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7 papers · 1 filter

cs.CV2025

Future-Aware End-to-End Driving: Bidirectional Modeling of Trajectory Planning and Scene Evolution

Bozhou Zhang, Nan Song, Jingyu Li +3

End-to-end autonomous driving methods aim to directly map raw sensor inputs to future driving actions such as planned trajectories, bypassing traditional modular pipelines. While t…

cs.CV2025

LMAD: Integrated End-to-End Vision-Language Model for Explainable Autonomous Driving

Nan Song, Bozhou Zhang, Xiatian Zhu +2

Large vision-language models (VLMs) have shown promising capabilities in scene understanding, enhancing the explainability of driving behaviors and interactivity with users. Existi…

cs.RO2025

Relative Position Matters: Trajectory Prediction and Planning with Polar Representation

Bozhou Zhang, Nan Song, Bingzhao Gao +1

Trajectory prediction and planning in autonomous driving are highly challenging due to the complexity of predicting surrounding agents' movements and planning the ego agent's actio…

cs.CV2025

Perception in Plan: Coupled Perception and Planning for End-to-End Autonomous Driving

Bozhou Zhang, Jingyu Li, Nan Song +1

End-to-end autonomous driving has achieved remarkable advancements in recent years. Existing methods primarily follow a perception-planning paradigm, where perception and planning…

cs.CV2025

DeMo++: Motion Decoupling for Autonomous Driving

Bozhou Zhang, Nan Song, Xiatian Zhu +1

Motion forecasting and planning are tasked with estimating the trajectories of traffic agents and the ego vehicle, respectively, to ensure the safety and efficiency of autonomous d…

cs.CV2025

RealEngine: Simulating Autonomous Driving in Realistic Context

Junzhe Jiang, Nan Song, Jingyu Li +2

Driving simulation plays a crucial role in developing reliable driving agents by providing controlled, evaluative environments. To enable meaningful assessments, a high-quality dri…

cs.RO2025

Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning

Bozhou Zhang, Nan Song, Xin Jin +1

End-to-end autonomous driving unifies tasks in a differentiable framework, enabling planning-oriented optimization and attracting growing attention. Current methods aggregate histo…