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Document
Efficient Algorithms for Fully Multimodal Journey Planning

Authors: Moritz Potthoff and Jonas Sauer

Published in: OASIcs, Volume 106, 22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022)


Abstract
We study the journey planning problem for fully multimodal networks consisting of public transit and an arbitrary number of non-schedule-based transfer modes (e.g., walking, e-scooter, bicycle). Obtaining reasonable results in this setting requires multicriteria optimization, making the problem highly complex. Previous approaches were either limited to a single transfer mode or suffered from prohibitively slow running times. We establish a fully multimodal journey planning model that excludes undesirable solutions and can be solved efficiently. We extend existing efficient bimodal algorithms to our model and propose a new algorithm, HydRA, which enables even faster queries. On metropolitan and mid-sized country networks with walking and e-scooter as transfer modes, HydRA achieves query times of around 30 ms, which is fast enough for interactive applications.

Cite as

Moritz Potthoff and Jonas Sauer. Efficient Algorithms for Fully Multimodal Journey Planning. In 22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022). Open Access Series in Informatics (OASIcs), Volume 106, pp. 14:1-14:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


Copy BibTex To Clipboard

@InProceedings{potthoff_et_al:OASIcs.ATMOS.2022.14,
  author =	{Potthoff, Moritz and Sauer, Jonas},
  title =	{{Efficient Algorithms for Fully Multimodal Journey Planning}},
  booktitle =	{22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022)},
  pages =	{14:1--14:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-259-4},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{106},
  editor =	{D'Emidio, Mattia and Lindner, Niels},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2022.14},
  URN =		{urn:nbn:de:0030-drops-171181},
  doi =		{10.4230/OASIcs.ATMOS.2022.14},
  annote =	{Keywords: Algorithms, Journey Planning, Multimodal, Multicriteria, Public Transit}
}
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