An adaptive trajectory compression and feature preservation method for maritime traffic analysis

Shaoqing Guo*, Victor Bolbot, Osiris Valdez Banda

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Ship trajectory data extracted from Automatic Identification System (AIS) has been extensively used for maritime traffic analysis. Yet the enormous volume of AIS data has come with substantial challenges related to storing, processing, analyzing, transmitting, and transferring. Trajectory compression techniques have been widely investigated to remedy the challenge. However, conventional compression techniques such as Douglas-Peucker (DP) algorithm mainly depend on line simplification algorithms, falling short in accurately identifying and preserving crucial information within trajectories. Moreover, using kinematic information from AIS data has posed difficulties associated with compression threshold determination. Hence, an adaptive method capable of considering multiple information from AIS is required. In this paper, a Top-Down Kinematic Compression (TDKC) algorithm aimed at adaptive trajectory compression and feature preservation is proposed. By incorporating time, position, speed, and course attributes from AIS data, TDKC exploits a Compression Binary Tree (CBT) method to address the recursion termination problem and determine the threshold automatically. A case study was conducted to evaluate the performance of TDKC using AIS data from Gulf of Finland, where a comparison with conventional algorithms and their improved versions based on specific performance evaluation metrics was involved. The results demonstrate TDKC's superiority in facilitating maritime traffic analysis.
Original languageEnglish
Article number119189
Number of pages31
JournalOcean Engineering
Volume312
Issue numberPart 2
DOIs
Publication statusPublished - 15 Nov 2024
MoE publication typeA1 Journal article-refereed

Keywords

  • AIS data
  • Adaptive ship trajectory compression
  • Data-driven analysis
  • Douglas-peucker algorithm
  • Feature preservation
  • op-down kinematic compression

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