Preprint
Aug 2026
Knowledge-Data-Dual-Driven Reinforcement Learning for Autonomous Vehicle Control in Mixed Traffic
This work proposes Knowledge-Data Dual-driven Reinforcement Learning (KDDRL), a conditional deep generative model that effectively handles intention uncertainty, accelerates training convergence, and outperforms conventional baseline methods in terms of safety, efficiency, and comfort.
Jie Fang, Wei Zheng, Mengyun Xu et al.
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