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Practical Application of Model-Based Safety Analysis to the Design of Global Operating System of New Rolling Stock on Automatic Metro Lines

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Model-Based Safety and Assessment (IMBSA 2022)

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Abstract

System safety assessments are an integral part of system development, as indicated by EN 5012x railway standards. These activities are usually performed manually and rely on reviews and engineering judgments, with limited use of models to support the system assessment phase. In this paper, we present an application of Model-Based Safety Assessment to the Global Operating System (GOS) validation for automatic and semi-automatic metro lines. Safety assessment is a fundamental part of the development of railway systems and the use of model-based techniques provides an effective method for the formalization and analysis of such complex systems. A MBSA deployment methodology using AltaRica Wizard platform and its stochastic simulator is presented and results of the application of the automatic metro lines use-case are shown.

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Acknowledgments

Fractus and EdgeMind work on a project to deploy tailor-made MBSA methods and tools dedicated to a railway Global Operating System (GOS) for a GOA4 metro line for a major urban public transport company in France.

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Authors and Affiliations

  1. Fractus, Rue de la Croix Ronde, 91360, Epinay-sur-Orge, France

    Anthony Legendre

  2. EdgeMind, Rue du départ, 75014, Paris, France

    Roland Donat

Authors
  1. Anthony Legendre
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  2. Roland Donat
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Corresponding author

Correspondence to Anthony Legendre .

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Editors and Affiliations

  1. ONERA, Toulouse, France

    Christel Seguin

  2. Siemens AG, Munich, Bayern, Germany

    Marc Zeller

  3. ONERA, Toulouse, France

    Tatiana Prosvirnova

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Legendre, A., Donat, R. (2022). Practical Application of Model-Based Safety Analysis to the Design of Global Operating System of New Rolling Stock on Automatic Metro Lines. In: Seguin, C., Zeller, M., Prosvirnova, T. (eds) Model-Based Safety and Assessment. IMBSA 2022. Lecture Notes in Computer Science, vol 13525. Springer, Cham. https://doi.org/10.1007/978-3-031-15842-1_6

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  • DOI: https://doi.org/10.1007/978-3-031-15842-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15841-4

  • Online ISBN: 978-3-031-15842-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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