CN111717204A - Lateral control method and system for automatic driving vehicle - Google Patents

Lateral control method and system for automatic driving vehicle Download PDF

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Publication number
CN111717204A
CN111717204A CN201910205151.3A CN201910205151A CN111717204A CN 111717204 A CN111717204 A CN 111717204A CN 201910205151 A CN201910205151 A CN 201910205151A CN 111717204 A CN111717204 A CN 111717204A
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vehicle
steering wheel
lane
control
current
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CN111717204B (en
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鲁宁
张凯
和林
甄龙豹
葛建勇
王天培
高健
张健
刘洪亮
曹增
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Haomo Zhixing Technology Co Ltd
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Great Wall Motor 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
    • 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
    • B60W30/10—Path keeping
    • B60W30/12—Lane keeping
    • 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
    • B60W30/18163—Lane change; Overtaking manoeuvres
    • 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
    • B60W40/02—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 ambient conditions
    • B60W40/06—Road conditions
    • B60W40/072—Curvature of the road
    • 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
    • B60W40/114—Yaw movement
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/14—Yaw

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  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The invention relates to the technical field of automatic driving, and provides a transverse control method and a transverse control system for an automatic driving vehicle. The transverse control method comprises the following steps: receiving decision information regarding an expected lateral behavior of the vehicle; and responsive to the decision information, performing any of: lane keeping control, wherein a target steering wheel rotating angle matched with the lane keeping control is determined based on the pre-aiming road curvature of the vehicle, the current course angle deviation and the current transverse position deviation, and meets a first condition that the course angle deviation and the transverse position deviation are 0 and a second condition that the current pre-aiming road curvature reaches the set optimal road curvature; controlling the normal lane change of the vehicle; and the vehicle abnormal lane changing control is that the target steering wheel angle matched with the vehicle abnormal lane changing control is determined based on the current transverse state value of the vehicle and the target line to be moved to, and meets a first condition and a second condition. The invention can control lane keeping, normal lane changing or abnormal lane changing of the vehicle aiming at the transverse behavior of the vehicle, and is suitable for various complex working conditions.

Description

Lateral control method and system for automatic driving vehicle
Technical Field
The invention relates to the technical field of automatic driving, in particular to a transverse control method and a transverse control system for an automatic driving vehicle.
Background
The automatic Driving vehicle is an intelligent vehicle which senses road environment through a vehicle-mounted sensing System, automatically plans a Driving route and controls the vehicle to reach a preset destination, and the automatic Driving vehicle realizes the functions of the automatic Driving vehicle by means of an automatic Driving System (ADS for short). According to the development and design process of the ADS, the ADS can be divided into: the method comprises five parts of environment perception, data fusion, decision, control and execution.
Specifically, the environment sensing part is used for extracting current running environment information of vehicles such as vehicles, pedestrians, roads, traffic signs and the like through the vehicle-mounted sensing part; the data fusion part is used for screening, correlating, tracking, filtering and the like the data information of different sensors so as to obtain more accurate information such as a road, an environmental object target and the like; the decision part is used for logically judging and outputting the vehicle behavior of the unmanned vehicle according to the driving states, roads, environment information and the like of the vehicles in different environments output by the data fusion part; the control part is used for calculating and outputting the transverse and longitudinal control variable quantity of the current vehicle in real time according to the information output by the data fusion part and the decision part; the execution part is used for replacing the operation processes of a steering wheel, an acceleration pedal and a deceleration pedal of the vehicle by a driver according to the control quantity of steering, acceleration and the like output by the control part.
More specifically, the control part can be divided into transverse control and longitudinal control, the transverse control is to realize real-time steering control of the automatic driving vehicle through a series of control algorithms, the real-time steering control comprises the steps of enabling the vehicle to carry out abnormal lane changing, automatic lane changing, dynamic obstacle avoidance, turning around, turning and the like according to a known planned driving route, and the longitudinal control is mainly to control the acceleration and the deceleration of the vehicle, so that the automatic driving vehicle can longitudinally drive at a certain safe driving speed, and the automatic starting, stopping, following, cruising and the like are realized. Through the coupling of the transverse and longitudinal control, the steering and the speed of the vehicle can be automatically controlled at the same time.
In the transverse control, the functions of lane keeping, automatic lane changing and the like occupy most of the driving time, and most of common driving conditions are covered. However, in the actual operation of the vehicle, various complex working conditions exist, and the decision part can judge and output various transverse vehicle behaviors such as lane keeping, lane changing, abnormal lane changing and the like aiming at the complex working conditions, and how to correctly control the transverse vehicle behaviors plays a significant role in driving safety.
Disclosure of Invention
In view of the above, the present invention is directed to a lateral control method for an autonomous vehicle to solve the problem of correctly controlling the behavior of the lateral vehicle.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a lateral control method of an autonomous vehicle, comprising:
receiving decision information about an expected lateral behavior of the vehicle output by a decision system of the autonomous vehicle, wherein the expected lateral behavior comprises any one of lane keeping, normal lane changing of the vehicle and abnormal lane changing of the vehicle; and
in response to the decision information, performing any of the following accordingly:
performing lane keeping control, wherein a target steering wheel angle matching the performing of the lane keeping control is determined based on a pre-line road curvature, a current heading angle deviation, and a current lateral position deviation of the autonomous vehicle, and satisfies: a first condition that the current course angle deviation and the current transverse position deviation are 0; and a second condition for causing the pre-aimed road curvature to reach an optimal road curvature that minimizes an error between an actual travel trajectory and an expected trajectory of the vehicle;
executing normal lane changing control of the vehicle, wherein a target steering wheel rotating angle matched with the execution of the normal lane changing control of the vehicle is determined based on the vehicle speed, the current transverse position deviation and the current course angle deviation;
and executing vehicle abnormal lane change control, wherein a target steering wheel angle matched with the execution of the vehicle abnormal lane change control is determined based on a current lateral state value of the vehicle and a target line to be moved corresponding to the current lateral state value, and the first condition and the second condition are satisfied.
Compared with the prior art, the transverse control method of the automatic driving vehicle can carry out lane keeping control, normal lane changing control or abnormal lane changing control on the expected transverse behavior of the vehicle in real time, ensures that the target steering wheel rotation angle in each control state meets the condition of transverse safe driving of the vehicle, is suitable for various complex working conditions, and is beneficial to improving the driving safety of the automatic driving vehicle.
