2026
Online Policy Adaptation for Personalized Lane-Keeping via Driver Intervention Guided Reinforcement Learning
RA-L 2026
Learning-based online adaptive driving policies hold considerable promise for enabling human-preferred autonomous driving or advanced driver assistance systems. However, existing personalization approaches often rely on limited style definitions or behavior cloning, requiring extensive data and plac