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International Journal of Automotive Technology > Volume 23(5); 2023 > Article
International Journal of Automotive Technology 2023;23(5): 1239-1253.
doi: https://doi.org/10.1007/s12239-022-0109-8
PATH PLANNING AND PATH TRACKING FOR AUTONOMOUS VEHICLE BASED ON MPC WITH ADAPTIVE DUAL-HORIZON-PARAMETERS
Yaohua Li , Jikang Fan , Yang Liu , Xiaoyu Wang
Chang’an University
PDF Links Corresponding Author.  Yaohua Li  , Email. yaohua.li@chd.edu.cn
ABSTRACT
According to the position relationship between the vehicle and the obstacle, a new obstacle avoidance path planner was designed to solve the limitation of traditional local obstacle avoidance path planner in excessive obstacle avoidance. In order to improve the control accuracy of the path tracking controller and ensure the stability of the vehicle, a comprehensive evaluation index of path tracking performance considering control accuracy and driving stability was established. The optimal prediction time domain and control time domain parameters at different vehicle speeds were obtained, and an adaptive dual time domain parameter path tracking controller was designed. Based on the joint-simulation platform, the integrated structure of the planning layer and the control layer was simulated and verified. Simulation results show that the new obstacle avoidance function can avoid excessive obstacle avoidance while ensuring real-time performance, and improve the driving stability of the vehicle. The adaptive time-domain parameter path tracking controller has better comprehensive control performance and can improve driving safety under extreme conditions. The integrated structure of local obstacle avoidance path planning and path tracking control are beneficial for the vehicle to plan and accurately track the local obstacle avoidance path in multiple static obstacle scenes.
Key Words: Autonomous vehicles, Model predictive control, Obstacle avoidance, Local path planning, Path tracking
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