Skip to main content

Fast Routing in Very Large Public Transportation Networks Using Transfer Patterns

  • Conference paper
Algorithms – ESA 2010 (ESA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6346))

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Extended version of this paper, http://ad.informatik.uni-freiburg.de/papers

  2. Bast, H.: Car or public transport – two worlds. In: Albers, S., Alt, H., Näher, S. (eds.) Efficient Algorithms. LNCS, vol. 5760, pp. 355–367. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  3. Berger, A., Delling, D., Gebhardt, A., Müller-Hannemann, M.: Accelerating time-dependent multi-criteria timetable information is harder than expected. In: ATMOS 2009. Dagstuhl Seminar Proceedings (2009)

    Google Scholar 

  4. Delling, D.: Time-dependent SHARC-routing. In: Halperin, D., Mehlhorn, K. (eds.) ESA 2008. LNCS, vol. 5193, pp. 332–343. Springer, Heidelberg (2008)

    Google Scholar 

  5. Delling, D., Sanders, P., Schultes, D., Wagner, D.: Engineering route planning algorithms. In: Lerner, J., Wagner, D., Zweig, K.A. (eds.) Algorithmics of Large and Complex Networks. LNCS, vol. 5515, pp. 117–139. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Disser, Y., Müller-Hannemann, M., Schnee, M.: Multi-criteria shortest paths in time-dependent train networks. In: McGeoch, C.C. (ed.) WEA 2008. LNCS, vol. 5038, pp. 347–361. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  7. Geisberger, R.: Contraction of timetable networks with realistic transfers. In: Festa, P. (ed.) SEA 2010. LNCS, vol. 6049, pp. 71–82. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  8. Loui, R.P.: Optimal paths in graphs with stochastic or multidimensional weights. Commun. ACM 26, 670–676 (1983)

    Article  MATH  MathSciNet  Google Scholar 

  9. Möhring, R.H.: Verteilte Verbindungssuche im öffentlichen Personenverkehr: Graphentheoretische Modelle und Algorithmen. In: Horster, P. (ed.) Angewandte Mathematik – insbesondere Informatik, pp. 192–220. Vieweg (1999)

    Google Scholar 

  10. Müller-Hannemann, M., Schulz, F., Wagner, D., Zaroliagis, C.: Timetable information: Models and algorithms. In: Geraets, F., Kroon, L.G., Schoebel, A., Wagner, D., Zaroliagis, C.D. (eds.) Railway Optimization 2004. LNCS, vol. 4359, pp. 67–90. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  11. Pyrga, E., Schulz, F., Wagner, D., Zaroliagis, C.D.: Efficient models for timetable information in public transportation systems. J. Exp. Algorithmics 12 (2007)

    Google Scholar 

  12. Schultes, D., Sanders, P.: Dynamic highway-node routing. In: Demetrescu, C. (ed.) WEA 2007. LNCS, vol. 4525, pp. 66–79. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  13. Theune, D.: Robuste und effiziente Methoden zur Lösung von Wegproblemen. Teubner (1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bast, H. et al. (2010). Fast Routing in Very Large Public Transportation Networks Using Transfer Patterns. In: de Berg, M., Meyer, U. (eds) Algorithms – ESA 2010. ESA 2010. Lecture Notes in Computer Science, vol 6346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15775-2_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15775-2_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15774-5

  • Online ISBN: 978-3-642-15775-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics