Paper Info
Title
Perspectives on Stability and Mobility of Passenger's Travel Behavior through Smart Card Data
Abstract
Existing studies have extensively used spatiotemporal data to discover the mobility patterns of various types of travellers. Smart card data (SCD) collected by the automated fare collection systems can reflect a general view of the mobility pattern of public transit riders. Mobility patterns of transit riders are temporally and spatially dynamic, and therefore difficult to measure. However, few existing studies measure both the mobility and stability of transit riders’ travel patterns over a long period of time. To analyse the long-term changes of transit riders’ travel behaviour, the authors define a metric for measuring the similarity between SCD, in this study. Also an improved density-based clustering algorithm, simplified smoothed ordering points to identify the clustering structure (SS-OPTICS), to identify transit rider clusters is proposed. Compared to the original OPTICS, SS-OPTICS needs fewer parameters and has better generalisation ability. Further, the generated clusters are categorised according to their features of regularity and occasionality. Based on the generated clusters and categories, fine- and coarse-grained travel pattern transitions of transit riders over four years from 2010 to 2014 are measured. By combining socioeconomic data of Beijing in the year of 2010 and 2014, the interdependence between stability and mobility of transit riders’ travel behaviour is also discussed.
Year
DOI
Venue
2015
10.1049/iet-its.2019.0212
Iet Intelligent Transport Systems
Keywords
DocType
Volume
smart cards,pattern clustering,traffic engineering computing
Journal
13
Issue
ISSN
Citations 
12
1751-956X
6
PageRank 
References 
Authors
0.53
8
2
Name
Order
Citations
PageRank
Zhiyong Cui1161.39
LONG Ying2309.46