Perceives but Doesn't Brake: A Perception-Action Binding Gap in Reasoning Driving VLAs

Matteo Cercola, Katie Z Luo, Simone Formentin, Marco Pavone · 2026 · arXiv

DOI: 10.48550/arXiv.2610.28184 · open-access PDF

Abstract

Reasoning-augmented vision-language-action (VLA) driving models can perceive and reason about safety-critical hazards yet fail to translate that evidence into safe actions. We characterize this failure as a perception-action binding gap: hazard information is available inside the model but exerts insufficient control over trajectory generation. Using matched simulated counterfactuals and logged driving replay, we show that in-path hazards are actually encoded in the visual representation, but longitudinal plans are dominated by ego-speed history and respond only weakly to hazard proximity or t

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