发表机构
University of Michigan Transportation Research Institute; University of Michigan; The University of Hong Kong; Laplace Intelligence; Tsinghua University（密歇根大学交通研究所; 密歇根大学; 香港大学; 拉普拉斯智能; 清华大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对传统功能安全方法不足，提出行为安全评估范式，通过行为能力测试和驾驶智能测试两个组件，系统评估自动驾驶车辆在交通环境中的安全行为。
AI 中文摘要
近年来，自动驾驶车辆（AV）在实际部署方面取得了显著进展，但安全性仍然是其广泛采用的关键障碍。传统的功能安全方法主要从车辆中心视角验证AV硬件和软件系统的可靠性、鲁棒性和充分性，但未能充分解决AV与周围交通环境的更广泛交互及行为影响。为克服这一局限，我们提出向行为安全的范式转变，这是一种聚焦于评估AV在交通环境中响应和交互的综合方法。为系统评估行为安全，我们引入了一个第三方AV安全评估框架，包含两个互补的评估组件：行为能力测试和驾驶智能测试。行为能力测试在受控场景下评估AV的反应性行为，确保基本行为能力；而驾驶智能测试在自然交通条件下评估AV的交互行为，量化安全关键事件的频率，以便在大规模部署前提供具有统计意义的安全指标。在本研究的第二部分，我们测试了一个开源的四级自动驾驶系统（ADS），以证明所提出方法的有效性。
英文摘要
Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespread adoption. Traditional functional safety approaches, which primarily verify the reliability, robustness, and adequacy of AV hardware and software systems from a vehicle-centric perspective, do not sufficiently address the AV's broader interactions and behavioral impact on the surrounding traffic environment. To overcome this limitation, we propose a paradigm shift toward behavioral safety, a comprehensive approach focused on evaluating AV responses and interactions within the traffic environment. To systematically assess behavioral safety, we introduce a third-party AV safety assessment framework comprising two complementary evaluation components: the Behavioral Competency Test and the Driving Intelligence Test. The Behavioral Competency Test evaluates the AV's reactive behaviors under controlled scenarios, ensuring basic behavioral competency. In contrast, the Driving Intelligence Test assesses the AV's interactive behaviors within naturalistic traffic conditions, quantifying the frequency of safety-critical events to deliver statistically meaningful safety metrics before large-scale deployment. In Part II of this study, an open-source Level 4 Automated Driving System (ADS) is tested to demonstrate the effectiveness of the proposed method.
