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<p>Efficient exploration and understanding of an autonomous driving system’s capabilities and functional boundaries are crucial for ensuring safety performance. This paper offers a comprehensive examination of safety verification and test case generation for autonomous driving function stacks, enhancing their safety and reliability. Firstly, we introduce a holistic approach that synergizes operational flow-oriented Hazard and Operability Study (HAZOP) with cascaded System-Theoretic Process Analysis (STPA) processes. Secondly, we propose a test case generation procedure that begins with an expansion to discrete parameters using tree search, followed by heterogeneous sampling in the continuous parameter space. Additionally, this paper features a real-world case study with WATonoBus, showcasing the practicality and effectiveness of the proposed methods in securing autonomous vehicles safe operation in complex urban settings. Our findings make a substantial contribution to the autonomous vehicle safety field, offering critical insights for ongoing research and development in this rapidly advancing area.</p>

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Cascaded Safety Analysis and Test Scenario Generation Techniques for Autonomous Driving: A Case Study with WATonoBus

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月28日

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  • Chen Sun,
  • Ruihe Zhang,
  • Ahmad Reza Alghooneh,
  • Minghao Ning,
  • Pouya Panahandeh,
  • Steven Tuer,
  • Amir Khajepour

摘要

Efficient exploration and understanding of an autonomous driving system’s capabilities and functional boundaries are crucial for ensuring safety performance. This paper offers a comprehensive examination of safety verification and test case generation for autonomous driving function stacks, enhancing their safety and reliability. Firstly, we introduce a holistic approach that synergizes operational flow-oriented Hazard and Operability Study (HAZOP) with cascaded System-Theoretic Process Analysis (STPA) processes. Secondly, we propose a test case generation procedure that begins with an expansion to discrete parameters using tree search, followed by heterogeneous sampling in the continuous parameter space. Additionally, this paper features a real-world case study with WATonoBus, showcasing the practicality and effectiveness of the proposed methods in securing autonomous vehicles safe operation in complex urban settings. Our findings make a substantial contribution to the autonomous vehicle safety field, offering critical insights for ongoing research and development in this rapidly advancing area.