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

Paulsen, Mads; Nagel, Kai

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.
Published in: Procedia Computer Science, 10.1016/j.procs.2019.04.112, Elsevier