Railway systems face the demand for efficient, reliable, and low-cost logistic services. Nevertheless, in many countries, punctuality of rail traffic plummet at a poor level. Even though high quality is pursued, there seems to be a lack of broad understanding when it comes to the concatenation of delays. However, understanding rail traffic delay chains is important for improving the performance of rail transport quality. Our research uses a data-mining approach for analysing rail transport delay chains, with data from passenger train traffic on the Finnish rail network. This study illustrates data mining is a useful tool for identifying and mapping the delay chains. It may be concluded that based on a deeper understanding of the delay concatenation, it is possible to develop rail traffic punctuality and the whole railway system. In medium and long-term planning, data-mining analyses of rail traffic can help to develop a more robust timetable structures, and provide tools for rail network planning.
Authors: Jouni Wallander and Miika Mäkitalo
Publication: International Journal of Shipping and Transport Logistics, 2012, Vol. 4, No. 3, p. 269–285
More information: http://www.inderscience.com/info/inarticle.php?artid=47492