Finding frequent sub-trajectories with time constraints
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
Computing similarity of coarse and irregular trajectories using space-time prisms
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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This article describes a novel approach for finding similar trajectories, using trajectory segmentation based on movement parameters MPs such as speed, acceleration, or direction. First, a segmentation technique is applied to decompose trajectories into a set of segments with homogeneous characteristics with respect to a particular MP. Each segment is assigned to a movement parameter class MPC, representing the behavior of the MP. Accordingly, the segmentation procedure transforms a trajectory to a sequence of class labels, that is, a symbolic representation. A modified version of edit distance called normalized weighted edit distance NWED is introduced as a similarity measure between different sequences. As an application, we demonstrate how the method can be employed to cluster trajectories. The performance of the approach is assessed in two case studies using real movement datasets from two different application domains, namely, North Atlantic Hurricane trajectories and GPS tracks of couriers in London. Three different experiments have been conducted that respond to different facets of the proposed techniques and that compare our NWED measure to a related method.