following state space equation:
wherein the matrix of the system
Step S4: a vehicle speed feedback gain coefficient table is determined by a state space equation and an LQR controller. A vehicle speed feedback gain coefficient table is determined by the A, B matrix of the state space equation and the LQR controller function (LQR function in the computer), the feedback gain coefficient is related to the vehicle speed, and different vehicle speeds correspond to different feedback gain coefficients.
The self-defined vehicle speed is set to be 1-50 m/s, the vehicle speed step length is set to be 0.1, the value of a defined variable i is set to be 1-500, the cycle calculation is carried out for 500 times by combining a lqr function in a computer, the vehicle speed in each cycle calculation is set to be 0.1 x i, and after the cycle is finished, a vehicle speed feedback gain coefficient table with the vehicle speed in the range of 1-50 m/s can be obtained, wherein the table size is 500X4.
It should be noted that the vehicle speed feedback gain coefficient table is well calculated offline, and does not occupy calculation time in the calculation process of the actual control algorithm, that is, the step S3 and the step S4 do not occupy actual calculation time in practice, so that the transverse control efficiency is improved.
Step S5: and determining a feedback gain coefficient corresponding to the actual vehicle speed according to the vehicle speed and the feedback gain coefficient table, further solving a feedback front wheel corner, and obtaining the feedforward front wheel corner according to a state space equation, the vehicle speed and the curvature of the lane center line. According to the vehicle speed feedback gain coefficient table and the real-time vehicle speed, determining a feedback gain coefficient corresponding to the actual vehicle speed in a table look-up mode, wherein the feedback front wheel rotation angle can be determined by the following formula:
δ b ＝-K*x；
wherein delta b For feeding back the front wheel rotation angle, K is the practically corresponding feedback gain coefficient, and x is the system state variable.
Further, a feedforward controller is designed through a state space equation, a front wheel corner is obtained through the feedforward controller, and if the transverse control is realized by adopting a mode of combining feedforward and feedback, the following steps are provided: delta=delta f +u, in combination with the state space equation in S3, can be given by:
wherein,obviously, the characteristics of the matrixes B1 and B2 determine that B cannot be caused 1 δ f +B 2 k=0, assuming that the feedforward controller can let +.>The feed forward deviation of (2) is 0, which can be obtained:
further, a feedforward controller is obtained:wherein delta f The front-feed wheel corner is the front-feed wheel corner, and k is the road curvature, namely the curvature of the lane center line.
Step S6: the desired steering wheel angle is determined by the feedforward front wheel angle and the feedback front wheel angle, and the transverse control of the vehicle is realized by controlling the steering wheel. As shown in fig. 3, which is a flowchart of calculating the desired steering wheel angle, the step S5 is to calculate the feedback front wheel angle delta b And feed-forward front wheel angle delta f After that, the final front wheel rotation angle δ=δ is determined b +δ f ；
In the actual control process, the transverse control of the vehicle can be realized only by controlling the steering wheel angle, the expected steering wheel angle is determined by the front wheel angle and the steering ratio coefficient, and θ=j=δ, wherein θ is the expected steering wheel angle, and j is the steering ratio coefficient.
The above disclosure is only a preferred embodiment of the present invention, and it should be understood that the scope of the invention is not limited thereto, and those skilled in the art will appreciate that all or part of the procedures described above can be performed according to the equivalent changes of the claims, and still fall within the scope of the present invention.

Claims (8)

