OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Driving
We present OmniV2X, a generative foundation model for vehicle-to-everything (V2X) cooperative driving. The model directly interprets independent context sequences comprising multi-modal and multi-agent observations. The new design mitigates the computational cost of dense 3D perception, the vulnerability to data scarcity in cooperative scenarios, and the poor compliance with standardized messaging in existing methods that fuse multi-modal inputs into a shared representation. For training, we present an end-to-end supervised pipeline using a downstream trajectory generation loss, in which a high-capacity generative sequence planner implicitly learns to steer the model and leverage multi-mo...
| Authors | Juntong Peng, Juanwu Lu, Yupeng Zhou et al. |
|---|---|
| Primary category | cs.RO |
| Published | 19 June 2026 |
| Last updated at source | 7 August 2026 |
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