| Popis: |
One of the main focuses in traffic technology and research area refers to increasing the safety in transport network. In this context, the highlight is on places where traffic flows and different modes of transport are integrated: intersections, pedestrian crossings, level crossings, etc. Although accidents at level crossings do not occur so often, their consequences are much more severe compared to other road accidents, on personal, social, and financial level. Due to the physical “conflict” between road users and railway infrastructure, trains and train operations, level crossings represent one of the most complex traffic safety systems. Accidents on railways mainly occur due to the irresponsible behaviour of drivers and pedestrians, whether it is illegal movements on the railway, or non-compliance with traffic regulations and signalling at level crossings, therefore it is necessary to devise a solution that will reliably influence their behaviour (Tey, Ferreira, & Wallace, 2011). The goal of this research is to analyse available open data from the traffic system that can be used to create a solution that will reliably warn all road users of an approaching train. Such a solution would be based on historical data on critical points, i.e., crossings that have a history of traffic accidents (and can be classified as "black spots"), as well as real-time data on the position of road vehicles and especially trains. A solution based on historical data is applicable to all registered level crossings for which there is available data, while, in addition, real-time data on train movement would increase reliability and could also be applied at unregistered level crossings and in case of illegal movement on the railway. |
