A path tracking control method for an autonomous vehicle

Abstract

The present invention discloses a path tracking control method for an autonomous vehicle, which includes: 1) establishing a path tracking model of the controlled autonomous vehicle; 2) introducing the following generalized nested exponential function as the tracking time-varying rate function; 3) introducing the rate function into the control design, performing error state conversion and defining the error function; 4) designing the controller; and 5) using the designed controller to control the vehicle to achieve path tracking. This method avoids complicated parameter tuning work, does not require knowledge of precise vehicle parameters, has the characteristics of completely suppressing vehicle system uncertainties / interferences and adjusting the tracking error to zero, improves the path tracking accuracy of the controlled vehicle under actual working conditions, introduces the nested exponential function as the tracking rate function, ensures that the vehicle system can quickly respond to changes in the desired heading angle, enables the lateral displacement error to reach and remain within the preset tracking accuracy range within a given time, and improves the reliability of the path tracking control of the controlled vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent driving, and particularly to a path tracking control method for a controlled vehicle. Background Art

[0002] The purpose of path tracking control is to enable an unmanned vehicle to track the trajectory obtained by a planning algorithm. Its main task is to output corresponding control parameters according to the kinematic and dynamic constraints of the vehicle, such as the front wheel steering angle, wheel braking force, etc. Therefore, the path tracking controller plays a key role in the field of intelligent driving technology, and its control performance is directly related to the safety and stability of the controlled vehicle. However, because the controller parameters of autonomous vehicles are vulnerable to the influence of different working states, such as passengers or goods, the parameter uncertainty and external interference of the vehicle greatly affect the vehicle performance. As a result, traditional control methods, such as the PID control method, etc., need to frequently adjust parameters to ensure the applicability of the controller, thus increasing the workload of R & D personnel and the difficulty of controller design. Summary of the Invention

[0003] The purpose of the present invention is to provide a path tracking control method for an autonomous vehicle to solve the technical problem of controlling the vehicle to quickly and accurately track the desired path under the conditions of parameter uncertainty and external interference, and ensuring that the autonomous vehicle reliably tracks the planned path.

[0004] The path tracking control method for the autonomous vehicle of the present invention includes the following steps:

[0005] 1) According to the dynamic model of the controlled autonomous vehicle, establish the path tracking model of the controlled autonomous vehicle as:

[0006]

[0007] Wherein, b = l f C f / I z ; ω n (t) is a disturbance variable, and the coordinate system OXY fixed on the driving road surface is an environmental coordinate system based on the ground, is the first derivative of the longitudinal displacement Y of the controlled vehicle in the environmental coordinate system, that is, is the longitudinal speed of the controlled vehicle, is the yaw angle of the vehicle in the environmental coordinate system; the coordinate system oxy represents the vehicle body coordinate system, the origin o of the coordinate system is fixed at the vehicle center of mass, the oxy plane is the vehicle left - right symmetry plane, the x - axis of the coordinate system is the vehicle longitudinal axis direction, the y - axis of the coordinate system is perpendicular to the vehicle longitudinal axis direction, v x is the longitudinal speed of the vehicle center of mass of the controlled vehicle in the vehicle body coordinate system, v yis the lateral velocity of the center of mass of the controlled vehicle in the vehicle body coordinate system, ω is the yaw angular velocity of the controlled vehicle, and l f is the distance from the front axle of the controlled vehicle to the center of mass, and l r is the distance from the rear axle of the controlled vehicle to the center of mass, and I z is the yaw moment of inertia of the controlled vehicle, and C f is the equivalent cornering stiffness of the front wheels of the controlled vehicle, and C r is the equivalent cornering stiffness of the rear wheels of the controlled vehicle, and δ f is the front wheel steering angle of the controlled vehicle in the vehicle body coordinate system, and β = arctan(v y / v x ) is the sideslip angle of the center of mass of the controlled vehicle in the vehicle body coordinate system;

[0008] Define the relationship between the desired yaw angle and the actual yaw angle of the controlled vehicle in the environmental coordinate system as:

[0009]

[0010] In the formula, Y e is the lateral displacement deviation between the controlled vehicle and the desired path, and Y e = Y - Y ref , c 0 and c 1 are design parameters, and at the same time satisfy that when π > c 0 > 0, c 1 > 0. After sorting, the following control system is obtained:

[0011]

[0012] In the formula, x 2 = ω, y is the system output; u is the system input, and u = δ f ; The f function is used as the total disturbance of the system;

[0013] 2) Introduce the following generalized nested exponential function as the tracking rate function:

[0014] v dm (t) = exp(d m (...exp(d 2 (exp(d 1 t) - 1))... - 1)) (12)

[0015] Among them, d i > 0 is the parameter of the i-th generalized nested exponential function. When d i = 1, the generalized nested exponential function is a nested exponential function, and the subscript i = 1,..., m;

[0016] 3) Introduce the rate function into the control design, perform the following error state conversion, and define the error function:

[0017]

[0018] where,

[0019] 4) Design the controller, and the expression of the controller u is

[0020]

[0021] where, θ, k and k 1 are set constants, b is a constant satisfying 0 ≤ b ≤ b, and the expressions of other variables are as follows:

[0022] z = w 2 +L 1 w 1 (15)

[0023] where, L 1 is a set coefficient constant, and its value range is (0, 1).

