Research on Intelligent Vehicle Trajectory Tracking Coordination Control Method Based on Extension Game

doi:10.3901/JME.2022.08.181

Abstract

Abstract: For the problems of intelligent vehicle under high-speed cornering conditions, large trajectory tracking errors and lateral stability cannot be guaranteed, an extension game trajectory tracking coordination control method is proposed, which combines extension zone switching control and game coordination. It breaks the working condition adaptability of a single control strategy and the jitter problem of multiple strategy switching control. The proposed method is based on a hierarchical control system, which decomposes the trajectory tracking control into an upper measurement pattern recognition layer and a lower game coordination layer. Based on the extension theory, the upper layer proposes a parallel extension measurement pattern recognition strategy, and maps the real-time state of the vehicle-road system to the corresponding three measurement modes:classic domain, extension domain, and non-domain in extension control architecture. The lower layer designs three control strategies corresponding to different measurement modes. The real-time policy switching is performed based on the recognition results of upper measurement modes. The game coordination method is introduced to coordinate the parallel extension weights, which effectively avoids the jitter problem caused by mode switching control. The joint simulation model is established by Simulink/Carsim, and the algorithm is compared and verified in the double-shift and "8-shaped" with time-varying curvature and high-speed conditions. Compared with the Proportion- Integral-Derivative(PID) control method, the proposed method improves the average tracking error accuracy by 45.08%, especially under bad working conditions with sudden changes in curvature, vehicle stability is improved by 44%. Finally, the intelligent vehicle experiment platform is used for comparison and verification, which has strong guiding significance and reference value for designing high-speed trajectory tracking control strategies for intelligent vehicles.

Key words: intelligent vehicles, parallel extension control, correlation function, game coordination control, nash equilibrium solution

CLC Number:

U471

ZANG Yong, CAI Yingfeng, SUN Xiaoqiang, XU Xing, CHEN Long, WANG Hai. Research on Intelligent Vehicle Trajectory Tracking Coordination Control Method Based on Extension Game[J]. Journal of Mechanical Engineering, 2022, 58(8): 181-194.

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