Large-Scale Assignment of Congested Bicycle Traffic Using Speed Heterogeneous Agents

Mads Paulsen*, Kai Nagel

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Despite requiring less space than most other modes of transport, bicycle traffic will also be prone to congestion when the traffic volume is sufficiently large. Such congestion can eventually influence the route choices of cyclists using the network. In this study we model bicycle congestion on a detailed network of the greater Copenhagen area by assigning an entire day of bicycle traffic using a recently developed method for dynamic network loading of speed heterogeneous multi-lane bicycle traffic. The model iteratively assigns appropriate routes for more than a million bicycle trips in the demand sensitive network, and with computation times of less than 15 minutes per iteration the proposed model proves to be large-scale applicable. This makes it the first dedicated bicycle traffic assignment model to account for congestion. The results indicate that the solid bicycle infrastructure of Copenhagen and cyclists’ willingness to change routes are key to keeping travel times low for cyclists.

Original languageEnglish
JournalProcedia Computer Science
Volume151
Pages (from-to)820-825
ISSN1877-0509
DOIs
Publication statusPublished - 2019
Event10th International Conference on Ambient Systems, Networks and Technologies - Leuven, Belgium
Duration: 29 Apr 20192 May 2019

Conference

Conference10th International Conference on Ambient Systems, Networks and Technologies
CountryBelgium
CityLeuven
Period29/04/201902/05/2019

Keywords

  • Bicycle traffic assignment
  • Bicycle congestion modelling
  • Multi-agent simulation
  • Speed heterogeneity

Cite this

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title = "Large-Scale Assignment of Congested Bicycle Traffic Using Speed Heterogeneous Agents",
abstract = "Despite requiring less space than most other modes of transport, bicycle traffic will also be prone to congestion when the traffic volume is sufficiently large. Such congestion can eventually influence the route choices of cyclists using the network. In this study we model bicycle congestion on a detailed network of the greater Copenhagen area by assigning an entire day of bicycle traffic using a recently developed method for dynamic network loading of speed heterogeneous multi-lane bicycle traffic. The model iteratively assigns appropriate routes for more than a million bicycle trips in the demand sensitive network, and with computation times of less than 15 minutes per iteration the proposed model proves to be large-scale applicable. This makes it the first dedicated bicycle traffic assignment model to account for congestion. The results indicate that the solid bicycle infrastructure of Copenhagen and cyclists’ willingness to change routes are key to keeping travel times low for cyclists.",
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author = "Mads Paulsen and Kai Nagel",
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Large-Scale Assignment of Congested Bicycle Traffic Using Speed Heterogeneous Agents. / Paulsen, Mads; Nagel, Kai .

In: Procedia Computer Science, Vol. 151, 2019, p. 820-825.

Research output: Contribution to journalJournal articleResearchpeer-review

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T1 - Large-Scale Assignment of Congested Bicycle Traffic Using Speed Heterogeneous Agents

AU - Paulsen, Mads

AU - Nagel, Kai

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AB - Despite requiring less space than most other modes of transport, bicycle traffic will also be prone to congestion when the traffic volume is sufficiently large. Such congestion can eventually influence the route choices of cyclists using the network. In this study we model bicycle congestion on a detailed network of the greater Copenhagen area by assigning an entire day of bicycle traffic using a recently developed method for dynamic network loading of speed heterogeneous multi-lane bicycle traffic. The model iteratively assigns appropriate routes for more than a million bicycle trips in the demand sensitive network, and with computation times of less than 15 minutes per iteration the proposed model proves to be large-scale applicable. This makes it the first dedicated bicycle traffic assignment model to account for congestion. The results indicate that the solid bicycle infrastructure of Copenhagen and cyclists’ willingness to change routes are key to keeping travel times low for cyclists.

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KW - Multi-agent simulation

KW - Speed heterogeneity

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