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Probabilistic Simulation of a Railway Timetable

Authors Rebecca Haehn, Erika Ábrahám, Nils Nießen



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Author Details

Rebecca Haehn
  • RWTH Aachen University, LuFG THS, Germany
Erika Ábrahám
  • RWTH Aachen University, LuFG THS, Germany
Nils Nießen
  • RWTH Aachen University, VIA, Germany

Acknowledgements

We are gratefult to Deutsche Bahn for supporting us with data.

Cite AsGet BibTex

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)
https://doi.org/10.4230/OASIcs.ATMOS.2020.16

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.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Model development and analysis
Keywords
  • Railway
  • Modeling
  • Scheduling
  • Probabilistic systems
  • Optimization

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