ITSC 2024 Paper Abstract

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Paper FrBT8.1

Yu, Ruilin (Jilin University), Wang, Cheng (Heriot-Watt University), Lv, Zhouhang (Jilin University), Zhang, Yuxin (Jilin University)

Requirements Decomposition for Perception Systems of Autonomous Vehicles: A Case Study of Multi-Object Tracking

Scheduled for presentation during the Regular Session "Advanced Vehicle Safety Systems III" (FrBT8), Friday, September 27, 2024, 13:30−13:50, Salon 16

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Keywords Advanced Vehicle Safety Systems, Sensing, Vision, and Perception

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.

 

 

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