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cs.RO2026
Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving
Zhexi Lian, Haoran Wang, Xuerun Yan +4
End-to-end autonomous driving is typically built upon imitation learning (IL), yet its performance is constrained by the quality of human demonstrations. To overcome this limitatio…
cs.RO2025
A simulation platform calibration method for automated vehicle evaluation: accurate on both vehicle level and traffic flow level
Jia Hu, Junqi Li, Xuerun Yan +2
Simulation testing is a fundamental approach for evaluating automated vehicles (AVs). To ensure its reliability, it is crucial to accurately replicate interactions between AVs and…
cs.RO2025
MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
Jia Hu, Zhexi Lian, Xuerun Yan +5
Autonomous Driving (AD) vehicles still struggle to exhibit human-like behavior in highly dynamic and interactive traffic scenarios. The key challenge lies in AD's limited ability t…