1. A lateral control method for an autonomous vehicle, comprising the steps of:
acquiring vehicle state information and lane line information, and determining lane center line information according to the lane line information;
determining an error variable of the vehicle from the vehicle state information and the lane centerline information;
establishing a two-degree-of-freedom dynamics model, and determining a state space equation by the two-degree-of-freedom dynamics model;
determining a vehicle speed feedback gain coefficient table by a state space equation and an LQR controller;
determining a feedback gain coefficient corresponding to the actual vehicle speed according to the vehicle speed and the feedback gain coefficient table, further solving a feedback front wheel corner, and obtaining the feedforward front wheel corner according to a state space equation, the vehicle speed and the curvature of the lane center line;
the desired steering wheel angle is determined by the feedforward front wheel angle and the feedback front wheel angle, and the transverse control of the vehicle is realized by controlling the steering wheel.
2. A lateral control method for an autonomous vehicle as claimed in claim 1, characterized in that,
the lane line information is obtained from the vehicle-mounted camera and comprises lane line quality Q, a distance C0 from a vehicle to a lane line, a yaw angle C1 of the vehicle and a road curvature C2, wherein the lane line quality Q is expressed as 1,2 and 3 from low to high, lane line central line information is output by the information of the left lane line and the right lane line, the lane central line information is divided into 3 states according to different qualities of the left lane line and the right lane line, and the orientation of the lane central line information is different under different states.
3. A lateral control method for an autonomous vehicle as claimed in claim 2, characterized in that,
when the left lane line quality Q_L is more than or equal to 2 and the right lane line quality Q_R is more than or equal to 2, the state 1 is set; when only Q_L is more than or equal to 2, the state is 2; when only Q_R is more than or equal to 2, the state is 3; when q_r, q_l are both less than 2, the driver is required to acquire the current vehicle state information:
in the case of the state 1, the state,
in the case of the state 2, the state,A 1 ＝C1_L,/>
in the case of the state 3, the state,A 1 ＝C1_R，/>
wherein the lane center line information includes a lateral deviation A of the lane center line 0 Course angle deviation A 1 And road curvature A 2 C0_l, c1_l, c2_l are left lane line information, c0_r, c1_r, c2_r are right lane line information.
4. A lateral control method for an autonomous vehicle as claimed in claim 3, characterized in that,
the error variables of the vehicle include the lateral error y and the lateral error change rateCourse angle error->And course angle error rate +.>Wherein is shown as A 0 As the lateral error y, A 2 As heading angle error phi, the lateral error rate of change +.>Course angle error rate +.>V in s And W is r The vehicle speed and yaw rate, respectively, are vehicle state information, and k is road curvature.
5. The lateral control method for an autonomous vehicle as claimed in claim 4, wherein,
the two-degree-of-freedom dynamics model is obtained by simplifying a two-wheel model for a vehicle model, and the expression is as follows:
in the method, in the process of the invention,for the lateral acceleration of the vehicle, +.>The yaw acceleration of the vehicle, m is the mass of the vehicle, C αf 、C αr Respectively the cornering stiffness of the front wheel and the rear wheel, wherein I is the moment of inertia of the vehicle body around the z axis, and a is the front axis to the mass centerB is the distance from the rear axis to the centroid.
6. The lateral control method for an autonomous vehicle as claimed in claim 5, wherein,
the feedback gain coefficients in the vehicle speed feedback gain coefficient table are related to the vehicle speed, different vehicle speeds correspond to different feedback gain coefficients, and the vehicle speed feedback gain coefficient table is calculated offline and does not occupy actual calculation time.
7. The lateral control method for an autonomous vehicle as claimed in claim 6, wherein,
the acquisition process of the vehicle speed feedback gain coefficient table specifically comprises the steps of setting a self-defined vehicle speed value to be 1-50 m/s, taking a vehicle speed step length to be 0.1, defining a variable i value to be 1-500, carrying out cycle calculation for 500 times by combining a lqr function in a computer, wherein the vehicle speed in each cycle calculation is 0.1X i, and obtaining the vehicle speed feedback gain coefficient table with the vehicle speed within the range of 1-50 m/s after the cycle is finished, wherein the table size is 500X4.
8. The lateral control method for an autonomous vehicle as claimed in claim 7, wherein,
the transverse control of the vehicle is realized by controlling the steering wheel angle, the expected steering wheel angle is determined by the front wheel angle and the steering ratio coefficient, and θ=j×δ, wherein δ is the final front wheel angle, θ is the expected steering wheel angle, and j is the steering ratio coefficient.
CN202311291301.XA 2023-10-08 2023-10-08 Transverse control method for automatic driving vehicle Pending CN117465479A (en)

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Application Number Priority Date Filing Date Title
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Publications (1)

Publication Number Publication Date
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