SCIENCE CHINA Information Sciences, Volume 60, Issue 1: 013201(2017) https://doi.org/10.1007/s11432-016-0310-1

Regional path moving horizon tracking controller design for autonomous ground vehicles

More info
  • ReceivedMay 12, 2016
  • AcceptedSep 29, 2016
  • PublishedNov 21, 2016


A novel regional path tracking description is presented in this manuscript, and the moving horizon control method that is model predictive control (MPC) is proposed to discuss the regional path tracking issue which could avoid colliding road boundary when tracking a more complex road effectively. The feasible region for autonomous ground vehicles (AGVs) running is determined first according to the detected road boundaries. Then, in order to keep the actual trajectory of AGVs in the region and satisfy the safety requirements, MPC method is employed to design the path tracking controller considering actuator and road boundary constraints. In order to verify the effectiveness of the proposed method, experiments based on Hongqi AGV HQ430 are carried out, and the results illustrate that the presented method could be successfully applied to Hongqi AGV vehicle HQ 430.

Funded by

Project of the Education Department of Jilin Province(2016-429)

National Nature Science Foundation of China(61520106008)

National Nature Science Foundation of China(61403158)



This work was supported by National Nature Science Foundation of China (Grant Nos. 61520106008, 61403158) and Project of the Education Department of Jilin Province (Grant No. 2016-429).


[1] Duan H B, Liu S Q. {Unmanned air/ground vehicles heterogeneous cooperative techniques: current status and prospects}. Sci China Tech Sci, 2010, 53: 1349-1355 CrossRef Google Scholar

[2] Lapierre L, Jouvencel B. {Robust nonlinear path-following control of an auv}. IEEE J Ocean Eng, 2008, 33: 89-102 CrossRef Google Scholar

[3] Snider J M. {Automatic steering methods for autonomous automobile path tracking}. Dissertation for Master Degree. Pittsburgh: Robotics Institute, Carnegie Mellon University, 2009. 10--21. Google Scholar

[4] Zhang K, Cui S M, Wang J F. {Intelligent vehicle's path tracking control based on self-adaptive RBF network compensation}. Contl Decis, 2014, 29: 627-631 Google Scholar

[5] Zhao X J, Liu H O, Jiang Y, et al. {Backstepping adaptive sliding mode control for automatic steering of intelligent vehicles}. Adv Sci Lett, 2012, 6: 696-701 CrossRef Google Scholar

[6] Shim T, Adireddy G, Yuan H L. {Autonomous vehicle collision avoidance system using path planning and model-predictive-control-based active front steering and wheel torque control}. P I Mech Eng D-J Aut, 2012, 226: 767-778 CrossRef Google Scholar

[7] Xiong L, Yu Z P, Wang Y, et al. {Vehicle dynamics control of four inwheel motor drive electric vehicle using gain scheduling based on tyre cornering stiffness estimation}. Vehicle Syst Dyn, 2012, 50: 831-846 CrossRef Google Scholar

Copyright 2020 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1       京公网安备11010102003388号