Publication Type

Journal Article

Version

publishedVersion

Publication Date

2-2017

Abstract

Concerned by the nuisances of motorized travel on urban life, policy makers are faced with the challenge of making cycling a more attractive alternative for everyday transportation. Route choice models can help achieve this objective by gaining insights into the trade-offs cyclists make when choosing their routes and by allowing the effect of infrastructure improvements to be analyzed. We estimate a link-based bike route choice model from a sample of GPS observations in the city of Eugene on a network comprising over 40,000 links. The so-called recursive logit (RL) model (Fosgerau et al., 2013) does not require to sample any choice set of paths. We show the advantages of this approach in the context of prediction by focusing on two applications of the model: link flows and accessibility measures. Compared to the path-based approach which requires to generate choice sets, the RL model proves to make significant gains in computational time and to avoid paradoxical accessibility measure results discussed in previous works, e.g. Nassir et al. (2014).

Keywords

Bike route choice, Recursive logit, Infinite choice set, Accessibility, Link flows

Discipline

Infrastructure | OS and Networks

Research Areas

Intelligent Systems and Optimization

Publication

Transportation Research Part C: Emerging Technologies

Volume

75

First Page

183

Last Page

196

ISSN

0968-090X

Identifier

10.1016/j.trc.2016.12.009

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.trc.2016.12.009

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