Open access
2026
Extensive Exploration in Highway Overtaking Scenarios Using Hierarchical Reinforcement Learning
A hierarchical reinforcement learning framework for autonomous highway driving that decomposes delayed-reward highway overtaking decision making into interpretable subtasks and achieves more reliable trap-escape performance than other hierarchical structures, including h-DQN and HIRO.
Zhihao Zhang, Ekim Yurtsever, K. Redmill
· IEEE Access · 0 citations