Trajectory Set Similarity Measure: An EMD-Based Approach

  • Dan He
  • Boyu Ruan
  • Bolong Zheng
  • Xiaofang Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10837)


To address the trajectory sparsity issue concerning Origin-Destination (OD) pairs, in general, most existing studies strive to reconstruct trajectories by concatenating the sub-trajectories along the specific paths and filling up the sparsity with conceptual trajectories. However, none of them gives the robustness validation for their reconstructed trajectories. By intuition, the reconstructed trajectories are more qualified if they are more similar to the exact ones traversing directly from the origin to the destination, which indicates the effectiveness of the corresponding trajectory augmentation algorithms. Nevertheless, to our knowledge, no existing work has studied the similarity of trajectory sets. Motivated by this, we propose a novel similarity measure to evaluate the similarity between two set of trajectories, borrowing the idea of the Earth Mover’s Distance. Empirical studies on a large real trajectory dataset show that our proposed similarity measure is effective and robust.


Trajectory Trajectory set similarity Earth Mover’s Distance 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Dan He
    • 1
  • Boyu Ruan
    • 1
  • Bolong Zheng
    • 2
  • Xiaofang Zhou
    • 1
  1. 1.The University of QueenslandBrisbaneAustralia
  2. 2.Aalborg UniversityAalborgDenmark

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