Searching similar trajectories in real time: an effectiveness and efficiency study
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
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Because moving objects usually move on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks, like FNR-tree and MON-tree. But, because both FNR-tree and MON-tree store the moving object's segment, they can not support a spatio-temporal range query and a similar trajectory query. In this paper, we propose an efficient trajectory index structure for moving objects, named TMN-Tree (Trajectory of Moving objects on Network Tree), which can support not only a range query but also a similar trajectory query. In addition, we present query processing algorithms to support them. Main advantages of the TMN-tree are as follows; i) storing temporal data and spatial data in separate structures, ii) preserving the entire trajectories of moving objects, and iii) providing efficient trajectory-based query processing algorithms. Finally, we show that our trajectory index structure outperforms existing trajectory index structures, like FNR-Tree and MON-Tree.