Autonomous Vehicles (AVs), also known as self-driving cars, are a potentially transformative technology, but developing and demonstrating AV safety remains an open question. AVs offer some unique challenges that stretch the limits of traditional safety engineering practices. Most current safety standards and methodologies in the AV industry were not originally intended for application to autonomous vehicles, and they have significant limitations and shortcomings. In this article, we analyze the literature to first build an argument that a new safety framework is needed for AVs. We then use the identified limitations of current methodologies as a basis to formulate a set of fundamental requirements that must be met by any proposed AV safety framework. We propose a new AV safety framework based on the Hybrid Causal Logic (HCL) methodology, which combines Event Sequence Diagrams (ESDs), Fault Tree Analysis (FTA), and Bayesian Networks (BNs). The HCL framework is developed at a conceptual level and then evaluated versus the identified fundamental requirements. To further illustrate how the framework may meet the requirements, a simple example of an AV perception system scenario is developed using the HCL framework and evaluated. The results demonstrate that the HCL framework provides an integrated approach that has the potential to satisfy more completely the fundamental requirements than the current methodologies.

自动驾驶汽车 (AV)，也称为自动驾驶汽车，是一种潜在的变革性技术，但开发和展示 AV 安全性仍然是一个悬而未决的问题。自动驾驶汽车提供了一些独特的挑战，突破了传统安全工程实践的限制。AV 行业当前的大多数安全标准和方法最初并非旨在应用于自动驾驶汽车，它们具有明显的局限性和缺点。在本文中，我们分析文献以首先建立一个论点，即自动驾驶汽车需要一个新的安全框架。然后，我们使用当前方法的已识别限制作为基础来制定任何提议的 AV 安全框架必须满足的一组基本要求。我们提出了一种基于混合因果逻辑 (HCL) 方法的新 AV 安全框架，它结合了事件序列图 (ESD)、故障树分析 (FTA) 和贝叶斯网络 (BN)。HCL 框架是在概念层面开发的，然后根据确定的基本要求进行评估。为了进一步说明该框架如何满足要求，使用 HCL 框架开发并评估了一个 AV 感知系统场景的简单示例。结果表明，HCL 框架提供了一种集成方法，与当前方法相比，它有可能更完全地满足基本要求。为了进一步说明该框架如何满足要求，使用 HCL 框架开发并评估了一个 AV 感知系统场景的简单示例。结果表明，HCL 框架提供了一种集成方法，与当前方法相比，它有可能更完全地满足基本要求。为了进一步说明该框架如何满足要求，使用 HCL 框架开发并评估了一个 AV 感知系统场景的简单示例。结果表明，HCL 框架提供了一种集成方法，与当前方法相比，该方法有可能更完全地满足基本要求。