  The impact of rail transport on the environment is one of the crucial factors
for the sustainable development of this form of mass transport. We present a
data-driven analysis of wild animal railway accidents in the region of southern
Poland, a step to create the train driver warning system. We built our method
by harnessing the Bayesian approach to the statistical analysis of information
about the geolocation of the accidents. The implementation of the proposed
model does not require advanced knowledge of data mining and can be applied
even in less developed railway systems with small IT support. Furthermore, we
have discovered unusual patterns of accidents while considering the number of
trains and their speed and time at particular geographical locations of the
railway network. We test the developed approach using data from southern
Poland, compromising wildlife habitats and one of the most urbanised regions in
Central Europe, based on this we conclude that our model is best suited to
railway lines that pass through varying types of landscape.
