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Combining Evasive and Braking Reactions for Safety Reference Models in Automated Vehicles

arXiv · AI, language, vision and robotics · article · Sep 24, 2026 · UTC

Computational models of careful and competent human drivers are essential for scenario-based evaluation of automated driving systems (ADS). However, most existing safety reference models primarily focus on longitudinal braking, neglecting the role of evasive steering in human collision avoidance. This paper proposes a hybrid Fuzzy-Safety Model (FSM-H) that integrates longitudinal mitigation and lateral avoidance within a unified behavioral framework. The braking component is governed by Proactive Fuzzy Safety (PFS) metrics, representing the erosion of longitudinal safety margins, while the ste

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Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-09-24T12:55:28.000Z

First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.