Analysis of travel pattern changes due to a medium-term disruption on public transit networks using smart card data

摘要

This study aims to analyze the travel behavior changes due to medium-term disruption on public transit networks by using smart card data, as a potential substitute to before-after surveys. The case studies are metro station closures in Montreal, Canada. The study examines the effects of the closures at the aggregate and disaggregate levels, in order to examine the travel pattern changes due to the presented disruption event. The study shows that even a medium-term disruption could have long-term impact on the travel patterns of frequent users of the impacted infrastructure. This study presents a first attempt to use passive data for analyzing the impacts of public transit service disruption on transit customers’ behavior in Montreal. Several limitations and some of the ongoing and future research topics to address the limitations are also discussed.