Abstract
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.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call