4 papers
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…
Implicit Action Chunking for Smooth Continuous Control
Bosun Liang, Shuo Pei, Zirui Chen +5
Reinforcement learning often produces high-frequency oscillatory control signals that undermine the safety and stability required for physical deployment. Explicit action chunking…
Multi-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous Driving
Guizhe Jin, Zhuoren Li, Bo Leng +3
Reinforcement Learning (RL) is increasingly used in autonomous driving (AD) and shows clear advantages. However, most RL-based AD methods overlook policy structure design. An RL po…
Hybrid Action Based Reinforcement Learning for Multi-Objective Compatible Autonomous Driving
Guizhe Jin, Zhuoren Li, Bo Leng +3
Reinforcement Learning (RL) has shown excellent performance in solving decision-making and control problems of autonomous driving, which is increasingly applied in diverse driving…