CN115214715A - Lateral control method and control device for automatic driving of vehicle and vehicle - Google Patents
Lateral control method and control device for automatic driving of vehicle and vehicle Download PDFInfo
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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
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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
- 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
- B60W30/18—Propelling the vehicle
- B60W30/18009—Propelling the vehicle related to particular drive situations
- B60W30/18145—Cornering
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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
- 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
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- B60W2520/00—Input parameters relating to overall vehicle dynamics
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
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- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/12—Lateral speed
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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
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Abstract
The invention discloses a lateral control method and a control device for automatic driving of a vehicle, and the vehicle, wherein the method comprises the following steps: acquiring current running state information of a vehicle, wherein the current state information of the vehicle comprises: a current lateral acceleration and a current yaw angular acceleration; determining planning point information at the next moment according to the current transverse acceleration and the current yaw angular acceleration; and determining error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the next-time planning point information, and adjusting the front wheel steering angle of the vehicle according to the error information of the vehicle so as to enable the running state information of the vehicle to meet the preset condition. The transverse control method can improve the control precision of the automatic driving of the vehicle and enable the automatic driving vehicle to be closer to a planned track when steering.
Description
Technical Field
The present invention relates to the field of vehicle automatic driving technologies, and in particular, to a lateral control method for vehicle automatic driving, a lateral control apparatus for vehicle automatic driving, a vehicle, and a computer-readable storage medium.
Background
The transverse control of the automatic driving of the vehicle is one of three cores of the technology, and the transverse control outputs a corresponding steering control instruction according to the target path information of an upper-layer decision planning system to control the vehicle to run along the target path. The transverse control method is the core of the whole motion control system, and the advantages and disadvantages of the transverse control method not only influence the tracking precision of the intelligent automobile on the target path, but also influence the stability, comfort and the like of the whole automobile.
In the conventional lateral control technology, there are two methods, i.e., a predictive model and a non-predictive model. For the method without a prediction model, the control algorithm cannot be applied to the controller in time due to the hysteresis problem of a physical system, the tracking effect is poor, and the control input quantity has obvious mutation. For the control method with the prediction model, certain errors exist when the position of the vehicle is estimated, the judgment of the aiming point is not accurate, and the prediction result has deviation.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art. Therefore, a first object of the present invention is to provide a lateral control method for vehicle automatic driving, which can improve the control accuracy during vehicle automatic driving and make the automatic driving vehicle closer to a planned trajectory during steering.
A second object of the invention is to propose a lateral control device for automatic driving of a vehicle.
A third object of the invention is to propose a vehicle.
A fourth object of the invention is to propose a computer-readable storage medium.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides a lateral control method for automatic driving of a vehicle, including: acquiring current running state information of a vehicle, wherein the current state information of the vehicle comprises: a current lateral acceleration and a current yaw angular acceleration; determining planning point information at the next moment according to the current transverse acceleration and the current yaw angular acceleration; and determining error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the next moment of planning point information, and adjusting the front wheel steering angle of the vehicle according to the error information of the vehicle so as to enable the running state information of the vehicle to meet the preset condition.
According to the transverse control method for the automatic driving of the vehicle, the current running state information of the vehicle is obtained, wherein the current state information of the vehicle comprises the following steps: a current lateral acceleration and a current yaw angular acceleration; determining planning point information at the next moment according to the current transverse acceleration and the current yaw angular acceleration; and determining error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the next-time planning point information, and adjusting the front wheel steering angle of the vehicle according to the error information of the vehicle so as to enable the running state information of the vehicle to meet the preset condition. Therefore, the method can improve the control precision of the automatic driving of the vehicle and enable the automatic driving vehicle to be closer to the planned track when the automatic driving vehicle turns.
In addition, the lateral control method for automatic driving of a vehicle according to the above embodiment of the present invention may further have the following additional technical features:
according to one embodiment of the invention, determining the planning point information of the next moment according to the current lateral acceleration and the current yaw acceleration comprises: and obtaining planning point information of the next moment by adopting a preview model according to the current transverse acceleration and the current yaw angular acceleration, wherein the planning point information comprises: the longitudinal coordinate of the planned point at the next moment of the vehicle, the transverse coordinate of the planned point at the next moment of the vehicle and the yaw angle of the planned point at the next moment of the vehicle.
