Analysis of bike route choice behaviour using the link-based recursive logit model

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. Despite the clear advantage of being healthy, cheap and sustainable, cycling yet fails to grow into more than a marginal mode of transport. One of the barriers lies in the design of road networks, which are often unsafe and unpractical for bike use. Route choice models can help achieve this objective by gaining insight into the trade-offs cyclists make when choosing their routes, hence providing helpful guidance for improving network infrastructure. The issue associated with such models is choice set generation, a time-consuming and theoretically problematic imperative. The contribution of this study consists in estimating a link-based bike route choice model which does not require to sample any choice set of paths. Moreover, we will provide validation results as well as comparing predicted bike traffic flows with traffic counts in a real network. These results are important to the partner organization in order to assess the possible impact of integrating the model in their traffic simulation software.

Faculty Supervisor:

Emma Frejinger

Student:

Partner:

INRO Consultants Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program: