{"ID":2887147,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.02919","arxiv_id":"2508.02919","title":"Context-aware Risk Assessment and Its Application in Autonomous Driving","abstract":"Ensuring safety in autonomous driving requires precise, real-time risk assessment and adaptive behavior. Prior work on risk estimation either outputs coarse, global scene-level metrics lacking interpretability, proposes indicators without concrete integration into autonomous systems, or focuses narrowly on specific driving scenarios. We introduce the Context-aware Risk Index (CRI), a light-weight modular framework that quantifies directional risks based on object kinematics and spatial relationships, dynamically adjusting control commands in real time. CRI employs direction-aware spatial partitioning within a dynamic safety envelope using Responsibility-Sensitive Safety (RSS) principles, a hybrid probabilistic-max fusion strategy for risk aggregation, and an adaptive control policy for real-time behavior modulation. We evaluate CRI on the Bench2Drive benchmark comprising 220 safety-critical scenarios using a state-of-the-art end-to-end model Transfuser++ on challenging routes. Our collision-rate metrics show a 19\\% reduction (p = 0.003) in vehicle collisions per failed route, a 20\\% reduction (p = 0.004) in collisions per kilometer, a 17\\% increase (p = 0.016) in composed driving score, and a statistically significant reduction in penalty scores (p = 0.013) with very low overhead (3.6 ms per decision cycle). These results demonstrate that CRI substantially improves safety and robustness in complex, risk-intensive environments while maintaining modularity and low runtime overhead.","short_abstract":"Ensuring safety in autonomous driving requires precise, real-time risk assessment and adaptive behavior. Prior work on risk estimation either outputs coarse, global scene-level metrics lacking interpretability, proposes indicators without concrete integration into autonomous systems, or focuses narrowly on specific dri...","url_abs":"https://arxiv.org/abs/2508.02919","url_pdf":"https://arxiv.org/pdf/2508.02919v1","authors":"[\"Boyang Tian\",\"Weisong Shi\"]","published":"2025-08-04T21:50:03Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}