Another object of the present invention is to provide a lateral control system for an autonomous vehicle to solve the problem of properly controlling the lateral vehicle behavior.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a lateral control system for an autonomous vehicle, comprising:
the system comprises a receiving module, a judging module and a judging module, wherein the receiving module is used for receiving decision information which is output by a decision system of the automatic driving vehicle and relates to the expected transverse behavior of the vehicle, and the expected transverse behavior comprises any one of lane keeping, normal lane changing of the vehicle and abnormal lane changing of the vehicle; and
a control module for responding to the decision information and correspondingly executing any one of the following modules:
a lane keeping control module for performing lane keeping control, wherein a target steering wheel angle matching the lane keeping control is determined based on a pre-line road curvature, a current course angle deviation, and a current lateral position deviation of the autonomous vehicle, and satisfies: a first condition that the current course angle deviation and the current transverse position deviation are 0; and a second condition for causing the pre-aimed road curvature to reach an optimal road curvature that minimizes an error between an actual travel trajectory and an expected trajectory of the vehicle;
the vehicle normal lane changing control module is used for executing vehicle normal lane changing control, wherein a target steering wheel rotating angle matched with the execution of the vehicle normal lane changing control is determined based on the vehicle speed, the current transverse position deviation and the current course angle deviation;
and the vehicle abnormal lane changing control module is used for executing vehicle abnormal lane changing control, wherein a target steering wheel rotating angle matched with the execution of the vehicle abnormal lane changing control is determined based on a current transverse state value of a vehicle and a target line to be moved corresponding to the current transverse state value, and the first condition and the second condition are met.
The lateral control system of the autonomous vehicle and the lateral control method of the autonomous vehicle have the same advantages compared with the prior art, and are not described again.
Another object of the invention is to propose a machine readable storage medium to solve the problem of correct control of the lateral vehicle behaviour.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a machine-readable storage medium having instructions stored thereon for causing a machine to perform the above-described lateral control method for an autonomous vehicle.
The machine-readable storage medium has the same advantages as the above-described lateral control method for an autonomous vehicle over the prior art, and will not be described herein again.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention.
In the drawings:
FIG. 1 is a schematic flow chart of a lateral control method for an autonomous vehicle in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of a course angle deviation and a lateral position deviation defined in an embodiment of the present invention;
FIG. 3 is a schematic flow chart of obtaining curvature of a current pre-aimed road according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of the Ackerman steering principle;
FIG. 5 is a schematic diagram of a fuzzy logic control flow;
FIG. 6 is a schematic illustration of an abnormal lane change condition of the vehicle;
FIG. 7 is a schematic flow chart illustrating preview tracking control for an autonomous vehicle in an embodiment of the present invention;
FIG. 8 is a schematic view of a vehicle following an arc of a desired trajectory with curvature R in an embodiment of the present invention; and
fig. 9 is a schematic structural diagram of a lateral control system of an autonomous vehicle according to another embodiment of the present invention.
Description of reference numerals:
100. a receiving module; 200. a control module; 210. a lane keeping control module; 220. the vehicle normal lane changing control module; 230. and the vehicle abnormal lane change control module.
Detailed Description
In addition, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
Fig. 1 is a flowchart illustrating a lateral control method of an autonomous vehicle according to an embodiment of the present invention, which is applied to a control part of an ADS of the autonomous vehicle. As shown in fig. 1, the lateral control method may include the steps of:
step S100, receiving decision information about an expected lateral behavior of the vehicle output by a decision system of the autonomous vehicle.
Wherein the expected lateral behavior comprises any one of lane keeping, a normal lane change of the vehicle, and an abnormal lane change of the vehicle. Specifically, the decision-making system (or decision-making part) judges and outputs the transverse and longitudinal vehicle behaviors of the automatic driving vehicle according to the input information of the environmental object target, the road and the like, wherein the transverse vehicle behaviors are represented by lane keeping, lane changing, abnormal lane changing and the like, the longitudinal vehicle behaviors are represented by cruise, follow, emergency brake and the like which are realized by acceleration and deceleration, and the control system of the vehicle outputs the corresponding transverse and longitudinal control quantity according to the decision-making information including the vehicle behaviors output by the decision-making system so as to control the safe driving of the vehicle.
And step S200, responding to the decision information, and correspondingly executing lane keeping control, vehicle normal lane changing control or vehicle abnormal lane changing control.
The lane keeping control, the vehicle normal lane change control, and the vehicle abnormal lane change control will be described below.
Lane keeping control
In an embodiment of the present invention, a target steering wheel angle matching execution of the lane keeping control is determined based on a predicted road curvature, a course angle deviation, and a lateral position deviation of the autonomous vehicle, and satisfies: a first condition that the course angle deviation and the lateral position deviation are 0; and a second condition for the pre-line road curvature to reach an optimal road curvature that minimizes an error between an actual travel trajectory and a desired trajectory of the vehicle.
For the purpose of satisfying the first and second conditions, the method for performing lane protection control in the embodiment of the present invention may include the following steps S210A-S240A (not shown in the figure):
step S210A, obtaining the heading angle deviation and the transverse position deviation to predict the curvature of the road.
Specifically, the course angle refers to an included angle between the current course of the vehicle and a lane line where the vehicle is located, and the course angle deviation is an angle deviation between the current course angle and a target course angle; the lateral position deviation is a distance deviation between the current lateral position of the vehicle and the target running track. FIG. 2 is a schematic diagram of a heading angle deviation and a lateral position deviation defined in an embodiment of the present invention, wherein d represents the lateral position deviation and α represents the heading angle deviation. In addition, during the lane keeping process, the target heading angle is consistent with the direction of the lane center line, and the target driving track can be, for example, the lane center line, so that in the ideal lane keeping process, d and α should be 0, so that the vehicle can keep driving safely on the lane center line.
Further, fig. 3 is a schematic flow chart of acquiring a curvature of a pre-aimed road according to an embodiment of the present invention. Referring to fig. 3, the following steps may be included:
step S211, obtaining a current lane line equation of the automatic driving vehicle.
For example, the fusion system of the automatic driving system outputs lane line information including lane line type, lane line width, lane line reliability, etc. by fitting the lane line information, a lane line equation in a vehicle coordinate system can be obtained, for example, as
y＝c0+c1*x+c2x2+c3x3(1)
In the formula, (x, y) represents a lane line coordinate, c0-c3 represents a pending parameter, different parameter values represent different types of roads, and when c2 and c3 are 0, straight line segments are represented. Wherein, the values of c0-c3 can be extracted in the lane line fitting.
