Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)

arXiv — cs.CV•Tuesday, October 28, 2025 at 4:00:00 AM

The recent advancements in reinforcement learning, particularly with the introduction of Raw2Drive, are paving the way for more effective end-to-end autonomous driving solutions. This approach addresses the challenges of traditional imitation learning by reducing causal confusion and distribution shifts, making it a significant step forward in the field. As the industry continues to evolve, these developments could lead to safer and more reliable autonomous vehicles, which is crucial for the future of transportation.

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