An adaptive trajectory compression and feature preservation method for maritime traffic analysis
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2024-11-15
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Language
en
Pages
31
Series
Ocean Engineering, Volume 312, issue Part 2
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.Description
Keywords
AIS data, Adaptive ship trajectory compression, Data-driven analysis, Douglas-peucker algorithm, Feature preservation, op-down kinematic compression
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Citation
Guo, S, Bolbot, V & Valdez Banda, O 2024, ' An adaptive trajectory compression and feature preservation method for maritime traffic analysis ', Ocean Engineering, vol. 312, no. Part 2, 119189 . https://doi.org/10.1016/j.oceaneng.2024.119189