And step S212, acquiring the current pre-aiming distance of the automatic driving vehicle.
When a driver drives a vehicle, the driver usually pays attention to a distance in front of the driving direction of the vehicle so as to grasp the next position (namely the front view point of the driver) where the vehicle drives, the distance from the current position to the next position selected by the driver is the pre-aiming distance, and the corresponding next position is the pre-aiming point. Generally, in order to better simulate the driving process of a driver, when lane keeping control is performed on an autonomous vehicle, a distance is selected as a pre-line distance in front of the driving path of the autonomous vehicle.
In the embodiment of the invention, the pre-aiming distance of the vehicle can be obtained through the following formula:
Figure BDA0001998741390000071
in the formula, s represents the pre-aiming distance and has the unit of meter; m is a predetermined coefficient, and can be determined empirically by those skilled in the art in conjunction with the minimum turning radius of the vehicle, for example m can be 1.5; v represents the vehicle speed in kilometers/hour, and s is converted into meters/second because of the meter, and 3.6 in the formula is a related conversion parameter. d0For fixed pre-aiming distance, it is typically 4m, based on road testing experience.
And S213, calculating the curvature of the pre-aimed road according to the current pre-aimed distance and the current lane line equation.
With the current pre-line distance and current lane line equation known, the pre-line road curvature can be calculated by:
ρ＝a1*c3*s+a2*c2 (3)
where a1 and a2 are conventional parameters, e.g., 6 and 2, respectively, c2 and c3 are obtained according to equation (1) above, and s is obtained according to equation (2) above.
Accordingly, the pre-line curvature of the vehicle is obtained.
In step S220A, a first controller, a second controller, and a third controller are provided.
Wherein the first controller inputs the pre-line road curvature and outputs a first target steering wheel angle at which the pre-line road curvature reaches the optimal road curvature.
Here, the input parameter is the pre-aiming road curvature, so the first controller is essentially a pre-aiming tracking controller, which is based on the pre-aiming following theory, the vehicle-driver forms a closed loop system, and the pre-aiming distance of the forward sight is estimated according to the current lane line information and the vehicle motion state, so that the error of the vehicle relative to the expected track in the route is minimized, and the required optimal pre-aiming curvature is achieved. That is, if the driver can grasp the mapping relationship between the trajectory curvature and the steering wheel angle in the continuous driving practice, the corresponding steering wheel angle is naturally determined when the driver observes a specific road curvature. Therefore, it is important to establish a mapping relationship between the target steering wheel angle and the curvature of the pre-line road in the control process of the first controller.
Preferably, in the embodiment of the present invention, a mapping relationship between the target steering wheel angle and the curvature of the pre-aimed road may be established based on Ackerman (Ackerman) steering principle, so that the optimal steering wheel angle required for lane keeping is obtained according to the mapping relationship. Fig. 4 is a schematic view of the ackermann steering principle, in which L is the wheel base, R is the turning radius of the vehicle,fis the corner of the front wheel. Under the condition that the vehicle G is in low-speed steering, the turning radius R of the vehicle is only equal to the front wheel steering anglefAnd the Ackerman principle is satisfied. For convenience of description, the four-wheel vehicle model is simplified into a two-wheel model, that is, the turning angles of the inner and outer wheels when the vehicle turns are considered to be equal, so that L, R is used as a basisfThe geometrical relationship of the three can be obtained:
Figure BDA0001998741390000081
further, front wheel steering anglefSteering wheel angle sigma and steering system gear ratio G of vehicleiThere is a mapping relationship between:
σ＝Gi*f(5)
further, the pre-line road curvature ρ is 1/R, so that the mapping relationship between the target steering wheel angle σ and the pre-line road curvature ρ can be obtained by combining the formula (4) and the formula (5):
σ＝arctan(L.ρ)*Gi(6)
therefore, the preview following theory is combined with the Ackerman steering principle, so that the target control quantity (namely the first target steering wheel angle) is compensated, and the nonlinear motion working condition of closed-loop response can be met.
Wherein the second controller inputs the lateral position deviation and outputs a second target steering wheel angle at which the lateral position deviation is 0.
In the embodiment of the present invention, the second controller may adopt a PID controller. When a PID controller is used, the PID controller is often required to be capable of self-tuning P, I, D parameters according to the change of a controlled object, so that a plurality of groups of P (proportional), I (integral) and D (differential) parameters need to be adjusted according to different vehicle speeds, and then corresponding parameters are obtained according to different lookup tables of the vehicle speeds. However, the parameters obtained by the table lookup are not continuous, and the vehicle speed is continuously varied, so that parameters that cannot be found in the table are always encountered.
In this regard, in a preferred embodiment, it is contemplated that the fuzzy logic control and the PID control are combined to design a fuzzy PID controller to eliminate the lateral position deviation. Fig. 5 is a schematic diagram of a fuzzy logic control flow, and as shown in fig. 5, a corresponding fuzzy logic control module can be divided into four components: an input quantity fuzzification interface, an output quantity defuzzification (clarification) interface, fuzzy reasoning and a knowledge base. In the embodiment of the invention, the input (vehicle speed) and the output (P, D parameters) of the fuzzy logic control module are fuzzified to obtain a fuzzy domain. And selecting a triangular function as a membership function of the input and output fuzzy subsets for mathematical expression and simple operation.
The fuzzy subset of inputs (vehicle speed) is:
[0，5]；[5，10]；[10，15]；[15，20]；[20，25]；[25，30]；[30，35]；[35，40]；[40，45]；[45，50]；[50，55]；[55，60]；[60，65]；[65，70]；[70，75]；[75，80]；[80，85]；[85，90]；[90，95]；[95，100]；[105，110]；[110，115]；[115，120]
the knowledge base comprises a database and a rule base, wherein P, I, D parameters are calibrated according to different vehicle speeds, and the fuzzy rules are in one-to-one correspondence with the knowledge base. The deblurring calculation adopts a weighted average method,according to the antecedent condition of each rule and the input fuzzy set, according to the determined membership degree kiAs a weight, the value z is represented for the back partiWeighted average is made and clear value z is output0The formula is as follows:
Figure BDA0001998741390000091
in the formula, ziFor the endpoint values of the fuzzy subset of output quantities, kiFor degree of membership, z, of input quantities in the fuzzy subset concerned0Is the exact value of the output. The fuzzy logic control module realizes the self-adaptive function of the PID parameters to the vehicle speed, and finally realizes the self-adaptive control.
In practical applications, the embodiment of the present invention, in which the second controller is adopted to make the lateral position deviation be 0, may specifically include:
1) PID control section
Firstly, setting the current lateral position deviation as e (t), and performing PD operation on the deviation e (t):
y＝kp*e(t)+kd*de(t)/dt (8)
where kp is the proportional (P) parameter and kd is the derivative (D) parameter, which is obtained by means of modulus control, as will be described in detail in the fuzzy control section.
And then, judging whether the transverse position deviation is e (t) or not, if so, ending the process, otherwise, returning to a formula (8), and adjusting the target control quantity y until the transverse position deviation is 0.
2) Fuzzy control part
The part mainly obtains the control coefficients kp and kd of the PID controller of the formula (8) through the real-time changing vehicle speed, and specifically comprises the following steps:
firstly, fuzzifying an input vehicle speed v to obtain a fuzzy domain, and calculating the membership degree of the input vehicle speed, wherein the main membership degree calculation formula is as follows:
lsd1＝(v-v(i))/(v(i+1)-v(i))
lsd2＝(v(i+1)-v)/(v(i+1)-v(i)) (9)
secondly, fuzzy reasoning is carried out, wherein a specific reasoning formula is as follows:
kp (i) < kp < kp (i +1) and kd (i) < kd < kd (i +1), if v (i) < v < v (i +1) (10)
And finally, carrying out ambiguity resolution, wherein a specific ambiguity resolution formula is as follows:
kp＝(lsd1*kp(i)+lsd2*kp(i+1))/(lsd1+lsd2)
kd＝(lsd1*kd(i)+lsd2*kd(i+1))/(lsd1+lsd2) (11)
accordingly, the fuzzy control portion supplies the PID control portion with the control coefficients kp and kd adaptive to the vehicle speed, so that the PID control portion performs PD control of the lateral position deviation based on the determined control coefficients kp, kd, resulting in a control amount for making the lateral position deviation 0.
And the third controller inputs the course angle deviation and outputs a third target steering wheel rotating angle which enables the course angle deviation to be 0.
In an embodiment of the present invention, the third controller may adopt a PID controller. Since the vehicle is always expected to have the same direction as the lane line direction during the traveling of the vehicle, the target heading angle is 0 degree. Therefore, through PID control, the course angle deviation is used as input, and then PID operation is carried out on the course angle deviation to obtain the control quantity. In the embodiment of the invention, in order to enable the designed PID controller to achieve the effect of quick response, only P control can be adopted for course angle deviation, and an ideal P parameter is obtained through real vehicle test calibration and correction.
In practical applications, the embodiment of the present invention, where the third controller is adopted to make the heading angle deviation be 0, may include:
firstly, the current course angle deviation is calculated, and a PID parameter table is looked up according to the actual vehicle speed.
For example, if the target heading angle is 0 degrees and the current heading angle is denoted by HeadingAngle, the heading angle deviation e (t) is-HeadingAngle. In addition, the PID parameter table is obtained by actual vehicle test calibration and correction, and shows the optimal kp values corresponding to different vehicle speeds.
And secondly, performing P control operation on the course angle deviation.
The operation formula can be expressed as y ═ kp × e (t), y represents the control quantity, kp is the proportional coefficient controlled by P, and kp is obtained by querying the PID parameter table.
And finally, judging whether the course angle deviation is e (t) is 0, if so, ending the process, otherwise, returning to the previous step, and adjusting the target control quantity y until the course angle deviation is 0.
Therefore, the course angle deviation is controlled to be 0 through P control on the course angle deviation, and the PID controller can achieve the effect of quick response.
Step S230A, determining a final target steering wheel angle according to the first target steering wheel angle, the second target steering wheel angle, and the third target steering wheel angle.
For example, the pre-aiming tracking control is performed on the curvature of the pre-aiming road to obtain a first target steering wheel angle y1, the PD calculation is performed on the lateral position deviation to obtain a second target steering wheel angle y2, and the P calculation is performed on the heading angle deviation to obtain a third target steering wheel angle y3, so that the final target control steering wheel angle may be represented as y1+ y2+ y 3.
And step S240A, controlling the autonomous vehicle to perform lane keeping according to the final target steering wheel angle.
For example, a steering wheel angle command may be generated according to a target steering wheel angle, the steering wheel angle command may be sent to the steering wheel controller, and the steering wheel controller may receive the steering wheel angle command, analyze the corresponding target steering wheel angle, and adjust the angle and direction of rotation of the steering wheel accordingly, so that the autonomous vehicle may keep running on the center line of the current driving lane.
In conjunction with the above-mentioned steps S210A-S240A, the lane keeping control scheme according to the embodiment of the present invention has the following advantages:
1) the algorithm is designed according to vehicle kinematics, fuzzy-PID and PID control are respectively applied to the horizontal position deviation and the course angle deviation through preview tracking control, the real-time control requirement is met, the lane keeping effect is good, and the algorithm has very high transportability after encapsulation.
2) The traditional lane keeping control method is generally designed based on the idea of track tracking, and high-precision positioning equipment needs to be installed on a vehicle, so that the hardware cost is additionally increased, and the embodiment of the invention can realize the same function through lane information output by a high-definition camera, so that the system cost is greatly reduced.
3) Through the optimal pre-aiming road curvature, the preliminary grasping and utilization of the front road information can be realized in the feedforward control, the automatic driving vehicle can be enabled to perform corresponding actions in advance according to the first target steering wheel corner output by the first controller, the driving process is more comfortable and smooth, the driving condition of the driver on the road is better met, the requirement that the automatic driving vehicle can keep lanes under the road conditions of straight roads, curved roads and the like at the safe driving speed is met, the problems of over-steering and understeer caused by improper operation are avoided, and the driving stability and the driving safety of the curved roads are improved.
4) The fuzzy reasoning module for self-tuning P, I, D parameters is designed according to the change of the vehicle speed and is combined with PID control to realize self-adaptive PID control, and in addition, a mature control theory is applied, so that the feasibility is strong, the stability and the control robustness of the system are improved, and the operation efficiency is high.
(II) normal lane change control of vehicle
It should be noted that the normal lane change and the abnormal lane change of the vehicle in the embodiment of the present invention are relative concepts, and the normal lane change may be understood as an automatic lane change, that is, a conventional lane change, such as a lane change of passing, a lane change, and the like, performed according to a road condition and a driving demand, and the abnormal lane change relates to a more complicated working condition, for example, driving into a target ramp under a forced cut-in working condition, abnormal driving in a vehicle lane, abnormal driving across a lane under a front obstacle or road repair condition, and the like.
And determining the target steering wheel rotation angle matched with the execution of the normal lane changing control of the vehicle based on the vehicle speed, the transverse position deviation and the course angle deviation. The related calculation schemes are well described in the prior art, and will not be described in more detail herein, for example, the patent with application number 201810652866.9, which was filed by the inventor of the present application before the present application, is a lane change control method and apparatus, and the entire content of the patent is incorporated herein by reference to explain the normal lane change control method of the embodiment of the present invention 201810652866.9.
(III) abnormal lane-changing control of vehicle
In the embodiment of the present invention, the target steering wheel angle that matches the execution of the abnormal lane change control of the vehicle is determined based on the current lateral state value of the vehicle and the target line to be traveled to corresponding to the current lateral state value, and the first condition and the second condition are satisfied.
Fig. 6 is a schematic diagram of a working condition of an Abnormal Lane Change (ALC) of the vehicle, and it can be known that the ALC includes working conditions such as driving into a target ramp under a forced cut-in working condition, Abnormal driving in the own Lane, Abnormal driving across lanes under a condition that an obstacle exists in front of the own Lane or road repair is performed. Referring to fig. 6, the following steps S210B-240B (not shown) may be employed in the embodiment of the present invention to perform ALC:
in step S210B, a current lateral state value of the autonomous vehicle and a target line to which the autonomous vehicle is to move corresponding to the current lateral state value are acquired.
Where different lateral state values are used to show different lateral states, it may be defined, for example, that when the lateral state value is 0, the vehicle is in a lane keeping state. And, each lateral state value is preconfigured to correspond to a different said target line, including for example: when the transverse state value is a first numerical value, the target line is the center line of the current lane; when the transverse state value is a second numerical value, the target line is a left lane central line; when the transverse state value is a third numerical value, the target line is the center line of the right lane; when the transverse state value is a fourth numerical value, the target line is a dynamic deviation line of the current lane; when the transverse state value is a fifth numerical value, the target line is a lane crossing dynamic deviation line; when the transverse state value is a sixth numerical value, the target line is a left safety offset line; and when the transverse state value is a seventh numerical value, the target line is a right safety offset line.
The first to seventh values are different and may be set arbitrarily, which is not limited in the embodiment of the present invention. For example, table 1 gives examples of the first to seventh numerical values and their correspondence with the target line.
TABLE 1 correspondence of lateral State values to target lines
The lateral state value: transverse state Target line
0: in-lane keeping Center line of the lane
1: left lane changing Left lane center line
-1: right lane changing Center line of right lane
2: abnormality in own lane Dynamic deviation line of the lane
3: abnormality across lanes Dynamic deviation line of cross lane
4: left side safety offset Left side safety offset line
-4: right side safety offset Right side safety offset line
According to table 1, when the lateral state values output by the decision system of the autonomous vehicle are 2, 3, 4, -4, it is indicated that the vehicle is in an abnormal lane change state. Therefore, according to the rule defined in table 1, the corresponding target line should be selected to control the vehicle to move to the selected target line, so as to accomplish the adaptive ALC control.
Step S220B, determining a desired trajectory of the autonomous vehicle from the target line.
According to the information of the lane line where the vehicle is located and the information of the environment of the vehicle, under the condition that the current transverse state and the target line of the vehicle are known, the expected track of the vehicle is easy to determine. For example, when there is an obstacle in the own lane of the vehicle, the current lateral state is that the own lane is abnormal, and the target line is the own lane dynamic deviation line, it is easy to determine the expected trajectory of the vehicle that deviates from the center line of the own lane to the target line.
And step S230B, performing preview tracking control on the automatic driving vehicle based on the expected track to obtain a target steering wheel angle.
The preview tracking control is performed based on the preview following theory. Fig. 7 is a schematic flow chart illustrating preview tracking control for an autonomous vehicle according to an embodiment of the present invention. As shown in fig. 7, the step S230B may further include the following steps:
step S231, determines the preview point.
In the embodiment of the invention, after the expected track and the longitudinal speed of the vehicle are obtained, the pre-aiming can be carried out along the driving direction of the vehicle by pre-estimating the information in front of the road, a reasonable pre-aiming distance is selected according to the current vehicle state, and a pre-aiming point is correspondingly determined.
Step S232, calculating a distance between a point closest to the preview point in the expected trajectory and the preview point, and taking the distance as a preview error.
And step S233, determining a transfer function relationship between the preview error and the steering wheel angle according to a vehicle dynamic model, a motion rule, a preview distance and a vehicle speed of the automatic driving vehicle.
Specifically, fig. 8 is a schematic diagram of the circular arc motion of the vehicle along the desired track with curvature R, where d is the preview distance, l is the preview error, h is the distance from the preview point to the center of the curve, R is the curvature radius of the desired track, w is the yaw rate, u is the longitudinal vehicle speed of the vehicle, and v is the lateral speed. With reference to fig. 4, the embodiment of the present invention adopts a two-degree-of-freedom vehicle dynamics model, neglecting the effects of the steering system and the suspension, assuming that the displacement of the vehicle about the z-axis and the pitch angle and roll angle of the vehicle about the y-axis and the x-axis are both zero, and the forward speed of the vehicle along the x-axis is regarded as constant. Therefore, the whole vehicle comprises two degrees of freedom of lateral direction and transverse swing, and the dynamic differential equation of the whole vehicle is as follows:
Figure BDA0001998741390000151
Figure BDA0001998741390000152
in the formula, is the corner of the front wheel, IzIs the moment of inertia of the vehicle around the z-axis, m is the vehicle mass, a is the distance from the vehicle center of mass to the front axle, b is the distance from the vehicle center of mass to the rear axle, KafFront wheel cornering stiffness; karIs rear wheel cornering stiffness.
Assuming that the vehicle is travelling along the desired curve with a steady state following error of zero, in steady state conditions,
Figure BDA0001998741390000153
the vehicle model equation obtained according to the above equation of differential is:
Figure BDA0001998741390000161
according to the above equation, the lateral velocity v of the vehicle in the steady state situation can be expressed as a relation expressed in yaw rate w:
ν＝e·w (15)
wherein e is a matrix type which can be obtained from the formula (14).
