From the 2 of 9 linked papers with an AI index.
1 citations · 1 across the 3 of their papers we have counts for
9 papers
Expert Knowledge-driven Reinforcement Learning for Autonomous Racing via Trajectory Guidance and Dynamics Constraints
Bo Leng, Weiqi Zhang, Zhuoren Li +4
The paper introduces TraD‑RL, a reinforcement‑learning framework for autonomous racing that uses expert racing lines for state augmentation and reward shaping, and incorporates veh…
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…
A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective
Zhuoren Li, Guizhe Jin, Ran Yu +8
Reinforcement learning (RL), with its ability to explore and optimize policies in complex, dynamic decision-making tasks, has emerged as a promising approach to addressing motion p…
FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving
Baoyun Wang, Zhuoren Li, Ran Yu +6
End-to-end diffusion planning has shown strong potential for autonomous driving, but the physical feasibility of generated trajectories remains insufficiently addressed. In particu…
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…
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…