According to one embodiment of the invention, the preview model is expressed using the following formula:
wherein x is p Longitudinal coordinate, y, representing the planned point at the next moment of the vehicle p The lateral coordinates of the planned point representing the next moment of the vehicle,
representing the yaw angle of a planned point at the next moment of the vehicle, x representing the longitudinal coordinate of the current moment of the vehicle, y representing the lateral coordinate of the current moment of the vehicle, v x Indicating the longitudinal speed, v, of the vehicle at the present moment y Indicating the lateral speed, t, of the vehicle at the present moment a Which represents the length of the prediction time period,
representing the yaw angle of the vehicle at the present moment, a x Representing the current longitudinal acceleration of the vehicle, a y Represents the current lateral acceleration of the vehicle,
represents the current yaw-rate of the vehicle,
representing the current yaw acceleration of the vehicle.
According to one embodiment of the present invention, adjusting a front wheel steering angle of a vehicle according to error information of the vehicle includes: determining a feedforward front wheel corner and a feedback front wheel corner of the vehicle according to the error information of the vehicle; and determining a front wheel steering angle adjusting value of the vehicle according to the feedforward front wheel steering angle and the feedback front wheel steering angle so as to adjust the front wheel steering angle of the vehicle.
According to an embodiment of the present invention, after determining the front wheel steering angle adjustment value of the vehicle, the above lateral control method for vehicle automatic driving further includes: performing analog simulation according to the front wheel steering angle adjustment value of the vehicle to determine the actual front wheel steering angle of the vehicle; and acquiring the current running state information of the vehicle by adopting a two-degree-of-freedom dynamic model according to the actual front wheel steering angle of the vehicle.
According to one embodiment of the present invention, determining a feed-forward front wheel steering angle and a feedback front wheel steering angle of a vehicle based on error information of the vehicle includes: determining a feedback front wheel corner of the vehicle by adopting a Linear Quadratic Regulator (LQR) feedback control model according to the error information of the vehicle; and determining the feedforward front wheel rotation angle of the vehicle by adopting a feedforward control model according to the error information of the vehicle.
According to an embodiment of the present invention, the lateral control method for automatic driving of a vehicle described above further includes: and when the running state information of the vehicle does not meet the preset condition, adjusting the predicted time length in the preview model and the parameters of the LQR feedback control model so as to enable the error information of the vehicle to be within a preset range.
According to one embodiment of the present invention, determining error information of a vehicle according to a current lateral acceleration, a current yaw acceleration and planned point information at a next time comprises: establishing a corresponding error model according to a two-degree-of-freedom dynamic model of the vehicle; and taking the current lateral acceleration, the current yaw angular acceleration and the planning point information at the next moment as the input of an error model to obtain the error information of the vehicle.
In order to achieve the above object, a second aspect of the present invention provides a lateral control device for automatic driving of a vehicle, including: the acquiring module is used for acquiring the current running state information of the vehicle, wherein the current state information of the vehicle comprises: a current lateral acceleration and a current yaw angular acceleration; the first determining module is used for determining planning point information at the next moment according to the current transverse acceleration and the current yaw angular acceleration; and the second determining module is used for determining error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the next-moment planning point information, and adjusting the front wheel steering angle of the vehicle according to the lateral position error of the vehicle and the heading angular error of the vehicle so as to enable the running state information of the vehicle to meet the preset condition.
According to the lateral control device for the automatic driving of the vehicle, the obtaining module obtains the current running state information of the vehicle, the first determining module determines the planning point information at the next moment according to the current lateral acceleration and the current yaw angular acceleration, the second determining module determines the error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the planning point information at the next moment, and the front wheel rotation angle of the vehicle is adjusted according to the lateral position error of the vehicle and the heading angular error of the vehicle, so that the running state information of the vehicle meets the preset condition. Therefore, the device can improve the control precision of the automatic driving of the vehicle and enable the automatic driving vehicle to be closer to the planned track when the automatic driving vehicle turns.
In order to achieve the above object, a third aspect of the present invention provides a vehicle, including a memory, a processor, and a lateral control program for vehicle automatic driving, stored in the memory and operable on the processor, wherein the processor implements the lateral control method for vehicle automatic driving when executing the lateral control program for vehicle automatic driving.
