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A consistent safety case argumentation for artificial intelligence in safety related automotive systems – An Evaluation of a New Conceptual Functional Safety Approach

  • Regarding the actual automotive safety norms the use of artificial intelligence (AI) in safety critical environments like autonomous driving is not possible. This paper introduces a new conceptual safety modelling approach and a safety argumentation to certify AI algorithms in a safety related context. Therefore, a model of an AI-system is presented first. Afterwards, methods and safety argumentation are applied to the model, whereas it is limited to a specific subset of AI-systems, i.e. off-board learning deterministic neural networks in this case. Other cases are left over for future research. The result is a consistent safety analysis approach that applies state of the art safety argumentations from other domains to the automotive domain. This will enforce the adaptation of the functional safety norm ISO26262 to enable general AI methods in safety critical systems in future.

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Metadaten
Author:Alexander Rudolph, Stefan Voget, Jürgen MottokORCiDGND
URL / DOI:https://hal.archives-ouvertes.fr/hal-02156048
Parent Title (English):Embedded Real-Time Software and Systems Conference (ERST²), Jan 2018, Toulouse/France
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2018
Release Date:2021/03/11
Institutes:Fakultät Elektro- und Informationstechnik
Fakultät Elektro- und Informationstechnik / Laboratory for Safe and Secure Systems (LAS3)
research focus:Digitalisierung
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