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Documents authored by Gebhardt, Andreas

Document
DOI: 10.4230/OASIcs.ATMOS.2011.100
Stochastic Delay Prediction in Large Train Networks

Authors: Annabell Berger, Andreas Gebhardt, Matthias Müller-Hannemann, and Martin Ostrowski

Published in: OASIcs, Volume 20, 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (2011)

Abstract
In daily operation, railway traffic always deviates from the planned schedule to a certain extent. Primary initial delays of trains may cause a whole cascade of secondary delays of other trains over the entire network. In this paper, we propose a stochastic model for delay propagation and forecasts of arrival and departure events which is applicable to all kind of public transport (not only to railway traffic). Our model is fairly realistic, it includes general waiting policies (how long do trains wait for delayed feeder trains), it uses driving time profiles (discrete distributions) on travel arcs which depend on the departure time, and it incorporates the catch-up potential of buffer times on driving sections and train stops. The model is suited for an online scenario where a massive stream of update messages on the current status of trains arrives which has to be propagated through the whole network. Efficient stochastic propagation of delays has important applications in online timetable information, in delay management and train disposition, and in stability analysis of timetables. The proposed approach has been implemented and evaluated on the German timetable of 2011 with waiting policies of Deutsche Bahn AG. A complete stochastic delay propagation for the whole German train network and a whole day can be performed in less than 14 seconds on a PC. We tested our propagation algorithm with artificial discrete travel time distributions which can be parametrized by the size of their fluctuations. Our forecasts are compared with real data. It turns out that stochastic propagation of delays is efficient enough to be applicable in practice, but the forecast quality requires further adjustments of our artificial travel time distributions to estimates from real data.
Cite as

Annabell Berger, Andreas Gebhardt, Matthias Müller-Hannemann, and Martin Ostrowski. Stochastic Delay Prediction in Large Train Networks. In 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Open Access Series in Informatics (OASIcs), Volume 20, pp. 100-111, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@InProceedings{berger_et_al:OASIcs.ATMOS.2011.100,
  author =	{Berger, Annabell and Gebhardt, Andreas and M\"{u}ller-Hannemann, Matthias and Ostrowski, Martin},
  title =	{{Stochastic Delay Prediction in Large Train Networks}},
  booktitle =	{11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems},
  pages =	{100--111},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-33-0},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{20},
  editor =	{Caprara, Alberto and Kontogiannis, Spyros},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2011.100},
  URN =		{urn:nbn:de:0030-drops-32705},
  doi =		{10.4230/OASIcs.ATMOS.2011.100},
  annote =	{Keywords: stochastic delay propagation, timetable information, delay management, train disposition, stability analysis}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2009.2148
Accelerating Time-Dependent Multi-Criteria Timetable Information is Harder Than Expected

Authors: Annabell Berger, Daniel Delling, Andreas Gebhardt, and Matthias Müller-Hannemann

Published in: OASIcs, Volume 12, 9th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'09) (2009)

Abstract
Speeding up multi-criteria search in real timetable information systems remains a challenge in spite of impressive progress achieved in recent years for related problems in road networks. Our goal is to perform multi-criteria range queries, that is, to find all Pareto-optimal connections with respect to travel time and number of transfers within a given start time interval. This problem can be modeled as a path search problem in a time- and event-dependent graph. In this paper, we investigate two key speed-up techniques for a multi-criteria variant of \textsc{Dijkstra}'s algorithm --- arc flags and contraction --- which seem to be strong candidates for railway networks, too. We describe in detail how these two techniques have to be adapted for a multi-criteria scenario and explain why we can expect only marginal speed-ups (compared to observations in road networks) from a direct implementation. Based on these insights we extend traditional arc-flags to \emph{time-period flags} and introduce \emph{route contraction} as a substitute for node contraction. A computational study on real queries demonstrates that these techniques combined with goal-directed search lead to a speed-up of factor 13.08 over the baseline variant for range queries for a full day.
Cite as

Annabell Berger, Daniel Delling, Andreas Gebhardt, and Matthias Müller-Hannemann. Accelerating Time-Dependent Multi-Criteria Timetable Information is Harder Than Expected. In 9th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'09). Open Access Series in Informatics (OASIcs), Volume 12, pp. 1-21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{berger_et_al:OASIcs.ATMOS.2009.2148,
  author =	{Berger, Annabell and Delling, Daniel and Gebhardt, Andreas and M\"{u}ller-Hannemann, Matthias},
  title =	{{Accelerating Time-Dependent Multi-Criteria Timetable Information is Harder Than Expected}},
  booktitle =	{9th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'09)},
  pages =	{1--21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-11-8},
  ISSN =	{2190-6807},
  year =	{2009},
  volume =	{12},
  editor =	{Clausen, Jens and Di Stefano, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2009.2148},
  URN =		{urn:nbn:de:0030-drops-21481},
  doi =		{10.4230/OASIcs.ATMOS.2009.2148},
  annote =	{Keywords: Timetable information, multi-criteria search, time-dependent networks, arc flags, contraction Timetable information, multi-criteria search, time-dependent networks, arc flags, contraction}
}
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