When and How Severely: Scenario-Specific Safety Envelopes for Driving VLAs 文章

ArXiv CS.AI2026-06-15NEWSen作者: Abhinaw Priyadershi, Jelena Frtunikj

详细信息

来源站点
ArXiv CS.AI
作者
Abhinaw Priyadershi, Jelena Frtunikj
文章类型
NEWS
语言
en
发布日期
2026-06-15

摘要

arXiv:2606.14238v1 Announce Type: cross Abstract: Safety certification of Vision-Language-Action (VLA) driving planners under ISO 21448 (SOTIF) rests on an Operational Design Domain (ODD) specification that answers two complementary questions: when does the planner start to fail, and how severely does it fail once it does? We evaluate Alpamayo R1, a 10B-parameter open-weight driving VLA, on 15,968 (clip, attack) pairs. We find a conservative-aggregate gap: an aggregate safe threshold of $\sigma \leq 50$ under a 15% average displacement error (ADE) budget masks well-sampled scenarios that tolerate the top of the tested grid ($\sigma = 70$). A Gaussian Mixture Model (GMM) on the changed-explanation subset identifies six discrete severity bands (BIC-optimal $k{=}6$), so two perturbation conditions with the same mean error can differ materially in their share of high-severity (C4/C5) failures.

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