Intelligent Control Switching for Autonomous Vehicles based on Reinforcement Learning
2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)(2022)
摘要
This paper presents the design and implementation of an intelligent switched control for lateral control of autonomous vehicles. The switched control is designed based on Linear Parameter-Varying (LPV) and Youla-Kucera (YK) parameterization. The proposed intelligent system aims to optimize the control switching performance using a Reinforcement Learning (RL) model. The presented approach studies the critical problem of initial or sudden large lateral errors in lane-tracking or lane-changing. It ensures stable and smooth switching performance to provide a smooth vehicle response regardless of the lateral error. The proposed RL-based switching strategy is validated using a RENAULT simulator on MATLAB, and compared to another modeled switching strategy with encouraging results.
更多查看译文
关键词
lateral control,autonomous vehicles,intelligent system,presented approach studies,initial errors,sudden large lateral errors,lane-tracking,lane-changing,switching performance,smooth vehicle response,lateral error,RL-based switching strategy,modeled switching strategy,intelligent control switching,Reinforcement Learning,intelligent switched control
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要