According to the vehicle provided by the embodiment of the invention, by executing the transverse control method for automatic driving of the vehicle, the control precision during automatic driving of the vehicle can be improved, and the automatic driving vehicle is enabled to be closer to a planned track during steering.
In order to achieve the above object, a fourth aspect of the present invention provides a computer-readable storage medium having a lateral control program for vehicle autonomous driving stored thereon, which when executed by a processor implements the above lateral control method for vehicle autonomous driving.
According to the computer-readable storage medium of the embodiment of the invention, by executing the transverse control method for automatic driving of the vehicle, the control precision of the automatic driving of the vehicle can be improved, and the automatic driving vehicle can be closer to a planned track when turning.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
Fig. 1 is a flowchart of a lateral control method of automatic driving of a vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic illustration of a two-degree dynamics model of a vehicle according to one embodiment of the invention;
FIG. 3 is a block schematic diagram of a vehicle lateral control system according to one embodiment of the present invention;
FIG. 4 is a block diagram representation of a vehicle lateral control system including a predictive model in accordance with one embodiment of the present invention;
FIG. 5 is a block schematic diagram of a lateral control device for vehicle autopilot according to an embodiment of the present invention;
FIG. 6 is a block schematic diagram of a vehicle according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
A lateral control method of vehicle autopilot, a lateral control apparatus of vehicle autopilot, a vehicle, and a computer-readable storage medium according to an embodiment of the invention are described below with reference to the drawings.
In the related art, the lateral control of the automatic driving of the vehicle mainly includes two control methods, i.e., a non-prediction model and a linear prediction model. The control method without the prediction model takes various information of the current position of the vehicle as control input at the next moment, the response of the system lags behind the application time of the current control quantity due to the limitation of a physical environment, and the shortening of the controllable time needs larger input quantity for compensation, so that larger control quantity jump can occur in the operation process of the algorithm. The control method of the linear prediction model is that the current speed and the yaw velocity are used as solving signals of a pre-aiming point, the corresponding position and the yaw angle of a planned path where the pre-aiming point is located are obtained according to the signals, and the steering wheel turning angle quantity and the throttle/brake control quantity which are required to be applied by a vehicle are reversely deduced, but the model has poor prediction precision, cannot make correct response to the acceleration working condition of the vehicle, and the prediction result has certain deviation.
Aiming at the problems that a linear prediction model is poor in control accuracy and cannot make correct response to the vehicle acceleration working condition, the invention provides a lateral control method for vehicle automatic driving, which introduces a vehicle linear acceleration signal and a yaw angular acceleration signal as supplementary signals, more accurately controls an actual position vector, a speed vector and an angular velocity vector of a pre-aiming point, can effectively improve the automatic driving control accuracy and enables an automatically driven vehicle to be closer to a planned track when the vehicle is turned.
Fig. 1 is a flowchart of a lateral control method of vehicle autonomous driving according to an embodiment of the present invention.
As shown in fig. 1, the lateral control method for vehicle automatic driving according to the embodiment of the present invention may include the steps of:
s1, acquiring current running state information of a vehicle, wherein the current state information of the vehicle comprises: the current lateral acceleration and the current yaw acceleration.
In an embodiment of the present invention, the vehicle has an ADAS (Advanced Driving Assistance System) System, and during automatic Driving of the vehicle, the ADAS System may monitor the current wheel speed information, lateral and longitudinal acceleration, yaw rate, yaw acceleration, accelerator opening, brake pedal information, etc. of the vehicle in real time, and transmit the vehicle operating state information to the automatic Driving control System of the vehicle through a vehicle body bus signal.
And S2, determining planning point information at the next moment according to the current transverse acceleration and the current yaw angular acceleration.
According to one embodiment of the invention, determining the planning point information of the next moment according to the current lateral acceleration and the current yaw acceleration comprises: and obtaining planning point information of the next moment by adopting a preview model according to the current transverse acceleration and the current yaw angular acceleration, wherein the planning point information comprises: the longitudinal coordinate of the planned point at the next moment of the vehicle, the transverse coordinate of the planned point at the next moment of the vehicle and the yaw angle of the planned point at the next moment of the vehicle.
