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MPC-based path tracking with PID speed control for high-speed autonomous vehicles considering time-optimal travel

基于 MPC 的考虑时间最优速度的高速无人驾驶车辆路径跟踪和 PID 速度控制

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Abstract

In order to track the desired path as fast as possible, a novel autonomous vehicle path tracking based on model predictive control (MPC) and PID speed control was proposed for high-speed automated vehicles considering the constraints of vehicle physical limits, in which a forward-backward integration scheme was introduced to generate a time-optimal speed profile subject to the tire-road friction limit. Moreover, this scheme was further extended along one moving prediction window. In the MPC controller, the prediction model was an 8-degree-of-freedom (DOF) vehicle model, while the plant was a 14-DOF vehicle model. For lateral control, a sequence of optimal wheel steering angles was generated from the MPC controller; for longitudinal control, the total wheel torque was generated from the PID speed controller embedded in the MPC framework. The proposed controller was implemented in MATLAB considering arbitrary curves of continuously varying curvature as the reference trajectory. The simulation test results show that the tracking errors are small for vehicle lateral and longitudinal positions and the tracking performances for trajectory and speed are good using the proposed controller. Additionally, the case of extended implementation in one moving prediction window requires shorter travel time than the case implemented along the entire path.

摘要

为了尽可能快地跟踪期望路径, 提出一种新的基于模型预测控制(MPC)和 PID 速度控制方法, 考虑高速无人驾驶车辆的物理约束, 通过前向后向积分策略生成轮胎路面附着极限内的时间最优速度曲线, 并将该方法进一步扩展应用于单个滚动预测窗口中. 在 MPC 算法框架的设计中, 以 8 自由度车辆模型作为预测模型, 以高置信度的 14 自由度车辆模型作为被控对象, 对于横向控制, 通过 MPC 控制器生成最优的前轮转角, 对于纵向控制, 通过嵌入模型预测控制优化求解中的 PID 控制器生成总的车辆驱动/制动力矩. 以任意连续变化曲率的路径为参考轨迹, 在 MATLAB 中实现所提出的控制器, 仿真结果表明车辆的横向位置和纵向位置的跟踪误差较小, 通过车轮转角、 车轮驱动/制动力矩的联合控制, 车辆的轨迹跟踪和速度跟踪性能良好. 另外, 将最优速度曲线生成方法进一步扩展应用于单个滚动预测窗口中, 其所需路径跟踪的时间比在整个路径上应用该策略时需要的时间短.

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Acknowledgments

This paper is funded by International Graduate Exchange Program of Beijing Institute of Technology. The authors also gratefully thank the reviewers for their valuable suggestions.

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  1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China

    Shu-ping Chen  (陈舒平), Guang-ming Xiong  (熊光明) & Hui-yan Chen  (陈慧岩)

  2. Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA

    Dan Negrut

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CHEN Shu-ping wrote the original draft of the manuscript and conducted the creation of the models and simulation analysis. XIONG Guang-ming reviewed and edited the draft of the manuscript. CHEN Hui-yan supervised and leaded the research activity. NEGRUT Dan provided the concept and goals of the manuscript.

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Correspondence to Guang-ming Xiong  (熊光明).

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CHEN Shu-ping, XIONG Guang-ming, CHEN Hui-yan and NEGRUT Dan declare that they have no conflict of interest.

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Foundation item: Project(20180608005600843855-19) supported by the International Graduate Exchange Program of Beijing Institute of Technology, China

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Chen, Sp., Xiong, Gm., Chen, Hy. et al. MPC-based path tracking with PID speed control for high-speed autonomous vehicles considering time-optimal travel. J. Cent. South Univ. 27, 3702–3720 (2020). https://doi.org/10.1007/s11771-020-4561-1

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