A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Authors

Le Minh Kieu
Ashish Bhaskar
Edward Chung

Document Type

Journal Article

Publication Date

2015

Subject Area

place - australasia, ridership - behaviour, technology - passenger information, technology - ticketing systems

Keywords

Spatial travel pattern, Public transport, Smart Card, AFC, DBSCAN

Abstract

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part C Home Page:

http://www.sciencedirect.com/science/journal/0968090X

Recommended Citation

Kieu, L.M., Bhaskar, A., & Chung, E. (2015). A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data. Transportation Research Part C: Emerging Technologies, Available online 6 April 2015. In Press, Corrected Proof.