Further, according to an embodiment of the present invention, the preview model is expressed by the following formula:
wherein x is p Longitudinal coordinate, y, representing the planned point at the next moment of the vehicle p The lateral coordinates of the planned point representing the next moment of the vehicle,
representing the yaw angle of a planned point at the next moment of the vehicle, x representing the longitudinal coordinate of the current moment of the vehicle, y representing the lateral coordinate of the current moment of the vehicle, v x Indicating the longitudinal speed, v, of the vehicle at the present moment y Indicating the lateral speed, t, of the vehicle at the present moment a Which represents the length of the prediction time period,
representing the yaw angle of the vehicle at the present moment, a x Representing the current longitudinal acceleration of the vehicle, a y Represents the current lateral acceleration of the vehicle,
represents the current yaw-rate of the vehicle,
representing the current yaw acceleration of the vehicle.
Specifically, the current lateral acceleration and the current yaw acceleration acquired in step S1, and the longitudinal and lateral coordinates, the longitudinal and lateral velocity, the longitudinal and lateral acceleration, the yaw angle, and the like of the vehicle at the current time are substituted into the above formulas, and planning point information (preview point information) at the next time, that is, the longitudinal coordinate x of the planning point at the next time of the vehicle, is obtained by calculation p Transverse coordinate y p Sum yaw angle
And S3, determining error information of the vehicle according to the current transverse acceleration, the current yaw angular acceleration and planning point information at the next moment, and adjusting the front wheel rotation angle of the vehicle according to the error information of the vehicle so as to enable the running state information of the vehicle to meet the preset condition.
According to one embodiment of the present invention, determining error information of a vehicle according to a current lateral acceleration, a current yaw acceleration, and planned point information at a next time comprises: establishing a corresponding error model according to a two-degree-of-freedom dynamic model of the vehicle; and taking the current lateral acceleration, the current yaw angular acceleration and the planning point information at the next moment as the input of an error model to obtain the error information of the vehicle.
Specifically, the two-degree-of-freedom vehicle dynamic model ignores the effect of the vehicle suspension, simplifies the whole vehicle into two wheels, considers that the tire cornering characteristic is linear, ignores the longitudinal driving or resistance, considers that the longitudinal vehicle speed is constant, and finally the linear two-degree-of-freedom vehicle dynamic model can be represented as shown in fig. 2. In FIG. 2, CG is the center of mass of the entire vehicle, MP is the instant center of motion, and F yf Is the lateral force of the front shaft; f yr For rear axle lateral forces, α f Is the front axle slip angle, α r Is the rear axle slip angle, v f Is the front wheel speed, v r Is the rear wheel speed, v is the vehicle center of mass speed,
is a yaw angle,/ f Is the distance of the center of mass to the front axis, l r The distance from the center of mass to the rear axle, l is the wheelbase, β is the center of mass slip angle, and δ is the actual front wheel rotation angle.
From fig. 2, the following system of equations can be obtained:
ma y ＝F yf +F yr
the equation set is deduced, and the expression of the two-degree-of-freedom dynamic model can be obtained as follows:
wherein, the first and the second end of the pipe are connected with each other,
is the lateral acceleration of the vehicle and,
is the yaw angular acceleration of the vehicle, m is the mass of the vehicle, C αf For front axle yaw stiffness, C αr For rear axle yaw stiffness, I Z Is the moment of inertia of the vehicle body around the Z axis.
Further, the above dynamic model is derived to obtain a corresponding error model, which can be expressed by the following formula:
wherein e is n Is the lateral position error;
the error is the error of the course angle,
in order to be a lateral velocity error,
in order to be a lateral acceleration error,
in order to determine the error in the course angular velocity,
as angular acceleration error of course，
The course angular speed is represented, and since the course angle is the sum of the slip angle and the yaw angle, and the slip angle is very small and is almost zero, the course angle is approximate to the yaw angle, and the course angular speed is regarded as the yaw angular speed.
The error information of the vehicle can be obtained by using the current lateral acceleration and the current yaw acceleration obtained in step S1 and the planned point information at the next time obtained in step S2 as inputs of the error model. Wherein the error information can be represented by an error matrix e e And (4) showing.
According to one embodiment of the invention, adjusting the front wheel steering angle of the vehicle according to the error information of the vehicle comprises: determining a feedforward front wheel corner and a feedback front wheel corner of the vehicle according to the error information of the vehicle; and determining a front wheel steering angle adjusting value of the vehicle according to the feedforward front wheel steering angle and the feedback front wheel steering angle so as to adjust the front wheel steering angle of the vehicle.
