iBOAT: Isolation-Based Online Anomalous Trajectory Detection

Trajectories obtained from Global Position System (GPS)-enabled taxis grant an opportunity not only to extract meaningful statistics, dynamics, and behaviors about certain urban road users but also to monitor adverse and/or malicious events. In this paper, the authors focus on the problem of detecting anomalous routes by comparing the latter against time-dependent historically “normal” routes. They propose an online method that is able to detect anomalous trajectories “on-the-fly” and to identify which parts of the trajectory are responsible for its anomalousness. Furthermore, they perform an in-depth analysis on around 43,800 anomalous trajectories that are detected out from the trajectories of 7600 taxis for a month, revealing that most of the anomalous trips are the result of conscious decisions of greedy taxi drivers to commit fraud. The authors evaluate the proposed isolation-based online anomalous trajectory (iBOAT) through extensive experiments on large-scale taxi data, and it shows that iBOAT achieves state-of-the-art performance, with a remarkable performance of the area under a curve (AUC) >= 0.99.

• Record URL:
  • https://doi.org/10.1109/TITS.2013.2238531
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Authors:
  • Chen, Chao
  • Zhang, Daqing
  • Castro, Pablo Samuel
  • Li, Nan
  • Sun, Lin
  • Li, Shijian
  • Wang, Zonghui
• Publication Date: 2013-6

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 806-818
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 14
  • Issue Number: 2
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Algorithms; Detection and identification systems; Methodology; Routes; Taxicabs; Vehicle trajectories
• Subject Areas: Data and Information Technology; Highways; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01524701
• Record Type: Publication
• Files: TLIB, TRIS
• Created Date: May 1 2014 4:36PM