Quantifying the impact of risk factors at railway level crossings using accident prediction models: A cross-country study

Railway level crossings are critical elements in railway and road networks with accident occurrences resulting in
fatal and severe injuries. In addition to the human loss, level crossing accidents also negatively impact rail
transport reliability and transport speed. For safety management, specific risk factors should be identified and
their impact on overall safety quantified. To this end, multivariate regression equations, commonly known as
accident prediction models, have been used in the study. The paper describes the development of accident
prediction models in three Central European countries (Czech Republic, Hungary and Austria), using samples of
data on railway level crossings with flashing lights. The models were used to quantify the impact of several risk
factors. The cross-country study design enabled comparison of obtained experience and drawing conclusions for
further development of both road and railway network safety management.