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Public Transit Labeling

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Experimental Algorithms (SEA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9125))

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Abstract

We study the journey planning problem in public transit networks. Developing efficient preprocessing-based speedup techniques for this problem has been challenging: current approaches either require massive preprocessing effort or provide limited speedups. Leveraging recent advances in Hub Labeling, the fastest algorithm for road networks, we revisit the well-known time-expanded model for public transit. Exploiting domain-specific properties, we provide simple and efficient algorithms for the earliest arrival, profile, and multicriteria problems, with queries that are orders of magnitude faster than the state of the art.

Work done mostly while all authors were at Microsoft Research Silicon Valley.

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Author information

Authors and Affiliations

  1. Sunnyvale, CA, USA

    Daniel Delling

  2. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Julian Dibbelt

  3. Microsoft Research, New York, NY, USA

    Thomas Pajor

  4. San Francisco, CA, USA

    Renato F. Werneck

Authors
  1. Daniel Delling
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  2. Julian Dibbelt
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  3. Thomas Pajor
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  4. Renato F. Werneck
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Corresponding author

Correspondence to Julian Dibbelt .

Editor information

Editors and Affiliations

  1. Université Pierre et Marie Curie LIP6, Paris, France

    Evripidis Bampis

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© 2015 Springer International Publishing Switzerland

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Delling, D., Dibbelt, J., Pajor, T., Werneck, R.F. (2015). Public Transit Labeling. In: Bampis, E. (eds) Experimental Algorithms. SEA 2015. Lecture Notes in Computer Science(), vol 9125. Springer, Cham. https://doi.org/10.1007/978-3-319-20086-6_21

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  • DOI: https://doi.org/10.1007/978-3-319-20086-6_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20085-9

  • Online ISBN: 978-3-319-20086-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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