According to the law of the steady circular motion, the following relation can be obtained:
Figure BDA0001998741390000162
V＝R·w (17)
in the formula, V is the speed of the circular motion of the vehicle. Due to the complexity of road working conditions, the selection of the pre-aiming distance has great influence on the pre-aiming following effect, and when the vehicle speed is low, if the pre-aiming distance is too large, the information of the road ahead cannot be well utilized; when the speed of a motor vehicle is higher, if the preview distance is too short, the road information in the front can be lost, the above conditions are integrated, and the preview distance is selected as follows:
Figure BDA0001998741390000163
wherein K is the preview coefficient, u is the longitudinal speed (km/h) of the vehicle, and d0For fixed pre-aiming distance, the experience is generally 4m according to road test, and 3.6 is related conversion parameters.
In addition, with reference to fig. 8, the corresponding relationship between the preview distance d and the preview error l in the figure can be obtained, and the front wheel rotation angle and the steering wheel rotation angle
Figure BDA0001998741390000164
And steering system gear ratio G of the vehicleiThere is a mapping relationship between:
Figure BDA0001998741390000165
finally, determining the transfer function between the desired steering wheel angle and the preview error according to the above equation and law of motion can be expressed as:
Figure BDA0001998741390000166
and step S234, calculating a target steering wheel rotation angle corresponding to the current preview error according to the transfer function relation.
For example, based on equation (20), after the current preview error is known, the corresponding target steering wheel angle may be calculated.
In other embodiments of the present invention, the target steering wheel angle may also be obtained according to the preview curvature of the vehicle, that is, the scheme of the formula (3) to the formula (6) in the foregoing step S213.
And step S240B, controlling the automatic driving vehicle to carry out abnormal lane changing of the vehicle according to the target steering wheel angle.
For example, a steering wheel angle command may be generated according to a target steering wheel angle, the steering wheel angle command may be sent to a steering wheel controller, and the steering wheel controller may receive the steering wheel angle command, analyze a corresponding target steering wheel angle, and adjust a steering wheel rotation angle and direction accordingly, so that the autonomous vehicle may safely and stably travel to a target line.
The transfer function based on the preview error and the steering wheel angle is established, so that the feedforward control of the steering wheel angle is realized, but in the transverse control process, due to model errors and various external interferences, the good control effect and stability are difficult to ensure only the feedforward control. Therefore, the method for controlling the abnormal lane change of the vehicle, provided by the embodiment of the invention, also adds the feedback control based on the deviation of the heading angle.
Specifically, during the course following process, the heading angle of the vehicle reflects the tangential direction of the vehicle tracking the course, since the vehicle driving direction is always expected to be consistent with the selected target line direction during the vehicle driving process, i.e. the target heading angle should be 0 degree. Accordingly, the control method for the abnormal lane change of the vehicle in the embodiment of the invention further comprises the following steps: the method comprises the steps of obtaining course angle deviation between a current course angle and a target course angle of an automatic driving vehicle, carrying out PID operation on the course angle deviation to obtain a control increment aiming at a steering wheel corner, and correcting the target steering wheel corner based on the control increment.
For example, if the target heading angle is 0 degrees and the current heading angle is denoted by HeadingAngle, the heading angle deviation e (t) is-HeadingAngle. When the lateral state values are 2, 3, 4 and-4 in table 1, a higher demand is placed on the control in the emergency state, and in order to achieve the effect of quick response by the controller designed, the P control may be adopted only for the vehicle heading angle deviation. Accordingly, the operational formula of P control can be expressed as y ═ kp × e (t), y represents the control increment, kp is the proportional coefficient of P control, and kp is obtained by querying the PID parameter table. And judging whether the heading angle deviation is 0 or not, if the deviation is 0, correcting the target steering wheel angle, and otherwise, adjusting the control increment y until the heading angle deviation is 0 through y-kp-e (t). Further, when the initial target steering wheel angle y1 is obtained and the heading angle deviation P is calculated to obtain the control increment y2 when the preview tracking control is performed on the preview error, the final target control steering wheel angle may be represented as y1+ y 2.
The automatic driving vehicle can be influenced by various complex working conditions and different road scenes in the driving process, and the abnormal lane changing control scheme of the vehicle has self-adaptability, so that the automatic driving vehicle can cope with various abnormal road working conditions. Furthermore, the abnormal lane changing control scheme of the vehicle provided by the embodiment of the invention adaptively selects the corresponding safety deviation line, the in-lane dynamic target line, the cross-lane dynamic target line and the like according to the transverse decision state aiming at the abnormal road working condition, and controls the vehicle to run according to the target line, thereby ensuring the driving safety and the safety of passengers. In addition, the abnormal lane change control scheme of the vehicle provided by the embodiment of the invention has a wide application range, can be suitable for automatic driving systems under curved roads and straight roads with different curvatures, and meets the requirements on the operation stability and the safety of the vehicle.
In summary, the lateral control method of the autonomous vehicle according to the embodiment of the present invention can perform lane keeping control, normal lane changing control or abnormal lane changing control on the expected lateral behavior of the vehicle in real time, and ensure that the target steering wheel angle in each control state meets the condition of lateral safe driving of the vehicle, so that the method is suitable for various complex working conditions, and is beneficial to improving the driving safety of the autonomous vehicle.
Fig. 9 is a schematic structural diagram of a lateral control system of an autonomous vehicle according to another embodiment of the present invention, which is based on the same inventive concept as the lateral control method described above. As shown in fig. 9, the lateral control system of the embodiment of the present invention includes: a receiving module 100 for receiving decision information regarding an expected lateral behavior of the vehicle output by a decision system of the autonomous vehicle; and a control module 200 for responding to the decision information, and executing any one of the following modules correspondingly:
a lane-keeping control module 210 for performing lane-keeping control, wherein a target steering wheel angle matching the lane-keeping control is determined based on a pre-line road curvature, a heading angle deviation, and a lateral position deviation of the autonomous vehicle, and satisfies: a first condition that the course angle deviation and the lateral position deviation are 0; and a second condition for the pre-line road curvature to reach an optimal road curvature that minimizes an error between an actual travel trajectory and a desired trajectory of the vehicle.
And a vehicle normal lane change control module 220, configured to execute a vehicle normal lane change control, where a target steering wheel angle matched to the execution of the vehicle normal lane change control is determined based on the vehicle speed, the lateral position deviation, and the heading angle deviation.
And a vehicle abnormal lane change control module 230 configured to perform vehicle abnormal lane change control, wherein a target steering wheel angle that matches the execution of the vehicle abnormal lane change control is determined based on a current lateral state value of the vehicle and a target line to be traveled to corresponding to the current lateral state value, and the first condition and the second condition are satisfied.
