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DOI: 10.4230/OASIcs.ATMOS.2020.16

Probabilistic Simulation of a Railway Timetable

Authors: Rebecca Haehn, Erika Ábrahám, and Nils Nießen

Published in: OASIcs, Volume 85, 20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020)

Abstract

Railway systems are often highly utilized, which makes them vulnerable to delay propagation. In order to minimize delays timetables are desired to be robust, a property that is often estimated by simulating the respective timetable for different deterministic delay values. To achieve an accurate estimation under consideration of uncertain delays many simulation runs need to be executed. Most established simulation systems additionally use microscopic models of the railway systems, which further increases the simulations running times and makes them applicable rather for small areas of interest for complexity reasons. In this paper, we present a probabilistic, symbolic simulation algorithm for given timetables, this means we do not simulate individual executions, but all possible executions at once. We use a macroscopic model of the railway infrastructure as input. This way we consider the railway systems in less detail but are able to examine certain performance indicators for larger areas. For a given input model this simulation computes exact results. We implement the algorithm, examine its results, and discuss possible improvements of this approach.

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Rebecca Haehn, Erika Ábrahám, and Nils Nießen. Probabilistic Simulation of a Railway Timetable. In 20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020). Open Access Series in Informatics (OASIcs), Volume 85, pp. 16:1-16:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{haehn_et_al:OASIcs.ATMOS.2020.16,
  author =	{Haehn, Rebecca and \'{A}brah\'{a}m, Erika and Nie{\ss}en, Nils},
  title =	{{Probabilistic Simulation of a Railway Timetable}},
  booktitle =	{20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020)},
  pages =	{16:1--16:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-170-2},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{85},
  editor =	{Huisman, Dennis and Zaroliagis, Christos D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2020.16},
  URN =		{urn:nbn:de:0030-drops-131527},
  doi =		{10.4230/OASIcs.ATMOS.2020.16},
  annote =	{Keywords: Railway, Modeling, Scheduling, Probabilistic systems, Optimization}
}

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Probabilistic Simulation of a Railway Timetable

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