Assessing the public transport travel behavior consistency from smart card data

Catalina Espinoza · Marcela A. Munizaga · Benjamín Bustos · Martin Trépanier

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

Abstract

The aim of this research is to measure, using smart card data, how much do public transport users change their behavior through time. To quantify the change in behavior, we split the smart card records of a user into a set of separated time windows. Then, we measure the variation between each pair of time windows. Three algorithms that calculate the variation in users’ mobility are assessed. Using data from a Canadian transport system, we show that measuring the stability of user behavior at an individual level provides new insights for public transport operators, e.g., it can be used to measure users’ adaptability to changes in the transport system.

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References

2008Understanding individual human mobility patterns 2010Limits of Predictability in Human Mobility 2011Smart card data use in public transit: A literature review 2012Estimation of a disaggregate multimodal public transport Origin–Destination matrix from passive smartcard data from Santiago, Chile 2003Habitual travel behaviour: Evidence from a six-week travel diary 2007Individual Trip Destination Estimation in a Transit Smart Card Automated Fare Collection System 2012Spatiotemporal Patterns of Urban Human Mobility 2014Behavioural data mining of transit smart card data: A data fusion approach

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2022Bayesian origin-destination estimation in networked transit systems using nodal in- and outflow counts 2021Exploring Equity in Public Transportation Planning Using Smart Card Data 2019Translation software: An alternative to transit data standards 2020Issues of Development of Smart Transport Assessment Indicators 2018Workshop Synthesis: Smart card data, new methods and applications for public transport

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