Adaptive coordinated collision avoidance control of autonomous ground vehicles

作者：Guo, Jinghua^*; Luo, Yugong; Li, Keqiang

来源：Proceedings of the Institution of Mechanical Engineers Part I-Journal of Systems and Control Engineering, 2018, 232(9): 1120-1133.

DOI：10.1177/0959651818774991

• Autonomous ground vehicles
• collision avoidance
• adaptive neural network-based backstepping control
• coupled dynamics
• uncertainties

This article presents a novel coordinated nonlinear adaptive backstepping collision avoidance control strategy for autonomous ground vehicles with uncertain and unmodeled terms. A nonlinear vehicle collision avoidance vehicle model which describes the coupled lateral and longitudinal dynamic features of autonomous ground vehicles is constructed. Then, a modified artificial potential field approach which can ensure that the total potential field of the target is goal minimum, is proposed to produce a collision-free trajectory for autonomous ground vehicles in real-time. Furthermore, in order to handle with the features of coupled and parameter uncertainties of autonomous ground vehicles, an adaptive neural network-based backstepping trajectory tracking control approach is proposed for collision avoidance control system of autonomous ground vehicles, and the stability of this proposed control system is proven by the Lyapunov theory. Finally, the co-simulation and experimental tests are implemented and the results show that the proposed collision avoidance control strategy has excellent tracking performance.

• 出版日期2018-10
• 单位清华大学; 厦门大学