4 papers
UniUncer: Unified Dynamic Static Uncertainty for End to End Driving
Yu Gao, Jijun Wang, Zongzheng Zhang +7
End-to-end (E2E) driving has become a cornerstone of both industry deployment and academic research, offering a single learnable pipeline that maps multi-sensor inputs to actions w…
DiffVLA++: Bridging Cognitive Reasoning and End-to-End Driving through Metric-Guided Alignment
Yu Gao, Anqing Jiang, Yiru Wang +7
Conventional end-to-end (E2E) driving models are effective at generating physically plausible trajectories, but often fail to generalize to long-tail scenarios due to the lack of e…
FlowDrive: Energy Flow Field for End-to-End Autonomous Driving
Hao Jiang, Zhipeng Zhang, Yu Gao +11
Recent advances in end-to-end autonomous driving leverage multi-view images to construct BEV representations for motion planning. In motion planning, autonomous vehicles need consi…
SparseMeXT Unlocking the Potential of Sparse Representations for HD Map Construction
Anqing Jiang, Jinhao Chai, Yu Gao +10
Recent advancements in high-definition \emph{HD} map construction have demonstrated the effectiveness of dense representations, which heavily rely on computationally intensive bird…