A comparison of data-driven and model-based approaches to quantifying railway risk

T.J. Bedford; J.L. Quigley; S. French

doi:10.1007/978-0-85729-410-4_443

A comparison of data-driven and model-based approaches to quantifying railway risk

T.J. Bedford, J.L. Quigley, S. French

Management Science

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Abstract

This paper presents some of the results of a project sponsored by the UK Railway Safety and Standards Board (RSSB). An earlier statistical evaluation of a previous version of the RSSB Safety Risk Model (SRM), a combined Fault/Event Tree, conducted by Prof Andrew Evans had concluded that the model was unduly pessimistic. We have constructed a hypothesis test based on the relative likelihood techniques using the most recent version of the SRM as the null hypothesis. The results support the SRM being consistent with the historical data. Two significant differences between these two studies are the statistical methods employed to support the analysis and the removal of certain significant conservative assumptions from updating the versions of the SRM.

The paper discusses the demands that different model purposes place on these models, and explores the question of whether or not it is meaningful to compare their outputs. The use of expected fatalities as a metric for expressing risk in both models is questioned because of the heavy-tailed form of the distribution for fatality numbers given a fatal accident.

Original language	English
Title of host publication	Probabilistic Safety Assessment and Management
Editors	Cornelia Spitzer, Ulrich Schmocker, Vinh N. Dang
Place of Publication	London
Publisher	Springer-Verlag
Pages	2765-2771
ISBN (Print)	9781852338275
DOIs	https://doi.org/10.1007/978-0-85729-410-4_443
Publication status	Published - 2004

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Keywords

UK Railway Safety and Standards Board
reliability
system performance
Safety Risk Model
RSSB

Cite this

Bedford, T. J., Quigley, J. L., & French, S. (2004). A comparison of data-driven and model-based approaches to quantifying railway risk. In C. Spitzer, U. Schmocker, & V. N. Dang (Eds.), Probabilistic Safety Assessment and Management (pp. 2765-2771). London: Springer-Verlag. https://doi.org/10.1007/978-0-85729-410-4_443

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abstract = "This paper presents some of the results of a project sponsored by the UK Railway Safety and Standards Board (RSSB). An earlier statistical evaluation of a previous version of the RSSB Safety Risk Model (SRM), a combined Fault/Event Tree, conducted by Prof Andrew Evans had concluded that the model was unduly pessimistic. We have constructed a hypothesis test based on the relative likelihood techniques using the most recent version of the SRM as the null hypothesis. The results support the SRM being consistent with the historical data. Two significant differences between these two studies are the statistical methods employed to support the analysis and the removal of certain significant conservative assumptions from updating the versions of the SRM.The paper discusses the demands that different model purposes place on these models, and explores the question of whether or not it is meaningful to compare their outputs. The use of expected fatalities as a metric for expressing risk in both models is questioned because of the heavy-tailed form of the distribution for fatality numbers given a fatal accident.",

keywords = "UK Railway Safety and Standards Board, reliability, system performance, Safety Risk Model, RSSB",

author = "T.J. Bedford and J.L. Quigley and S. French",

note = "Also presented at: International Conference on Probabalistic Safety Assessment and Management (PSAM), Hotel Inter-Continental Berlin, Germany, 14-18 June, 2004.",

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AB - This paper presents some of the results of a project sponsored by the UK Railway Safety and Standards Board (RSSB). An earlier statistical evaluation of a previous version of the RSSB Safety Risk Model (SRM), a combined Fault/Event Tree, conducted by Prof Andrew Evans had concluded that the model was unduly pessimistic. We have constructed a hypothesis test based on the relative likelihood techniques using the most recent version of the SRM as the null hypothesis. The results support the SRM being consistent with the historical data. Two significant differences between these two studies are the statistical methods employed to support the analysis and the removal of certain significant conservative assumptions from updating the versions of the SRM.The paper discusses the demands that different model purposes place on these models, and explores the question of whether or not it is meaningful to compare their outputs. The use of expected fatalities as a metric for expressing risk in both models is questioned because of the heavy-tailed form of the distribution for fatality numbers given a fatal accident.

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KW - system performance

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BT - Probabilistic Safety Assessment and Management

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Access to Document

10.1007/978-0-85729-410-4_443

BedfordQuigleyFrenchPSAM2004-approaches-to-quantifying-railway-riskSubmitted manuscript, 125 KB