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Research questionHow can end-to-end autonomous-driving world models use surround-view inputs without costly future-video generation at inference?World models can predict future scene dynamics for driving, but generating future videos during deployment is computationally expensive. Using only a front camera reduces spatial coverage for maneuvers such as lane changes, merges, and turns.
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Latest papersRecent research connected to this question, newest first.SV-WAM: An Efficient Surround-View World-Action Model for End-to-End Autonomous DrivingThe source describes a shared generative model trained with future-video supervision but deployed for action-only planning, using six-camera observations. Evidence is reported on the closed-loop NAVSIMv2 and open-loop nuScenes benchmarks, including planning performance, inference latency, boundary awareness, and zero-shot transfer.research paper · Sep 3, 2026
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