Human risk factors leading to level crossing accidents

Anne Silla, Esko Lehtonen

Research output: Contribution to conferenceConference AbstractScientificpeer-review

Abstract

Background: Quantitative estimates of effects of road/rail safety measures are often needed, but experimental or naturalistic data required is typically challenging to collect. The objective of this paper was to show how in-depth accident data could be used in estimating quantitative safety effects. The estimation was based on the analysis of the risk factors leading to LC accidents. Method was applied to measures supporting the detection of approaching LC and/or train.

Method: The analysis of LC accidents utilised data from two sources: i) article of Laapotti (2016) who analysed fatal motor vehicle accidents at LCs in Finland during the years 1991–2011, and ii) descriptions of in-depth LC accident data from seven countries which were analysed as part of an EU project SAFER-LC (https://safer-lc.eu/). For the purposes of this paper, the available LC statistics were structured around three main variables: type of LC, type of victim, and type of behaviour. The focus was especially on the type of behaviour since this is a variable with least information in publicly available LC statistics. Impact evaluation framework and piloted safety measures from the same projects were used to demonstrate safety potential.

Results: The work resulted in five main risk factors underlying the accidents: ‘Situation awareness error’, ‘Vehicle handling error’, ‘Other human risk factors’. ‘Vehicles risk factors’ and ‘Other’. Most accidents (93.5%) at unprotected (passive) LCs were related to situation awareness error whereas for protected (active) LCs the majority of accidents were related either to situation awareness error (53.5%) or to other human risk factors (34.9%) such as deliberate risk taking. These results were used in the impact assessment framework and the safety potential of 13 measures were evaluated.

Conclusions: Majority of the LC accidents were associated with errors in situation awareness or other road user related human factor, especially deliberate risk-taking. The share of potentially prevented LC accidents by measure ranged from 8 to 96% which highlights the differences in suitability of safety measures to target different LC types, road users and road user behaviours.

Reference: Laapotti, S. 2016. Comparison of fatal motor vehicle accidents at passive and active railway level crossings in Finland. IATSS Research 40 (2016), 1–6.
Original languageEnglish
Publication statusPublished - 24 Aug 2022
MoE publication typeNot Eligible
Event7th International Conference on Traffic and Transport Psychology, ICTTP7 - Gothenburg, Sweden
Duration: 23 Aug 202225 Aug 2022
https://www.icttp7.se/

Conference

Conference7th International Conference on Traffic and Transport Psychology, ICTTP7
Country/TerritorySweden
CityGothenburg
Period23/08/2225/08/22
Internet address

Keywords

  • level crossing
  • road user behaviour
  • safety
  • situation awareness

Fingerprint

Dive into the research topics of 'Human risk factors leading to level crossing accidents'. Together they form a unique fingerprint.

Cite this