Route Planning in Transportation Networks

  • Hannah Bast
  • Daniel Delling
  • Andrew Goldberg
  • Matthias Müller-Hannemann
  • Thomas Pajor
  • Peter Sanders
  • Dorothea Wagner
  • Renato F. Werneck
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9220)

Abstract

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Hannah Bast
    • 1
  • Daniel Delling
    • 2
  • Andrew Goldberg
    • 3
  • Matthias Müller-Hannemann
    • 4
  • Thomas Pajor
    • 5
  • Peter Sanders
    • 6
  • Dorothea Wagner
    • 6
  • Renato F. Werneck
    • 3
  1. 1.University of FreiburgFreiburg im BreisgauGermany
  2. 2.Apple Inc.CupertinoUSA
  3. 3.AmazonSeattleUSA
  4. 4.Martin-Luther-Universität Halle-WittenbergHalleGermany
  5. 5.Microsoft ResearchMountain ViewUSA
  6. 6.Karlsruhe Institute of TechnologyKarlsruheGermany

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