3 papers
cs.RO2025
An Uncertainty-Weighted Decision Transformer for Navigation in Dense, Complex Driving Scenarios
Zhihao Zhang, Chengyang Peng, Minghao Zhu +2
Autonomous driving in dense, dynamic environments requires decision-making systems that can exploit both spatial structure and long-horizon temporal dependencies while remaining ro…
cs.RO2025
Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving
Zhihao Zhang, Chengyang Peng, Ekim Yurtsever +1
Automated vehicle control using reinforcement learning (RL) has attracted significant attention due to its potential to learn driving policies through environment interaction. Howe…
cs.LG2025
Extensive Exploration in Complex Traffic Scenarios using Hierarchical Reinforcement Learning
Zhihao Zhang, Ekim Yurtsever, Keith A. Redmill
Developing an automated driving system capable of navigating complex traffic environments remains a formidable challenge. Unlike rule-based or supervised learning-based methods, De…