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2022
Conference Paper
Title
Towards Continuous Safety Assurance for Autonomous Systems
Abstract
Ensuring the safety of autonomous systems over time and in light of unforeseeable changes is an unsolved task. This work outlines a continuous assurance strategy to ensure the safe ageing of such systems. Due to the difficulty of quantifying uncertainty in an empirically sound manner or at least providing a complete list of uncertainty during the system design, alternative run-time monitoring approaches are proposed to enable a system to self-identify its exposure to a yet unknown hazardous condition and subsequently trigger immediate safety reactions as well as to initiate a redesign and update process in order to ensure the future safety of the system. Moreover, this work unifies the inconsistently used terminology found in literature regarding the automation of different aspects of safety assurance and provides a conceptual framework for understanding the difference between known unknowns and unknown unknowns.
Project(s)
Sichere Künstliche Intelligenz am Beispiel eines fahrerlosen Regionalzuges
Funder
Bundesministerium für Wirtschaft und Klimaschutz -BMWK-
Open Access
Rights
Under Copyright
Language
English
Fraunhofer Group
Fraunhofer-Verbund IuK-Technologie