| Speed-varying path tracking based on model predictive control for autonomous vehicles
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| Shuang Tang 1, Jun Li 1, Wei Zhou 2 |
1School of Mechatronics and Vehicle Engineering , Chongqing Jiaotong University
2Faculty of Intelligence Manufacturing , Yibin University |
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| ABSTRACT |
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In order to improve autonomous vehicles path-tracking accuracy and stability, a lateral–longitudinal coordination pathtracking
control method is proposed. The proposed coordination control consists of path-tracking control and speed tracking
control. First, the desired safety speed is planned according to the known road curvature and adhesion coeffi cient in order
to prevent the tire force saturation. Based on the three-degree-of-freedom (3DOF) vehicle dynamic model and the preview
tracking error model, model predictive control (MPC) theory is adopted to design the speed-varying vehicle path-tracking
controller. Then, the quadratic programming (QP) method is used to solve the objective function with constraints, which
calculates the steering angle to control the vehicle track the reference path. In addition, a PID speed controller is designed to
calculate the torque of each wheel to track the desired speed. Finally, according to the yaw rate error and the vehicle slip angle
error, a yaw moment stability controller based on the fuzzy logic control theory is designed to balance the vehicle stability
and motility. The simulation results based on a Matlab/Carsim platform show that the coordination path-tracking control
method proposed in this paper can eff ectively improve the vehicle tracking accuracy and the stability on diff erent roads. |
| Key Words:
Autonomous vehicles · Path-tracking control · Model predictive control · Lateral–longitudinal coordination control
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Corresponding Author.
Jun Li , Email. 
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