[0024]

[0025] 5) Use the designed controller u to control the vehicle to achieve path tracking.

[0026] Advantages of the present invention: The path tracking control method of this autonomous vehicle uses a time-varying feedback gain through a time-varying rate function v dm (t), thus eliminating the need for complex parameter tuning and precise vehicle parameters. It has the characteristics of completely suppressing (rather than partially attenuating) vehicle system uncertainties / interferences and adjusting the tracking error to zero, improving the path tracking control accuracy of the controlled vehicle under actual working conditions. A nested exponential function is introduced into the time-varying rate function, ensuring that the vehicle system can quickly respond to changes in the desired yaw angle, enabling the lateral displacement error to reach and remain within the preset tracking accuracy range within a given time, and improving the reliability of the path tracking control of the controlled vehicle. Description of the Drawings

[0027] Figure 1 is a schematic diagram of the controlled vehicle in the environmental coordinate system and the vehicle body coordinate system.

[0028] Figure 2 is a comparison diagram of the yaw angle changes when the vehicle is controlled using the traditional PID control method and the control method of the present invention.

[0029] Figure 3It is a comparison chart of the change in the yaw angle tracking error when controlling a vehicle using the traditional PID control method and the control method of the present invention.

[0030] Figure 4 It is a comparison chart of the actual track and the desired track of the vehicle when controlling the vehicle using the traditional PID control method and the control method of the present invention.

[0031] Figure 5 It is a comparison chart of the change in the lateral displacement error of the vehicle when controlling the vehicle using the traditional PID control method and the control method of the present invention. Detailed implementation manners

[0032] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0033] As shown in the figure, the path tracking control method of the autonomous vehicle in this embodiment includes the following steps:

[0034] The path tracking control method of the autonomous vehicle includes the following steps:

[0035] 1) According to the dynamic model of the controlled autonomous vehicle, establish the path tracking model of the controlled autonomous vehicle as:

[0036]

[0037] Among them, b = l f C f / I z ; ω n (t) is a disturbance variable, and the coordinate system OXY fixed on the driving road surface is the environmental coordinate system based on the ground. It is the first derivative of the longitudinal displacement Y of the controlled vehicle in the environmental coordinate system, that is It is the longitudinal speed of the controlled vehicle. It is the yaw angle of the vehicle in the environmental coordinate system; the coordinate system oxy represents the vehicle body coordinate system, the origin o of the coordinate system is fixed at the vehicle center of mass, the oxy plane is the vehicle left-right symmetry plane, the x-axis of the coordinate system is the vehicle longitudinal axis direction, the y-axis of the coordinate system is perpendicular to the vehicle longitudinal axis direction, v x It is the longitudinal speed of the center of mass of the controlled vehicle in the vehicle body coordinate system, v y It is the lateral speed of the center of mass of the controlled vehicle in the vehicle body coordinate system, ω is the yaw angular velocity of the controlled vehicle, l f It is the distance from the front axle of the controlled vehicle to the center of mass, l r is the distance from the rear axle of the controlled vehicle to the center of mass, I z is the yaw moment of inertia of the controlled vehicle, C f is the equivalent cornering stiffness of the front wheels of the controlled vehicle, C r is the equivalent cornering stiffness of the rear wheels of the controlled vehicle, δf is the front wheel steering angle of the controlled vehicle in the vehicle body coordinate system, β = arctan(v y v x ).) is the sideslip angle of the center of mass of the controlled vehicle in the vehicle body coordinate system.

[0038] Define the desired yaw angle of the controlled vehicle in the environmental coordinate system and the actual yaw angle The relationship is:

[0039]

[0040] In the formula, Y e is the lateral displacement deviation between the controlled vehicle and the desired path, Y e = Y - Y ref , c 0 and c 1 are design parameters, and at the same time satisfy that when π > c 0 > 0, c 1 > 0, after sorting out, the following control system is obtained:

[0041]

[0042] In the formula, x 2 = ω, y is the system output; u is the system input, u = δ f ; The f function is used as the total disturbance of the system.

[0043] 2) Introduce the following generalized nested exponential function as the tracking rate function:

[0044] v dm (t) = exp(d m (... exp(d 2 (exp(d 1 t) - 1))... - 1)) (20)

[0045] Among them, d i > 0 (i = 1,..., m) is the parameter of the i-th generalized nested exponential function. When d i = 1 (i = 1,..., m), the generalized nested exponential function is a nested exponential function.

