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  4. Approach for Argumenting Safety on Basis of an Operational Design Domain
 
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2024
Conference Paper
Title

Approach for Argumenting Safety on Basis of an Operational Design Domain

Abstract
The Operational Design Domain (ODD) is a representative model of the real world in which an Automated Driving System (ADS) is intended to operate. The definition of the ODD is a crucial part of the development process for such an artificial intelligence (AI)-enabled system. This is due to the fact that the ODD is the basis for several critical development activities, like defining system-level requirements, test & verification, and building a well-founded safety case for an AI-based ADS. Since an inadequately defined ODD poses a major safety concern for the entire development, an ODD must be defined completely and consistently during the development process. In this work, we present an approach for the ODD definition and maintenance during the development of safety-critical AI-based ADS functionalities and provide evidences to argue the sufficient completeness and consistency. We demonstrate the feasibility of our approach by an industrial use case of a fully automated system in the railway domain.
Author(s)
Weiß, Gereon  
Fraunhofer-Institut für Kognitive Systeme IKS  
Zeller, Marc
Siemens AG  
Schoenhaar, Hannes
Siemens AG  
Drabek, Christian  
Fraunhofer-Institut für Kognitive Systeme IKS  
Kreutz, Andreas  
Fraunhofer-Institut für Kognitive Systeme IKS  
Mainwork
IEEE/ACM 3rd International Conference on AI Engineering – Software Engineering for AI, CAIN 2024. Proceedings  
Project(s)
safe.trAIn
Funder
Bundesministerium für Wirtschaft und Klimaschutz -BMWK-
Conference
International Conference on AI Engineering - Software Engineering for AI 2024  
Open Access
File(s)
Download (1.07 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.1145/3644815.3644944
10.24406/publica-3218
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Kognitive Systeme IKS  
Fraunhofer Group
Fraunhofer-Verbund IUK-Technologie  
Keyword(s)
  • operational design domain

  • OOD

  • autonomous system

  • safety

  • safety assurance

  • artificial intelligence

  • AI

  • machine learning

  • ML

  • automated train operation

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