Assessing Temporary Speed Restrictions and Associated Unavailability Costs in Railway Infrastructure

Abstract

This paper analyses the occurrence of temporary speed restrictions in railway infrastructure associated with railway track geometry degradation. A negative binomial regression model is put forward to estimate the expected number of temporary speed restrictions, controlling for the main quality indicators of railway track geometry degradation and for the maintenance and renewal actions/decisions. The prediction of temporary speed restrictions provides a quantitative way to support the assessment of unavailability costs to railway users. A case study on the Lisbon–Oporto Portuguese line is explored, comparing three statistical models: the Poisson, the ‘over-dispersed’ Poisson and the proposed negative binomial regression. Main findings suggest that the main quality indicators for railway track geometry degradation are statistically significant variables, apart from the maintenance and renewal actions. Finally, a discussion on the impacts of the unavailability costs associated with temporary speed restrictions is also provided in a regulated railway context.

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Acknowledgements

The authors would like to thank the support and collaboration of the Portuguese Railway Infrastructure Manager, REFER, E. P. E, and of the Portuguese Foundation for Science and Technology (FCT) through the project MODURAIL (PTDC/SEN-TRA/112975/2009) and MIT Portugal program through the PhD Grant (SFRH/BD/33785/2009).

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Correspondence to António Ramos Andrade.

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Portuguese Foundation for Science and Technology (FCT) and MIT Portugal. Portuguese Railway Infrastructure Manager (REFER).

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Andrade, A.R., Teixeira, P.F. Assessing Temporary Speed Restrictions and Associated Unavailability Costs in Railway Infrastructure. Int J Civ Eng 16, 219–228 (2018). https://doi.org/10.1007/s40999-016-0121-3

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Keywords

  • Temporary speed restrictions
  • Railway maintenance
  • Statistical modelling
  • Negative binomial regression
  • Unavailability costs