Safety Assurance of Autonomous Systems using Machine Learning: An Industrial Case Study and Lessons Learnt
Marc Zeller
Abstract:In order to assess AI/ML‐based autonomous systems in terms of safety, it is not sufficient to assess the system w.r.t. potential failures that could lead to hazards (e.g., as proposed by standards such as IEC 61508, ARP 4761, etc.). Also, functional weaknesses/insufficiencies of the used algorithms according to Safety Of The Intended Functionality (SOTIF) standard ISO 21448 must be considered. In this paper, we present an approach for the safety assessment of systems incorporating AI/ML models using a Model‐ba… Show more
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