Path complexity for observed and predicted bicyclist routes

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Everyday route choices made by bicyclists are known to be more difficult to explain than vehicle routes, yet prediction of these choices is essential for guiding infrastructural investment in safe cycling. In this paper we study how the concept of route complexity can help generate and analyze plausible choice sets in the demand modeling process. The complexity of a given path in a graph is the minimum number of shortest paths that is required to specify that path. Complexity is a path attribute which is considered to be important for route choice in a similar way as the number of left turns, the number of speed bumps, distance and other. The complexity was determined for a large set of observed routes and for routes in the generated choice sets for the corresponding origin-destination pairs. The respective distributions seem to significantly differ so that the choice sets do not reflect the traveler preferences. This paper looks at how the observed routes compare to routes generated by Breadth First Search Link Elimination and Double Stochastic Generation Function method.

Original languageEnglish
Pages (from-to)393-400
Number of pages8
JournalProcedia Computer Science
Volume151
Early online date21 May 2019
DOIs
Publication statusPublished - 2019
Event10th International Conference on Ambient Systems, Networks and Technologies, ANT 2019 and The 2nd International Conference on Emerging Data and Industry 4.0, EDI40 2019, Affiliated Workshops - Leuven, Belgium
Duration: 29 Apr 20192 May 2019

Bibliographical note

Part of special issue: The 10th International Conference on Ambient Systems, Networks and Technologies (ANT 2019) / The 2nd International Conference on Emerging Data and Industry 4.0 (EDI40 2019) / Affiliated Workshops. Edited by Elhadi Shakshuki

Keywords

  • Choice sets
  • Route choice generation
  • Route complexity

Cite this

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title = "Path complexity for observed and predicted bicyclist routes",
abstract = "Everyday route choices made by bicyclists are known to be more difficult to explain than vehicle routes, yet prediction of these choices is essential for guiding infrastructural investment in safe cycling. In this paper we study how the concept of route complexity can help generate and analyze plausible choice sets in the demand modeling process. The complexity of a given path in a graph is the minimum number of shortest paths that is required to specify that path. Complexity is a path attribute which is considered to be important for route choice in a similar way as the number of left turns, the number of speed bumps, distance and other. The complexity was determined for a large set of observed routes and for routes in the generated choice sets for the corresponding origin-destination pairs. The respective distributions seem to significantly differ so that the choice sets do not reflect the traveler preferences. This paper looks at how the observed routes compare to routes generated by Breadth First Search Link Elimination and Double Stochastic Generation Function method.",
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Path complexity for observed and predicted bicyclist routes. / Koch, Thomas; Knapen, Luk; Dugundji, Elenna.

In: Procedia Computer Science, Vol. 151, 2019, p. 393-400.

Research output: Contribution to JournalArticleAcademicpeer-review

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