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Collecting evidence from distributed sources to evaluate railway suicide and trespass prevention measures

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It can be difficult to select from available safety preventative measures, especially where there is limited evidence of effectiveness in different contexts. This paper describes application of a method to identify and evaluate wide-ranging preventative measures for rail suicide and trespass fatalities. Evidence from literature and industry sources was collated and reviewed in a two stage process to achieve consensus among experts on the likely effects of the measures and factors influencing their implementation. Multiple evaluation criteria were used to examine the measures from different perspectives. Fencing, awareness campaigns and different types of organisational initiatives were recommended for further testing. This is the first time evidence has been collected internationally across such a range of preventative measures. Commentary is provided on using this type of approach to select safety measures from a pool of prevention options, including how re-framing the scope of the exercise could identify alternative options for prevention.

Practitioner summary: The findings give insight to how different measures work in different ways and how industry can consider this in strategic initiatives. The method could be used in future studies with different frames of reference (e.g. different timescales, level of ambition and safety context e.g. railway crossings or highway fatalities).

Abbreviation: RESTRAIL: REduction of Suicides and Trespasses on RAILway property

Keywords: Rail fatalities; evaluation; experts and consensus methods; prevention; suicide; trespass

Document Type: Research Article

Affiliations: 1: Faculty of Engineering, University of Nottingham, University Park, Nottingham, UK; 2: VTT, Technical Research Centre of Finland Ltd, VTT, Finland; 3: Trafikverket, Borlänge, Sweden; 4: International Union of Railways (UIC), Paris, France; 5: Institute of General Practice and Family Medicine, University Hospital of Ludwig-Maximilians-University Munich, Munich, Germany; 6: IFSTTAR-LPC, Versailles, France; 7: CRISTAL - Centre deRecherche en Informatique, Signal et Automatique de Lille, University of Lille, Lille, France; 8: IFSTTAR-ESTAS, Villeneuve, d’Ascq, France; 9: ProRail, Utrecht, The Netherlands

Publication date: 02 November 2018

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