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.
Requirements Decomposition for Perception Systems of Autonomous Vehicles: A Case Study of Multi-Object Tracking
24.09.2024
963419 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Lane/object detection and tracking perception system for autonomous vehicles
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