Ship trajectory data compression based on SH-DP algorithm

Zhilong Ma

doi:10.1117/12.3015797

20 February 2024 Ship trajectory data compression based on SH-DP algorithm

Zhilong Ma

Proceedings Volume 13064, Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023); 130642N (2024) https://doi.org/10.1117/12.3015797
Event: 7th International Conference on Traffic Engineering and Transportation System (ICTETS 2023), 2023, Dalian, China

Abstract

The traditional Douglas Pucker (DP) ship trajectory compression algorithm usually suffers from high trajectory distortion and the loss of important trajectory "inflection points". The compressed data cannot restore the true traffic flow characteristics. In order to improve the quality of ship trajectory compression, this paper proposes a trajectory compression algorithm based on SH-DP, which adds two important latitude information, namely ship speed and heading, to the traditional DP compression algorithm. Firstly, by traversing all trajectory points on the trajectory, the distance, mean speed difference, and maximum steering angle are calculated and compared with their respective thresholds to segment the trajectory. Secondly, trajectory feature points are filtered and retained for the segmented sub trajectories. Finally, compressed trajectory point data is output in chronological order, which not only preserves more trajectory feature points but also improves trajectory compression rate. The experiment was conducted using ship trajectory data from the Baoshan Waterway in Shanghai. By comparing with traditional compression algorithms, the results showed that the ship trajectory compressed by the method in the article was closest to the original trajectory.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhilong Ma "Ship trajectory data compression based on SH-DP algorithm", Proc. SPIE 13064, Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023), 130642N (20 February 2024); https://doi.org/10.1117/12.3015797

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