In a preferred embodiment, the lane keeping control module includes 210: the lane keeping obtaining submodule is used for obtaining the course angle deviation, the transverse position deviation and the pre-aiming road curvature; a first controller for inputting the pre-addressed road curvature and outputting a first target steering wheel angle at which the pre-addressed road curvature reaches the optimal road curvature; a second controller for inputting the lateral position deviation and outputting a second target steering wheel angle at which the lateral position deviation is 0; a third controller for inputting the course angle deviation and outputting a third target steering wheel angle at which the course angle deviation is 0; a first steering wheel turn angle determining submodule, configured to determine a final target steering wheel turn angle according to the first target steering wheel turn angle, the second target steering wheel turn angle, and the third target steering wheel turn angle; and the lane keeping control submodule is used for controlling the automatic driving vehicle to keep a lane according to the final target steering wheel turning angle.
In a preferred embodiment, the vehicle abnormal lane change control module 230 includes: the abnormal lane changing obtaining submodule is used for obtaining the current horizontal state value and the target line, wherein each horizontal state value is preconfigured to correspond to different target lines; an expected trajectory determination submodule for determining an expected trajectory of the autonomous vehicle based on the target line; a second steering wheel angle determination submodule configured to perform preview tracking control on the autonomous vehicle based on the desired trajectory to obtain a target steering wheel angle that satisfies the first condition and the second condition; and the abnormal lane changing control submodule is used for controlling the automatic driving vehicle to carry out abnormal lane changing of the vehicle according to the target steering wheel angle.
More preferably, the second steering wheel angle determination submodule includes: the first calculation submodule is used for determining a preview point, calculating the distance between the point, closest to the preview point, in the expected track and the preview point, and taking the distance as a preview error; and the second calculation submodule is used for determining a transfer function relationship between the preview error and the steering wheel corner according to a vehicle dynamic model, a motion rule, a preview distance and a vehicle speed of the automatic driving vehicle, and calculating a target steering wheel corner corresponding to the current preview error according to the transfer function relationship.
For details and effects of other implementations of the lateral control system of the autonomous vehicle according to the embodiment of the present invention, reference may be made to the foregoing embodiment of the lateral control method of the autonomous vehicle, and details are not described herein again.
Another embodiment of the present invention also provides a machine-readable storage medium having instructions stored thereon for causing a machine to perform the lateral control method of an autonomous vehicle described above. The machine-readable storage medium includes, but is not limited to, phase change Memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Flash Memory (Flash Memory) or other Memory technologies, compact disc read only Memory (CD-ROM), Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, and the like, which can store program code.
The machine-readable storage medium CAN be executed by a processor on the vehicle, and the processor CAN utilize a vehicle CAN bus and the like to acquire required vehicle information, lane line information, environment information and the like from an environment sensing part and the like of the ADS to judge whether the vehicle is in a lane keeping state, a vehicle normal lane changing state or a vehicle abnormal lane changing state and the like, and correspondingly execute the instructions stored in the machine-readable storage medium.
The Processor may be an ECU (Electronic Control Unit) of the vehicle, or may be an independently configured conventional controller, such as a CPU, a single Chip, a DSP (Digital Signal Processor), an SOC (System On a Chip), and the like, and it is understood that these independent controllers may also be integrated into the ECU. The processor is preferably configured by adopting a controller with high operation speed and abundant I/O port equipment, and is required to be provided with an input/output port capable of communicating with the CAN of the whole vehicle, an input/output port for switching signals, a network cable interface and the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (13)

1. A lateral control method of an autonomous vehicle, characterized by comprising:
receiving decision information about an expected lateral behavior of the vehicle output by a decision system of the autonomous vehicle, wherein the expected lateral behavior comprises any one of lane keeping, normal lane changing of the vehicle and abnormal lane changing of the vehicle; and
in response to the decision information, performing any of the following accordingly:
performing lane keeping control, wherein a target steering wheel angle matching the performing of the lane keeping control is determined based on a pre-line road curvature, a current heading angle deviation, and a current lateral position deviation of the autonomous vehicle, and satisfies:
a first condition that the current course angle deviation and the current transverse position deviation are 0; and
a second condition, enabling the curvature of the pre-aiming road to reach the optimal curvature of the road, wherein the error between the actual running track and the expected track of the vehicle is minimum;
executing normal lane changing control of the vehicle, wherein a target steering wheel rotating angle matched with the execution of the normal lane changing control of the vehicle is determined based on the vehicle speed, the current transverse position deviation and the current course angle deviation;
and executing vehicle abnormal lane change control, wherein a target steering wheel angle matched with the execution of the vehicle abnormal lane change control is determined based on a current lateral state value of the vehicle and a target line to be moved corresponding to the current lateral state value, and the first condition and the second condition are satisfied.
2. The lateral control method of an autonomous vehicle as claimed in claim 1, characterized in that the performing lane-keeping control includes:
acquiring the current course angle deviation, the current transverse position deviation and the pre-aiming road curvature;
setting a first controller, wherein the first controller inputs the curvature of the pre-aimed road and outputs a first target steering wheel corner which enables the curvature of the pre-aimed road to reach the optimal curvature of the road;
setting a second controller, which inputs the current lateral position deviation and outputs a second target steering wheel angle at which the current lateral position deviation is 0;
setting a third controller, wherein the third controller inputs the current course angle deviation and outputs a third target steering wheel rotation angle which enables the current course angle deviation to be 0;
determining a final target steering wheel angle according to the first target steering wheel angle, the second target steering wheel angle and the third target steering wheel angle; and
and controlling the automatic driving vehicle to keep the lane according to the final target steering wheel angle.
3. The lateral control method of an autonomous vehicle according to claim 2,
the first controller is configured to establish a mapping relationship between the target steering wheel angle and the pre-line road curvature based on ackermann steering principles; and/or
The second controller is configured to determine a control coefficient of the second controller for fuzzy PID control according to the real-time vehicle speed of the autonomous vehicle.
4. The lateral control method of an autonomous vehicle as recited in claim 1, characterized in that the executing of the vehicle abnormal lane change control includes:
acquiring the current lateral state values and the target lines, wherein each lateral state value is preconfigured to correspond to a different target line;
determining a desired trajectory of the autonomous vehicle from the target line;
performing preview tracking control on the autonomous vehicle based on the desired trajectory to obtain a target steering wheel angle that satisfies the first and second conditions; and
and controlling the automatic driving vehicle to carry out abnormal lane changing of the vehicle according to the target steering wheel angle.
5. The lateral control method of an autonomous vehicle as recited in claim 4, wherein the each lateral state value being preconfigured to correspond to a different one of the target lines comprises:
when the transverse state value is a first numerical value, the target line is the center line of the current lane;
when the transverse state value is a second numerical value, the target line is a left lane central line;
when the transverse state value is a third numerical value, the target line is the center line of the right lane;
when the transverse state value is a fourth numerical value, the target line is a dynamic deviation line of the current lane;
when the transverse state value is a fifth numerical value, the target line is a lane crossing dynamic deviation line;
when the transverse state value is a sixth numerical value, the target line is a left safety offset line; and
and when the transverse state value is a seventh numerical value, the target line is a right safety offset line.
6. The lateral control method of an autonomous vehicle as recited in claim 4, wherein the pre-aim tracking control of the autonomous vehicle based on the desired trajectory to obtain a target steering wheel angle comprises:
determining a preview point;
calculating the distance between the point closest to the pre-aiming point in the expected track and the pre-aiming point, and taking the distance as a pre-aiming error;
determining a transfer function relation between the preview error and a steering wheel corner according to a vehicle dynamic model, a motion rule, a preview distance and a vehicle speed of the automatic driving vehicle; and
and calculating the target steering wheel rotation angle corresponding to the current preview error according to the transfer function relation.
7. A lateral control system for an autonomous vehicle, comprising:
the system comprises a receiving module, a judging module and a judging module, wherein the receiving module is used for receiving decision information which is output by a decision system of the automatic driving vehicle and relates to the expected transverse behavior of the vehicle, and the expected transverse behavior comprises any one of lane keeping, normal lane changing of the vehicle and abnormal lane changing of the vehicle; and
a control module for responding to the decision information and correspondingly executing any one of the following modules:
a lane keeping control module for performing lane keeping control, wherein a target steering wheel angle matching the lane keeping control is determined based on a pre-line road curvature, a current course angle deviation, and a current lateral position deviation of the autonomous vehicle, and satisfies:
a first condition that the current course angle deviation and the current transverse position deviation are 0; and
a second condition, enabling the curvature of the pre-aiming road to reach the optimal curvature of the road, wherein the error between the actual running track and the expected track of the vehicle is minimum;
the vehicle normal lane changing control module is used for executing vehicle normal lane changing control, wherein a target steering wheel rotating angle matched with the execution of the vehicle normal lane changing control is determined based on the vehicle speed, the current transverse position deviation and the current course angle deviation;
and the vehicle abnormal lane changing control module is used for executing vehicle abnormal lane changing control, wherein a target steering wheel rotating angle matched with the execution of the vehicle abnormal lane changing control is determined based on a current transverse state value of a vehicle and a target line to be moved corresponding to the current transverse state value, and the first condition and the second condition are met.
8. The lateral control system of an autonomous vehicle as recited in claim 7, wherein the lane-keeping control module comprises:
the lane keeping obtaining submodule is used for obtaining the current course angle deviation, the current transverse position deviation and the pre-aiming road curvature;
a first controller for inputting the pre-addressed road curvature and outputting a first target steering wheel angle at which the pre-addressed road curvature reaches the optimal road curvature;
a second controller configured to input the current lateral position deviation and output a second target steering wheel angle at which the current lateral position deviation is 0;
a third controller for inputting the current course angle deviation and outputting a third target steering wheel angle at which the current course angle deviation is 0;
a first steering wheel turn angle determining submodule, configured to determine a final target steering wheel turn angle according to the first target steering wheel turn angle, the second target steering wheel turn angle, and the third target steering wheel turn angle; and
and the lane keeping control submodule is used for controlling the automatic driving vehicle to keep a lane according to the final target steering wheel turning angle.
9. The lateral control system of an autonomous vehicle of claim 8,
the first controller is configured to establish a mapping relationship between the target steering wheel angle and the pre-line road curvature based on ackermann steering principles; and/or
The second controller is configured to determine a control coefficient of the second controller for fuzzy PID control according to the real-time vehicle speed of the autonomous vehicle.
10. The lateral control system of an autonomous vehicle as recited in claim 7, wherein the vehicle abnormal lane change control module comprises:
the abnormal lane changing obtaining submodule is used for obtaining the current horizontal state value and the target line, wherein each horizontal state value is preconfigured to correspond to different target lines;
an expected trajectory determination submodule for determining an expected trajectory of the autonomous vehicle based on the target line;
a second steering wheel angle determination submodule configured to perform preview tracking control on the autonomous vehicle based on the desired trajectory to obtain a target steering wheel angle that satisfies the first condition and the second condition; and
and the abnormal lane changing control submodule is used for controlling the automatic driving vehicle to carry out abnormal lane changing of the vehicle according to the target steering wheel angle.
11. The lateral control system of an autonomous vehicle of claim 10, wherein the each lateral state value preconfigured to correspond to a different one of the target lines comprises:
when the transverse state value is a first numerical value, the target line is the center line of the current lane;
when the transverse state value is a second numerical value, the target line is a left lane central line;
when the transverse state value is a third numerical value, the target line is the center line of the right lane;
when the transverse state value is a fourth numerical value, the target line is a dynamic deviation line of the current lane;
when the transverse state value is a fifth numerical value, the target line is a lane crossing dynamic deviation line;
when the transverse state value is a sixth numerical value, the target line is a left safety offset line; and
and when the transverse state value is a seventh numerical value, the target line is a right safety offset line.
12. The lateral control method of an autonomous vehicle as set forth in claim 10, wherein the second steering wheel angle determining submodule includes:
the first calculation submodule is used for determining a preview point, calculating the distance between the point, closest to the preview point, in the expected track and the preview point, and taking the distance as a preview error; and
and the second calculation submodule is used for determining a transfer function relationship between the preview error and the steering wheel corner according to a vehicle dynamic model, a motion rule, a preview distance and a vehicle speed of the automatic driving vehicle, and calculating a target steering wheel corner corresponding to the current preview error according to the transfer function relationship.
13. A machine-readable storage medium having instructions stored thereon for causing a machine to perform the lateral control method of an autonomous vehicle of any of claims 1 to 6.
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CN114291094A (en) * 2021-12-28 2022-04-08 清华大学苏州汽车研究院（相城） Road condition perception response system and method based on automatic driving
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