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Understanding public transit patterns with open geodemographics to facilitate public transport planning

Liu, Y; Cheng, T; (2018) Understanding public transit patterns with open geodemographics to facilitate public transport planning. Transportmetrica A: Transport Science pp. 1-28. 10.1080/23249935.2018.1493549. (In press). Green open access

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Abstract

Plentiful studies have discussed the potential applications of contactless smart card from understanding interchange patterns to transit network analysis and user classifications. However, the incomplete and anonymous nature of the smart card data inherently limit the interpretations and understanding of thefindings, whichfurther limit planning implementations. Geodemographics, as ‘an analysis of people by where they live’, can be utilised as a promising supplement to provide contextual information to transport planning. This paper develops a methodological framework that conjointly integrates personalised smart card data with open geodemographics so as to pursue a better understanding of the traveller’s behaviours. It adopts a text mining technology, latent Dirichlet allocation modelling, to extract the transit patterns from the personalised smart card data and then use the open geodemographics derived from census data to enhance the interpretation of the patterns. Moreover, it presents night tube as an example to illustrate its potential usefulness in public transport planning.

Type: Article
Title: Understanding public transit patterns with open geodemographics to facilitate public transport planning
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/23249935.2018.1493549
Publisher version: https://doi.org/10.1080/23249935.2018.1493549
Language: English
Additional information: © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10056537
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