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Using Bayesian Networks to Model Accident Causation in the UK Railway Industry

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Probabilistic Safety Assessment and Management

Abstract

We describe a method of modelling organisational causes of accidents, using Bayesian Networks. A rigorous method is used to relate interactions within the organisation operating the system to causal factors for accidents. Using examples from a model of the causes of SPAD incidents in the UK railways, we describe how such a model can be used for risk assessment.

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Author information

Authors and Affiliations

  1. RADAR Group, Queen Mary, University of London, Mile End Road, El 4NS, London, UK

    William Marsh

  2. Atkins Rail, Euston Tower, 286 Euston Road, NW1 3AT, London, UK

    George Bearfield

Authors
  1. William Marsh
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  2. George Bearfield
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Editor information

Editors and Affiliations

  1. TÜV Süddeutschland, Dudenstrasse 28, D-68167, Mannheim, Germany

    Cornelia Spitzer Dipl.-Math.

  2. Swiss Federal Nuclear Safety Inspectorate (HSK), CH-5232, Villigen-HSK, Switzerland

    Ulrich Schmocker PhD

  3. Paul Scherrer Institut (PSI), CH-5232, Villigen PSI, Switzerland

    Vinh N. Dang PhD

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© 2004 Springer-Verlag London

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Marsh, W., Bearfield, G. (2004). Using Bayesian Networks to Model Accident Causation in the UK Railway Industry. In: Spitzer, C., Schmocker, U., Dang, V.N. (eds) Probabilistic Safety Assessment and Management. Springer, London. https://doi.org/10.1007/978-0-85729-410-4_575

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  • DOI: https://doi.org/10.1007/978-0-85729-410-4_575

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1057-6

  • Online ISBN: 978-0-85729-410-4

  • eBook Packages: Springer Book Archive

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