most citedHierarchical End-to-End Autonomous Driving: Integrating BEV Perception with Deep Reinforcement Learning

1 citations · 1 across the 2 of their papers we have counts for

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cs.AI2025

ME-BEV: Mamba-Enhanced Deep Reinforcement Learning for End-to-End Autonomous Driving with BEV-Perception

Siyi Lu, Run Liu, Dongsheng Yang +1

Autonomous driving systems face significant challenges in perceiving complex environments and making real-time decisions. Traditional modular approaches, while offering interpretab…

cs.AI2024★ 1 cited

Hierarchical End-to-End Autonomous Driving: Integrating BEV Perception with Deep Reinforcement Learning

Siyi Lu, Lei He, Shengbo Eben Li +3

End-to-end autonomous driving offers a streamlined alternative to the traditional modular pipeline, integrating perception, prediction, and planning within a single framework. Whil…