Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving

Ähnliche Einträge

• MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
  von: Hu, Jia, et al.
  Veröffentlicht: (2025)
• XBG: End-to-end Imitation Learning for Autonomous Behaviour in Human-Robot Interaction and Collaboration
  von: Cardenas-Perez, Carlos, et al.
  Veröffentlicht: (2024)
• DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving
  von: Song, Ziying, et al.
  Veröffentlicht: (2025)
• Human-Machine Shared Control Approach for the Takeover of CACC
  von: Wang, Haoran, et al.
  Veröffentlicht: (2024)
• ZTRS: Zero-Imitation End-to-end Autonomous Driving with Trajectory Scoring
  von: Li, Zhenxin, et al.
  Veröffentlicht: (2025)