🤖 AI Summary
本文探讨了如何通过不同类型的演练来提高自动驾驶车辆事故管理的有效性，提出了一套针对自动驾驶车辆特性的演练框架。
📝 Abstract
Incident management (IM) has evolved over recent decades to cover an ever-expanding array of hazards and systems. Barring real-life experience, exercises are a key tool in developing an effective IM program. As part of enterprise resilience and operational readiness, IM practitioners design exercises to understand and build capabilities for efficiently and effectively responding to incidents. Combining research and policy on an emerging transportation technology, automated vehicles (AVs), with established practices for IM, we describe what makes exercises effective and how they can be used to identify gaps and develop capacity. A range of exercise types exist, from workshops, to tabletops, to drills, and to full-scale exercises. Every stage of an exercise - preparing, setting up, facilitating, closing, and assessing - is interconnected and should further the exercise's objectives. AV IM practitioners can maximize the utility of a mature exercise program through exercise quality, diversity, and volume. The need to respond to AV incidents, from collisions to natural hazards, is inevitable. This paper tailors existing practices to a series of frameworks, predicated on the unique socio-technical nature of AVs to provide first-of-its-kind guidance for AV IM exercises. Additionally, these frameworks are company-neutral to enable intercompany and inter-organization collaboration.