构建自动驾驶行为分类体系,填补运行域规范与行为验证间的空白
From Operational Design Domain to Action: A Systematic Behavioral Taxonomy for Autonomous Driving

- 基于六层模型构建21项行为能力分类,覆盖高速、城市、枢纽三场景
- 每项行为从纵向/横向控制维度,按安全、合规、舒适、效率四属性量化评估
- 可生成具体测试场景,支持SOTIF覆盖证据,适合安全验证团队使用
自动驾驶系统(ADS)的运行设计域(ODD)规定了其允许运行的范围,但未明确部署后必须实现的具体行为。这一规范与行为验证之间的鸿沟是自动驾驶安全保证的关键挑战。本文基于PEGASUS六层模型构建了一个结构化的行为分类体系,涵盖高速公路(HWY)、城市(URB)和枢纽(HUB)三大操作域,共21项行为能力。每项行为沿纵向与横向控制轴分解,并依据四属性框架——安全性(间隙维持、冲突规避、运动稳定性)、合规性(法规与行为规范)、舒适性(乘客动态与信任感)、效率(任务完成与产品级指标)进行表征。研究进一步表明,将ODD参数与行为能力结合可生成可系统测试的场景族,用于SOTIF覆盖证据。该分类体系基于AVSC00008202111、SAE J3237和SAE J3016标准,经规则约束轨迹优化系统部署验证。枢纽域被识别为结构独特且定义不清的领域,亟需专项研究。
原文摘要 · Abstract (English)
Operational Design Domain (ODD) specifications describe where an automated driving system (ADS) is permitted to operate, but they do not prescribe what the ADS must demonstrably do once deployed within that domain. This gap between operating condition specification and behavioral validation represents a critical unresolved challenge in ADS safety assurance. This paper presents a structured, standards-grounded taxonomy of 21 behavioral competencies organized across three operational domains-Highway (HWY), Urban (URB), and Hub (HUB)-derived systematically from the PEGASUS six-layer model-based ODD. Each behavior is decomposed along longitudinal and lateral control axes and characterized against a four-property framework: Safety (gap maintenance, conflict avoidance, kinematic stability), Compliance (legal rules and behavioral norms), Comfort (rider dynamics and trust), and Efficiency (mission completion and product-level metrics). We further demonstrate that the crossing of ODD layer parameterizations with behavioral competency specifications yields concrete scenario families suitable for systematic behavioral testing and SOTIF coverage evidence. The taxonomy is grounded in AVSC00008202111, SAE J3237, and SAE J3016, and is validated as an operational specification layer through its deployment in a rule-enforced trajectory optimization system. The Hub domain is identified as a structurally distinct, underspecified domain warranting dedicated research attention.
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