3 papers
cs.RO2026
A Risk-Sensitive and Uncertainty-Aware Decision-Making and Control Framework for Safe and Robust Autonomous Driving
Zhuoren Li, Ran Yu, Weiqi Zhang +4
Reinforcement learning (RL) has demonstrated considerable potential for autonomous driving decision-making. However, its deployment in urban autonomous driving, particularly at hig…
cs.RO2026
Comparison-Based Ordinal Learning for Proactive Driving Risk Assessment
Zhuoren Li, Yi Zhong, Weiqi Zhang +4
Real-time driving risk assessment provides an essential basis for proactive safety by identifying and quantifying the danger of ongoing road interactions before adverse outcomes oc…
cs.RO2026
Expert Knowledge-driven Reinforcement Learning for Autonomous Racing via Trajectory Guidance and Dynamics Constraints
Bo Leng, Weiqi Zhang, Zhuoren Li +4
Reinforcement learning has shown significant potential for autonomous racing, but it still faces challenges such as training instability, inefficient exploration, and unsafe action…