According to one embodiment of the present invention, determining a feed-forward front wheel steering angle and a feedback front wheel steering angle of a vehicle based on error information of the vehicle includes: determining a feedback front wheel corner of the vehicle by adopting a linear quadratic regulator LQR feedback control model according to error information of the vehicle; and determining the feedforward front wheel rotation angle of the vehicle by adopting a feedforward control model according to the error information of the vehicle.
Specifically, as shown in fig. 3, from the relationship between the graphic data, the matrix equation of the error model can be expressed as:
wherein, the first and the second end of the pipe are connected with each other,
representing the derivative of the error matrix, e e Representing vehicle error information; u is a control amount and indicates a front wheel steering angle adjustment value of the vehicle.
Comparing the matrix equation of the error model with the error model formula, the expression of the coefficient matrix A can be obtained as follows:
the coefficient matrix B is expressed as:
with continued reference to FIG. 3, the error information of the vehicle is fed back to the front wheel corner u using the LQR feedback control model k Can be expressed as u k ＝-We e Where W is the feedback matrix.
The feedback matrix W may be expressed by the following equation:
W＝(R+B T PB) -1 B T PA
and R is a control weight matrix, and when the vehicle is at different turning radii, the values of the control weight matrix are different.
Calculating a matrix P according to a Riccati equation, wherein the expression is as follows:
P＝A T PA-A T PB(R+B T PB) -1 B T PA+Q
wherein, the matrix Q is a state weight matrix, and the expression is:
wherein q is 1 、q 2 、q 3 And q is 4 The weight values respectively indicate the lateral position error, the lateral velocity error, the yaw angle error, and the yaw rate error.
Substituting the control weight matrix R, the state weight matrix Q, the matrix P, the coefficient matrix A and the coefficient matrix B into a formula: w = (R + B) T PB) -1 B T PA, a feedback matrix W and thus a feedback front wheel angle u can be obtained k 。
Further, the feedforward front wheel rotation angle delta can be calculated according to the feedback matrix W f . The specific process is as follows:
taking line 3 of the 4 × 4 feedback matrix W as W (3), a feedforward control model may be established, which may be expressed by the following equation:
let e n =0, available feedforward front wheel steering angle δ f Comprises the following steps:
for front wheel turning angle delta f And feeding back the front wheel angle u k And summing to obtain the front wheel steering angle adjustment value u. And adjusting the front wheel steering angle of the vehicle according to the front wheel steering angle adjustment value until the error between the running state information of the vehicle and the next planned point is 0, so that the automatic driving vehicle runs according to the planned path.
According to an embodiment of the present invention, the lateral control method for automatic driving of a vehicle further comprises: and when the running state information of the vehicle does not meet the preset condition, adjusting the predicted time length in the preview model and the parameters of the LQR feedback control model so as to enable the error information of the vehicle to be within a preset range.
That is, when the error information between the current operating state information of the autonomous vehicle and the planned point information at the next time is not 0, the error information of the autonomous vehicle is within a preset range by adjusting the predicted time length in the preview model and also adjusting parameters of the LQR feedback control model, such as a sampling period, so that the autonomous vehicle travels along the planned path.
According to one embodiment of the invention, after determining the front wheel steering angle adjustment value for the vehicle, the method further comprises: performing analog simulation according to the front wheel steering angle adjustment value of the vehicle to determine the actual front wheel steering angle of the vehicle; and acquiring the current running state information of the vehicle by adopting a two-degree-of-freedom dynamic model according to the actual front wheel turning angle of the vehicle.
Specifically, as shown in fig. 4, the preview model plans a driving path of the automatically-driven vehicle according to the current vehicle running state and the preview time, the vehicle control system (i.e., the LQR feedback control model and the feedforward control model) obtains a front wheel steering angle adjustment value u according to the error information, the carsim simulation software simulates the front wheel steering angle adjustment value u, and the actual front wheel steering angle δ of the vehicle can be obtained after the simulation. Substituting the actual front wheel corner delta of the vehicle into the following two-degree-of-freedom dynamic model formula:
the running state information of the automatically driven vehicle after planning running through the preview model, namely the current lateral acceleration and the current yaw angular acceleration can be obtained. And inputting the current transverse acceleration and the current yaw angular acceleration as feedback to a preview model, compensating the error information in a circulating mode until the error information is 0, and controlling the vehicle to run according to the vehicle running state information when the error is 0.
