Fast Routing in Very Large Public Transportation Networks Using Transfer Patterns

  • Hannah Bast
  • Erik Carlsson
  • Arno Eigenwillig
  • Robert Geisberger
  • Chris Harrelson
  • Veselin Raychev
  • Fabien Viger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6346)

Abstract

We show how to route on very large public transportation networks (up to half a billion arcs) with average query times of a few milliseconds. We take into account many realistic features like: traffic days, walking between stations, queries between geographic locations instead of a source and a target station, and multi-criteria cost functions. Our algorithm is based on two key observations: (1) many shortest paths share the same transfer pattern, i.e., the sequence of stations where a change of vehicle occurs; (2) direct connections without change of vehicle can be looked up quickly. We precompute the respective data; in practice, this can be done in time linear in the network size, at the expense of a small fraction of non-optimal results. We have accelerated public transportation routing on Google Maps with a system based on our ideas. We report experimental results for three data sets of various kinds and sizes.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hannah Bast
    • 1
    • 2
  • Erik Carlsson
    • 2
  • Arno Eigenwillig
    • 2
  • Robert Geisberger
    • 3
    • 2
  • Chris Harrelson
    • 2
  • Veselin Raychev
    • 2
  • Fabien Viger
    • 2
  1. 1.Albert-Ludwigs-Universität FreiburgFreiburgGermany
  2. 2.GoogleZürichSwitzerland
  3. 3.Karlsruhe Institute of Technology (KIT)KarlsruheGermany

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