Abstract
Safety requirements decomposition is critical to ensure a safe autonomous vehicle (AV) by design despite the importance of safety verification and validation. This study proposes a method called QUASARS (QUAntifying SAfety Requirements using Shapley) for efficiently decomposing AV perception safety requirements into component-level and effectively quantifying them. QUASARS models the quantification of the impact of component-level faults on system-level faults as a feature importance calculation problem. We demonstrated QUASARS using a multi-object tracking system as an example and validated component-level safety requirements 100 times on the test set. After meeting the generated component-level safety requirements, the testing system was able to meet the system-level safety requirements, indicating the effectiveness of this method in decomposing system-level safety requirements into component-level.
| Original language | English |
|---|---|
| Title of host publication | 27th IEEE International Conference on Intelligent Transportation Systems 2024 |
| Publisher | IEEE |
| Pages | 4095-4101 |
| Number of pages | 7 |
| ISBN (Electronic) | 9798331505929 |
| DOIs | |
| Publication status | Published - 20 Mar 2025 |
Keywords
- Quantitative Requirements
- Risk Decomposition
- SOTIF
- Shapely Value
- autonomous vehicles
ASJC Scopus subject areas
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications
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