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

L.-M. Kieu, A. Bhaskar, Edward Chin Shin Chung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

52 Citations (Scopus)


© 2015 Elsevier Ltd.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.
Original languageEnglish
Pages (from-to)193-207
Number of pages15
JournalTransportation Research Part C: Emerging Technologies
Publication statusPublished - 1 Sep 2015
Externally publishedYes


  • AFC
  • Public transport
  • Smart Card
  • Spatial travel pattern

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications

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