EditWM: Event-Decomposed World Modeling with Incremental Correction for End-to-End Autonomous Driving
A novel world modeling framework that optimizes autonomous navigation by correcting for unpredictable event dynamics.
World models support autonomous driving by predicting the scene evolution associated with candidate trajectories. Driving dynamics differ in predictability, motivating a distinction between regular evolution and event-induced deviations that call for selective correction. We prop...
ArXiv CS.RO
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EditWM advances autonomous driving by distinguishing between predictable motion and sudden, event-driven anomalies that require immediate adjustment. This hierarchical approach improves simulation reliability, allowing vehicles to better anticipate and adapt to erratic real-world traffic scenarios.
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