DreamStream: Towards Policy-Oriented Generative Simulation for End-to-End Driving
Faithfully evaluating end-to-end driving policies in simulation requires observations that are not merely photo-realistic, but preserve the scene features a policy relies on to make decisions. Existing platforms, however, exhibit a sim-to-real visual gap that corrupts policy perception, undermining their ability to assess a policy's closed-loop decision-making. To this end, we propose DreamStream, a generative, closed-loop simulator that achieves policy-oriented fidelity using a simulator-grounded autoregressive video model. Our video model is distilled from a large pretrained video model via traffic layout guidance, varying visual appearance while preserving policy-relevant features such...
| Authors | Ziyang Leng, Sicheng Mo, Seth Z. Zhao et al. |
|---|---|
| Primary category | cs.RO |
| Published | 22 September 2026 |
| Last updated at source | 22 September 2026 |
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