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International Journal of Automotive Technology > Volume 24(1); 2023 > Article
International Journal of Automotive Technology 2023;24(1): 63-78.
doi: https://doi.org/10.1007/s12239-023-0007-8
Zhigen Nie 1, Zhongliang Li 2, Wanqiong Wang 1, Yufeng Lian 3, Rachid Outbib 2
1Faculty of Transportation Engineering, Kunming University of Science and Technology
2LIS Lab (UMR CNRS 7020), Aix-Marseille University
3School of Electrical and Electronic Engineering, Changchun University of Technology
PDF Links Corresponding Author.  Zhigen Nie  , Email. niezhigen@kust.edu.cn
Dynamic trajectory planning (DTP) and Dynamic trajectory tracking (DTT) are the real-time mutual coupling in the process of the dynamic lateral obstacle avoidance (DLOA) of connected and automated vehicles (CAVs). Meanwhile, the varying velocity and acceleration of obstacle vehicles (OVs) increase the difficulties of DTP. Furthermore, the parameters perturbation in CAVs (such as mass and cornering stiffness), the varying velocities of CAVs and the signal disturbances, raise the difficulties of DTT. Therefore, the DLOA is challenging due to the interaction of the above multiple factors. To address the problem, this paper proposes a robust gain-scheduling control strategy of DLOA for CAVs. The strategy is divided into two modules namely DTP and DTT, and the two modules cooperate with each other in real time. In the module of DTP, the optimal trajectory considering the efficiency, passenger comfort and safety is real-time optimized in the dynamic safe limit which is real time predicted according to the information from CAVs and OVs. In the module of DTT, the real-time trajectory reference is tracked. Robust gain-scheduling control is realized to cope with variation of real-time trajectory reference, varying velocity, parameters perturbation and signal disturbances during the process of DLOA. The simulation results indicate that the strategy can effectively achieve DLOA maintaining the vehicle stability across various working conditions.
Key Words: Connected and automated vehicles (CAVs), Lateral obstacle avoidance, Trajectory planning and tracking, Robust control, Parameter perturbation, Linear parameter varying (LPV)
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