Comparative study on the effectiveness of trajectory similarity measurement algorithms

Yanfu Wu

doi:10.1117/12.2626417

21 December 2021 Comparative study on the effectiveness of trajectory similarity measurement algorithms

Yanfu Wu

Proceedings Volume 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021); 121560S (2021) https://doi.org/10.1117/12.2626417
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 2021, Sanya, China

Abstract

Spatial-temporal trajectory data is a position sequence recording the time and space of moving objects. It is the most important data source for the study of moving objects. The analysis and mining of spatial-temporal trajectory data is a research hotspot of spatial data mining. In the process of analysis and mining, the similarity measurement between trajectories is a key problem. This paper studies the spatial-temporal trajectory similarity measurement algorithms, selects the trajectory similarity measurement algorithms based on Hausdorff distance and One Way distance as the research object, and sets three comparative experiments on the execution time, robustness and trajectory similarity discrimination effect of different location relations of the algorithm. Through the experimental results, the advantages, disadvantages and application occasions of the two algorithms are analyzed, It provides a reference for spatial-temporal trajectory analysis and mining.

Citation Download Citation

Yanfu Wu "Comparative study on the effectiveness of trajectory similarity measurement algorithms", Proc. SPIE 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 121560S (21 December 2021); https://doi.org/10.1117/12.2626417

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