为自动驾驶车重新定义安全标准中的可控性,引入可迁移性和可预测性指标。
Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability
- 将可控性拆解为可迁移性与可预测性两个可衡量维度
- 提出数学框架量化可预测性,支持对系统行为的可验证评估
- 适合自动驾驶系统安全认证与测试人员参考
ISO 26262 标准基于人为驾驶场景定义车辆功能安全,其核心要素包括严重性、暴露度和可控性。在自动驾驶车辆(AV)中,因缺乏人类驾驶员,需重新审视这些原则。本文将‘可控性’分解为两个可审计的子维度:可迁移性与可预测性。可迁移性衡量系统将控制权移交至专用应急机制的能力;可预测性则反映外部实体预判车辆行为的难易程度,基于人机交互理论形式化定义并提供量化框架。文中引入‘设计-实现差距’概念,区分架构层面的应急承诺与实际场景下的可用应急能力。所提指标与 ISO 26262 及 ISO/PAS 21448(SOTIF)兼容,使应急与交互声明可在不同运行设计域(ODD)切片中被验证与追溯。该改进不替代原有标准,而是扩展其适用范围至 SAE Level 4/5 的无人驾驶系统。
原文摘要 · Abstract (English)
The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded in a human-driven vehicle paradigm. In the context of autonomous vehicles (AVs), the absence of a human driver necessitates revisiting these principles. This paper decomposes the Controllability placeholder into two auditable evidence dimensions of ISO 26262 by introducing two measurable sub-concepts: Transferability and Predictability. Transferability extends Controllability to capture AV systems' ability to hand off control to dedicated fallback safety mechanisms, while Predictability captures how easily external agents can anticipate AV behavior. Predictability is formally defined from human-robot interaction-inspired principles, and a mathematical framework is provided to quantify it. A designed-versus-achievable gap is introduced to distinguish architectural fallback claims from scene-conditioned achievable fallback capability. The proposed metrics align with ISO 26262 and ISO/PAS 21448 (SOTIF), rendering fallback and interaction claims falsifiable and traceable across ODD slices. These dimensions complement rather than replace existing standards, and the enhancements preserve the structure of ISO 26262 while extending its applicability to driverless automated systems operating at SAE Levels 4 and 5.
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