Abstract
One of the objectives of railway infrastructure managers is to improve the punctuality of their operations while satisfying safety requirements and coping with limited capacity. To fulfil this objective, capacity planning and monitoring have become an absolute necessity. Railway infrastructure managers possess tremendous amounts of data about the railway operations, which are recorded in so-called train describer systems. In this paper, a set of methods is proposed to guide the analysis of capacity usage based on these data. In particular, train connections are categorized according to the severity of train reroutings as well as the diversity of these reroutings. The applied method is able to highlight areas in the railway network, where trains have a higher tendency to diverge from their allocated route. The method is independent from the underlying infrastructure, and can, therefore, be reused effortlessly on new cases. The analysis provides a starting point to improve the planning of capacity usage and can be used to facilitate the communication between capacity planning at one hand and operations on the other hand. At the same time, it presents an illustration on how process mining can be used for analysis of train describer data.
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Notes
A graph is strongly connected if there is a path from each node to any other node.
Both train numbers and signals have been anonymised.
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Janssenswillen, G., Depaire, B. & Verboven, S. Detecting train reroutings with process mining. EURO J Transp Logist 7, 1–24 (2018). https://doi.org/10.1007/s13676-017-0105-8
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DOI: https://doi.org/10.1007/s13676-017-0105-8