iBAT : detecting anomalous taxi trajectories from GPS traces - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2011

iBAT : detecting anomalous taxi trajectories from GPS traces

Résumé

GPS-equipped taxis can be viewed as pervasive sensors and the large-scale digital traces produced allow us to reveal many hidden "facts" about the city dynamics and human behaviors. In this paper, we aim to discover anomalous driving patterns from taxi's GPS traces, targeting applications like automatically detecting taxi driving frauds or road network change in modern cites. To achieve the objective, firstly we group all the taxi trajectories crossing the same source destination cell-pair and represent each taxi trajectory as a sequence of symbols. Secondly, we propose an Isolation-Based Anomalous Trajectory (iBAT) detection method and verify with large scale taxi data that iBAT achieves remarkable performance (AUC>0.99, over 90% detection rate at false alarm rate of less than 2%). Finally, we demonstrate the potential of iBAT in enabling innovative applications by using it for taxi driving fraud detection and road network change detection
Fichier non déposé

Dates et versions

hal-01302049 , version 1 (13-04-2016)

Identifiants

Citer

Daqing Zhang, Nan Li, Zhi-Hua Zhou, Chao Chen, Lin Sun, et al.. iBAT : detecting anomalous taxi trajectories from GPS traces. UBICOMP 2011 : 13th ACM International Conference on Ubiquitous Computing, Sep 2011, Beijing, China. pp.99 - 108, ⟨10.1145/2030112.2030127⟩. ⟨hal-01302049⟩
101 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More