Passenger segmentation using smart card data
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32860841. |
Description
Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.
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ID Code: | 79563 | ||
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Item Type: | Contribution to Journal (Journal Article) | ||
Refereed: | Yes | ||
ORCID iD: |
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Measurements or Duration: | 12 pages | ||
Keywords: | AFC, Market segmentation, Public transport, Smart Card, Travel pattern | ||
DOI: | 10.1109/TITS.2014.2368998 | ||
ISSN: | 1558-0016 | ||
Pure ID: | 32860841 | ||
Divisions: | Past > Institutes > Institute for Future Environments Past > QUT Faculties & Divisions > Science & Engineering Faculty Current > Research Centres > Smart Transport Research Centre |
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Copyright Owner: | 2014 IEEE | ||
Copyright Statement: | © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||
Deposited On: | 18 Dec 2014 05:19 | ||
Last Modified: | 02 Aug 2024 08:58 |
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