Research Article
Real-Time Detection of Anomalous Taxi Trajectories from GPS Traces
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@INPROCEEDINGS{10.1007/978-3-642-30973-1_6, author={Chao Chen and Daqing Zhang and Pablo Samuel Castro and Nan Li and Lin Sun and Shijian Li}, title={Real-Time Detection of Anomalous Taxi Trajectories from GPS Traces}, proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 8th International ICST Conference, MobiQuitous 2011, Copenhagen, Denmark, December 6-9, 2011, Revised Selected Papers}, proceedings_a={MOBIQUITOUS}, year={2012}, month={10}, keywords={}, doi={10.1007/978-3-642-30973-1_6} }- Chao Chen
Daqing Zhang
Pablo Samuel Castro
Nan Li
Lin Sun
Shijian Li
Year: 2012
Real-Time Detection of Anomalous Taxi Trajectories from GPS Traces
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-642-30973-1_6
Abstract
Trajectories obtained from GPS-enabled taxis grant us an opportunity to not only extract meaningful statistics, dynamics and behaviors about certain urban road users, but also to monitor adverse and/or malicious events. In this paper we focus on the problem of detecting anomalous routes by comparing against historically “normal” routes. We propose a real-time method, , that is able to detect anomalous trajectories “on-the-fly”, as well as identify which parts of the trajectory are responsible for its anomalousness. We evaluate our method on a large dataset of taxi GPS logs and verify that it has excellent accuracy (AUC ≥ 0.99) and overcomes many of the shortcomings of other state-of-the-art methods.
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