Analyzing Transit User Behavior with 51 Weeks of Smart Card Data

Elodie Deschaintres · Catherine Morency · Martin Trépanier

48 citations0/0 files storedTransportation Research Record Journal of the Transportation Research Board

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Transportation Planning and Optimization Urban Transport and Accessibility Human Mobility and Location-Based Analysis

Abstract

A better understanding of mobility behaviors is relevant to many applications in public transportation, from more accurate travel demand models to improved supply adjustment, customized services and integrated pricing. In line with this context, this study mined 51 weeks of smart card (SC) data from Montréal, Canada to analyze interpersonal and intrapersonal variability in the weekly use of public transit. Passengers who used only one type of product (AP − annual pass, MP − monthly pass, or TB − ticket book) over 12 months were selected, amounting to some 200,000 cards. Data was first preprocessed and summarized into card-week vectors to generate a typology of weeks. The most popular weekly patterns were identified for each type of product and further studied at the individual level. Sequences of week clusters were constructed to represent the weekly travel behavior of each user over 51 weeks. They were then segmented by type of product according to an original distance, therefore highlighting the heterogeneity between passengers. Two indicators were also proposed to quantify intrapersonal regularity as the repetition of weekly clusters throughout the weeks. The results revealed MP owners have a more regular and diversified use of public transit. AP users are mainly commuters whereas TB users tend to be more occasional transit users. However, some atypical groups were found for each type of product, for instance users with 4-day work weeks and loyal TB users.

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References

2011Smart card data use in public transit: A literature review 2013Mining smart card data for transit riders’ travel patterns 2003Habitual travel behaviour: Evidence from a six-week travel diary 2007Measuring transit use variability with smart-card data 2006MINING PUBLIC TRANSPORT USER BEHAVIOUR FROM SMART CARD DATA 2016Inferring patterns in the multi-week activity sequences of public transport users 2017Analyzing year-to-year changes in public transport passenger behaviour using smart card data 1998Activity Pattern Analysis by Means of Sequence-Alignment Methods

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