In summary, the lateral control method according to the present invention takes a two-degree-of-freedom system of a vehicle as an error model, LQR control as closed-loop feedback, compensates for a steady-state error by feedforward control, and improves the problem of hysteresis inherent in a physical system by using lateral acceleration and yaw acceleration as control parameters of a preview model.
In summary, according to the lateral control method for vehicle automatic driving in the embodiment of the present invention, the current operation state information of the vehicle is acquired, wherein the current state information of the vehicle includes: a current lateral acceleration and a current yaw angular acceleration; determining planning point information at the next moment according to the current transverse acceleration and the current yaw angular acceleration; and determining error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the next moment of planning point information, and adjusting the front wheel steering angle of the vehicle according to the error information of the vehicle so as to enable the running state information of the vehicle to meet the preset condition. Therefore, the method can improve the control precision of the automatic driving of the vehicle and enable the automatic driving vehicle to be closer to the planned track when the automatic driving vehicle turns.
Corresponding to the embodiment, the invention also provides a transverse control device for automatic driving of the vehicle.
Fig. 5 is a block diagram schematically illustrating a lateral control apparatus for vehicle autonomous driving according to an embodiment of the present invention.
As shown in fig. 5, the lateral control apparatus for vehicle autonomous driving according to the embodiment of the present invention includes: an acquisition module 10, a first determination module 20 and a second determination module 30.
The obtaining module 10 is configured to obtain current operating state information of a vehicle, where the current operating state information of the vehicle includes: the current lateral acceleration and the current yaw acceleration. The first determination module 20 is configured to determine planning point information at a next moment according to a current lateral acceleration and a current yaw acceleration. The second determining module 30 is configured to determine error information of the vehicle according to the current lateral acceleration, the current yaw acceleration, and the planning point information at the next time, and adjust a front wheel steering angle of the vehicle according to the lateral position error of the vehicle and the heading angle error of the vehicle, so that the operating state information of the vehicle meets a preset condition.
According to an embodiment of the present invention, the first determining module 20 determines the planning point information at the next moment according to the current lateral acceleration and the current yaw acceleration, and is specifically configured to obtain the planning point information at the next moment by using a preview model according to the current lateral acceleration and the current yaw acceleration, where the planning point information includes: the longitudinal coordinate of the planned point at the next moment of the vehicle, the transverse coordinate of the planned point at the next moment of the vehicle and the yaw angle of the planned point at the next moment of the vehicle.
According to one embodiment of the invention, the preview model is expressed using the following formula:
wherein x is p Longitudinal coordinate, y, representing the planned point at the next moment of the vehicle p The lateral coordinates of the planned point representing the next moment of the vehicle,
representing the yaw angle of a planned point at the next moment of the vehicle, x representing the longitudinal coordinate of the current moment of the vehicle, y representing the lateral coordinate of the current moment of the vehicle, v x Indicating the longitudinal speed, v, of the vehicle at the present moment y Indicating the lateral speed, t, of the vehicle at the present moment a Which represents the length of the prediction time period,
representing the yaw angle of the vehicle at the present moment, a x Representing the current longitudinal acceleration of the vehicle, a y Represents the current lateral acceleration of the vehicle,
represents the current yaw-rate of the vehicle,
representing the current yaw acceleration of the vehicle.
According to one embodiment of the invention, the second determination module 30 adjusts the front wheel steering angle of the vehicle based on the error information of the vehicle, and is specifically configured to determine a feed-forward front wheel steering angle and a feedback front wheel steering angle of the vehicle based on the error information of the vehicle; and determining a front wheel steering angle adjusting value of the vehicle according to the feedforward front wheel steering angle and the feedback front wheel steering angle so as to adjust the front wheel steering angle of the vehicle.
According to an embodiment of the present invention, after determining the front wheel steering angle adjustment value of the vehicle, the second determining module 30 is further configured to perform simulation based on the front wheel steering angle adjustment value of the vehicle to determine an actual front wheel steering angle of the vehicle; and acquiring the current running state information of the vehicle by adopting a two-degree-of-freedom dynamic model according to the actual front wheel steering angle of the vehicle.
According to one embodiment of the invention, the second determining module 30 determines a feedforward front wheel angle and a feedback front wheel angle of the vehicle according to the error information of the vehicle, and is specifically configured to determine the feedback front wheel angle of the vehicle according to the error information of the vehicle by using a linear quadratic form regulator LQR feedback control model; and determining the feedforward front wheel rotation angle of the vehicle by adopting a feedforward control model according to the error information of the vehicle.
According to an embodiment of the present invention, the second determining module 30 is further configured to, when the running state information of the vehicle does not satisfy the preset condition, adjust the predicted time length in the preview model and the parameters of the LQR feedback control model so that the error information of the vehicle is within a preset range.
According to an embodiment of the present invention, the second determining module 30 determines error information of the vehicle according to the current lateral acceleration, the current yaw acceleration and the planning point information at the next moment, and is specifically configured to establish a corresponding error model according to a two-degree-of-freedom dynamic model of the vehicle; and taking the current lateral acceleration, the current yaw angular acceleration and the planning point information at the next moment as the input of an error model to obtain the error information of the vehicle.
It should be noted that, please refer to the details disclosed in the lateral control method for automatic vehicle driving in the embodiment of the present invention, which are not disclosed in the lateral control device for automatic vehicle driving in the embodiment of the present invention, and detailed descriptions thereof are omitted here.
According to the lateral control device for the automatic driving of the vehicle, the obtaining module obtains the current running state information of the vehicle, the first determining module determines the planning point information at the next moment according to the current lateral acceleration and the current yaw angular acceleration, the second determining module determines the error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the planning point information at the next moment, and the front wheel rotation angle of the vehicle is adjusted according to the lateral position error of the vehicle and the heading angular error of the vehicle, so that the running state information of the vehicle meets the preset condition. Therefore, the device can improve the control precision of the automatic driving of the vehicle and enable the automatic driving vehicle to be closer to the planned track when the automatic driving vehicle turns.
The invention further provides a vehicle corresponding to the embodiment.
FIG. 6 is a block schematic diagram of a vehicle according to an embodiment of the present invention.
As shown in fig. 6, a vehicle 200 according to an embodiment of the present invention includes a memory 210, a processor 220, and a lateral control program for vehicle autonomous driving, which is stored in the memory 210 and can be executed on the processor 220, and when the processor 220 executes the lateral control program for vehicle autonomous driving, the lateral control method for vehicle autonomous driving is implemented.
According to the vehicle provided by the embodiment of the invention, by executing the transverse control method for automatic driving of the vehicle, the control precision during automatic driving of the vehicle can be improved, and the automatic driving vehicle can be closer to a planned track during steering.
The invention further provides a computer readable storage medium corresponding to the above embodiment.
A computer-readable storage medium of an embodiment of the present invention has stored thereon a lateral control program for vehicle autonomous driving, which when executed by a processor implements the above-described lateral control method for vehicle autonomous driving.
According to the computer-readable storage medium of the embodiment of the invention, by executing the transverse control method for automatic driving of the vehicle, the control precision during automatic driving of the vehicle can be improved, and the automatic driving vehicle can be closer to a planned track during steering.
It should be noted that the logic and/or steps shown in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following technologies, which are well known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description of the specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise explicitly stated or limited, the terms "mounted," "connected," "fixed," and the like are to be construed broadly, e.g., as being permanently connected, detachably connected, or integral; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
Although embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that changes, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (11)
1. A lateral control method for automatic driving of a vehicle, comprising:
acquiring current running state information of the vehicle, wherein the current state information of the vehicle comprises: a current lateral acceleration and a current yaw angular acceleration;
determining planning point information at the next moment according to the current transverse acceleration and the current yaw angular acceleration;
and determining error information of the vehicle according to the current lateral acceleration, the current yaw angular acceleration and the planning point information at the next moment, and adjusting the front wheel steering angle of the vehicle according to the error information of the vehicle so as to enable the running state information of the vehicle to meet a preset condition.
2. The lateral control method of vehicle autonomous driving according to claim 1, wherein determining planned point information at the next time based on the current lateral acceleration and the current yaw angular acceleration includes:
and acquiring planning point information of the next moment by adopting a preview model according to the current transverse acceleration and the current yaw angular acceleration, wherein the planning point information comprises: the longitudinal coordinate of the planned point at the next moment of the vehicle, the transverse coordinate of the planned point at the next moment of the vehicle and the yaw angle of the planned point at the next moment of the vehicle.
