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Computing Multimodal Journeys in Practice

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Part of the book series:Lecture Notes in Computer Science ((LNTCS,volume 7933))

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Abstract

We study the problem of finding multimodal journeys in transportation networks, including unrestricted walking, driving, cycling, and schedule-based public transportation. A natural solution to this problem is to use multicriteria search, but it tends to be slow and to produce too many journeys, several of which are of little value. We propose algorithms to compute a full Pareto set and then score the solutions in a postprocessing step using techniques from fuzzy logic, quickly identifying the most significant journeys. We also propose several (still multicriteria) heuristics to find similar journeys much faster, making the approach practical even for large metropolitan areas.

Partial support by DFG grant WA654/16-1 and EU grant 288094 (eCOMPASS).

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Author information

Authors and Affiliations

  1. Microsoft Research Silicon Valley, Mountain View, CA, 94043, USA

    Daniel Delling & Renato F. Werneck

  2. Karlsruhe Institute of Technology (KIT), 76128, Karlsruhe, Germany

    Julian Dibbelt, Thomas Pajor & Dorothea Wagner

Authors
  1. Daniel Delling

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  2. Julian Dibbelt

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  3. Thomas Pajor

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  4. Dorothea Wagner

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  5. Renato F. Werneck

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Editor information

Editors and Affiliations

  1. Institute for Systems Analysis and Computer Science (IASI), National Research Council (CNR), Viale Manzoni 30, 00185, Rome, Italy

    Vincenzo Bonifaci

  2. Department of Computer and Systems Science, Sapienza University of Rome, Via Ariosto 25, 00185, Rome, Italy

    Camil Demetrescu  & Alberto Marchetti-Spaccamela  & 

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Delling, D., Dibbelt, J., Pajor, T., Wagner, D., Werneck, R.F. (2013). Computing Multimodal Journeys in Practice. In: Bonifaci, V., Demetrescu, C., Marchetti-Spaccamela, A. (eds) Experimental Algorithms. SEA 2013. Lecture Notes in Computer Science, vol 7933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38527-8_24

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