[0046] 3) Introduce the rate function into the control design, perform the following error state conversion, and define the error function:

[0047]

[0048] In the formula,

[0049] 4) Design a controller, and the expression of the controller u is

[0050]

[0051] where θ, k, and k 1 are set constants, b is a constant that satisfies 0 ≤ b ≤ |b|, and the expressions of other variables are as follows:

[0052] z = w 2 + L 1 w 1 (23)

[0053] where L 1 is a set coefficient constant, and its value range is (0, 1),

[0054]

[0055] 5) Use the designed controller u to control the vehicle to achieve path tracking.

[0056] Use the method proposed in this embodiment and the traditional PID control method to perform simulation path tracking control on an autonomous vehicle in the case of a curved path. The simulation results are as Figures 2 - 5 shown. Figure 2 For the comparison of the yaw angles of the two control methods, it can be seen that this control method enables the yaw angle of the controlled vehicle to reach a smooth and stable state faster, while the PID control method reaches stability after a longer fluctuation time; Figure 3 For the comparison of the yaw angle tracking errors of the two control methods, it can be seen that this control method can basically achieve stable error-free output at 1 s, while the PID control method has large error fluctuations. Although the error order of magnitude is already very small, the error cannot be completely eliminated; Figure 4 For the comparison of the actual tracking path and the desired path obtained by the two control methods, it can be seen that the tracking path obtained by this control method is more consistent with the desired path; Figure 5 For the comparison of the lateral displacement tracking error Y e = Y - Y ref of the two control methods, it can be seen that the displacement error of this control method can tend to zero faster and more smoothly, while the error of the PID control method has large fluctuations and always exists. Therefore, this control method has better control effects in terms of faster response speed, higher accuracy, better stability, and smoother performance compared with the traditional PID method.

Claims

1. A path tracking control method for an autonomous vehicle, comprising the following steps: 1) Based on the dynamic model of the controlled autonomous vehicle, establish the path tracking model of the controlled autonomous vehicle as: Among them, b = l f C f / I z ; ω n (t) is a disturbance variable. The coordinate system OXY fixed on the driving road surface is an environmental coordinate system based on the ground. is the first derivative of the longitudinal displacement Y of the controlled vehicle in the environmental coordinate system, that is, is the longitudinal speed of the controlled vehicle. is the yaw angle of the vehicle in the environmental coordinate system; the coordinate system oxy represents the vehicle body coordinate system. The origin o of the coordinate system is fixed at the vehicle's center of mass. The oxy plane is the vehicle's left - right symmetry plane. The x - axis of the coordinate system is in the longitudinal direction of the vehicle, and the y - axis of the coordinate system is perpendicular to the longitudinal direction of the vehicle. v x is the longitudinal speed of the center of mass of the controlled vehicle in the vehicle body coordinate system. v y is the lateral speed of the center of mass of the controlled vehicle in the vehicle body coordinate system. ω is the yaw angular velocity of the controlled vehicle. l f is the distance from the front axle of the controlled vehicle to the center of mass. l r is the distance from the rear axle of the controlled vehicle to the center of mass. I z is the yaw moment of inertia of the controlled vehicle. C f is the equivalent cornering stiffness of the front wheels of the controlled vehicle. C r is the equivalent cornering stiffness of the rear wheels of the controlled vehicle. δ f is the front wheel angle of the controlled vehicle in the vehicle body coordinate system. β = arctan(v y / v x ) is the sideslip angle of the center of mass of the controlled vehicle in the vehicle body coordinate system. Define the desired yaw angle of the controlled vehicle in the environmental coordinate system and the actual yaw angle The relationship is as follows: where Y e is the lateral displacement deviation between the controlled vehicle and the desired path, and Y e = Y - Y ref , c 0 and c 1 are design parameters, and simultaneously satisfy that when π > c 0 > 0, c 1 > 0, and after arrangement, the following control system is obtained: In the formula, x 2 = ω, y is the system output; u is the system input, u = δ f ; The f function is used as the total disturbance of the system; 2) Introduce the following generalized nested exponential function as the tracking rate function: v dm (t) = exp(d m (...exp(d 2 (exp(d 1 t) - 1))... - 1)) (4) where d i > 0 is the parameter of the i-th generalized nested exponential function. When d i = 1, the generalized nested exponential function is a nested exponential function, and the subscript i = 1, …, m; 3) Introduce the rate function into the control design, perform the following error state transformation, and define the error function: In the formula, 4) Design the controller, and the expression of the controller u is where θ, k, and k 1 are set constants, b is a constant that satisfies 0 ≤ b ≤ |b|, and the other variable expressions are as follows: z = w 2 + L 1 w 1 (7) where L 1 is a set coefficient constant with a value range of (0, 1). 5) Use the designed controller u to control the vehicle to achieve path tracking.

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