3. The lateral control method for automatic vehicle driving according to claim 2, wherein the preview model is expressed by the following formula:
wherein x is p Indicating the next moment of said vehicleLongitudinal coordinate of the planning point, y p A lateral coordinate representing a planned point at a next moment of the vehicle,
representing the yaw angle of a planned point at the next moment of the vehicle, x representing the longitudinal coordinate of the current moment of the vehicle, y representing the lateral coordinate of the current moment of the vehicle, v x Representing the longitudinal speed, v, of the vehicle at the present moment y Representing the lateral speed, t, of the vehicle at the present moment in time a Which represents the length of the prediction time period,
a yaw angle representing the current time of the vehicle, a x Representing the current longitudinal acceleration of the vehicle, a y Represents the current lateral acceleration of the vehicle,
represents a current yaw rate of the vehicle,
representing a current yaw acceleration of the vehicle.
4. The lateral control method of vehicular automated driving according to claim 3, wherein adjusting a front wheel steering angle of the vehicle based on the error information of the vehicle comprises:
determining a feedforward front wheel corner and a feedback front wheel corner of the vehicle according to the error information of the vehicle;
and determining a front wheel steering angle adjusting value of the vehicle according to the feedforward front wheel steering angle and the feedback front wheel steering angle so as to adjust the front wheel steering angle of the vehicle.
5. The lateral control method of vehicle autopilot according to claim 4 wherein after determining a front wheel steering angle adjustment value for the vehicle, the method further comprises:
performing analog simulation according to the front wheel steering angle adjustment value of the vehicle to determine the actual front wheel steering angle of the vehicle;
and acquiring the current running state information of the vehicle by adopting a two-degree-of-freedom dynamic model according to the actual front wheel steering angle of the vehicle.
6. The lateral control method of automatic driving of a vehicle according to claim 4, wherein determining a feed-forward front wheel steering angle and a feed-back front wheel steering angle of the vehicle based on the error information of the vehicle comprises:
determining a feedback front wheel corner of the vehicle by adopting a Linear Quadratic Regulator (LQR) feedback control model according to the error information of the vehicle;
and determining a feedforward front wheel corner of the vehicle by adopting a feedforward control model according to the error information of the vehicle.
7. The lateral control method of vehicle autopilot according to claim 6, characterized by further comprising:
and when the running state information of the vehicle does not meet the preset condition, adjusting the predicted time length in the preview model and the parameters of the LQR feedback control model so as to enable the error information of the vehicle to be within a preset range.
8. The lateral control method of automatic driving of a vehicle according to claim 6, wherein determining error information of the vehicle based on the current lateral acceleration, the current yaw angular acceleration, and the planned point information at the next time comprises:
establishing a corresponding error model according to the two-degree-of-freedom dynamic model of the vehicle;
and taking the current transverse acceleration, the current yaw angular acceleration and the planning point information of the next moment as the input of the error model to obtain the error information of the vehicle.
9. A lateral control device for automatic driving of a vehicle, comprising:
the acquiring module is used for acquiring the current running state information of the vehicle, wherein the current state information of the vehicle comprises: a current lateral acceleration and a current yaw angular acceleration;
the first determining module is used for determining planning point information of the next moment according to the current transverse acceleration and the current yaw angular acceleration;
and the second determining module is used for determining error information of the vehicle according to the current transverse acceleration, the current yaw angular acceleration and the next-moment planning point information, and adjusting the front wheel steering angle of the vehicle according to the transverse position error of the vehicle and the course angle error of the vehicle so as to enable the running state information of the vehicle to meet preset conditions.
10. A vehicle comprising a memory, a processor, and a lateral control program for vehicle autopilot stored on the memory and executable on the processor, the processor implementing the lateral control method for vehicle autopilot according to any one of claims 1-8 when executing the lateral control program for vehicle autopilot.
11. A computer-readable storage medium, characterized in that a lateral control program of vehicle autonomous driving is stored thereon, which when executed by a processor implements the lateral control method of vehicle autonomous driving according to any one of claims 1 to 8.
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| CN118210316A (en) * | 2024-05-21 | 2024-06-18 | 武汉未来幻影科技有限公司 | Continuous track transverse control method and related equipment thereof |
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