Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Kieu, Le Minh, Bhaskar, Ashish, & Chung, Edward (2014) Transit passenger segmentation using travel regularity mined from Smart Card transactions data. In Transportation Research Board 93rd Annual Meeting, 12-16 January 2014, Washington, D.C.


Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.

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ID Code: 66571
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Smart Card, Travel regularity, Passenger market segmentation, DBSCAN, Big Data
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000)
Divisions: Current > Schools > School of Civil Engineering & Built Environment
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Current > Research Centres > Smart Transport Research Centre
Copyright Owner: Copyright 2014 Please consult the authors
Deposited On: 22 Jan 2014 22:12
Last Modified: 09 Apr 2014 07:16

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