An online method for ship trajectory compression using AIS data
Loading...
Access rights
openAccess
CC BY
CC BY
publishedVersion
URL
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Date
2024-01
Major/Subject
Mcode
Degree programme
Language
en
Pages
22
Series
Journal of Navigation, Volume 77, issue 1, pp. 37-58
Abstract
Vessel trajectories from the Automatic Identification System (AIS) play an important role in maritime traffic management, but a drawback is the huge amount of memory occupation which thus results in a low speed of data acquisition in maritime applications due to a large number of scattered data. This paper proposes a novel online vessel trajectory compression method based on the Improved Open Window (IOPW) algorithm. The proposed method compresses vessel trajectory instantly according to vessel coordinates along with a timestamp driven by the AIS data. In particular, we adopt the weighted Euclidean distance (WED), fusing the perpendicular Euclidean distance (PED) and synchronous Euclidean distance (SED) in IOPW to improve the robustness. The realistic AIS-based vessel trajectories are used to illustrate the proposed model by comparing it with five traditional trajectory compression methods. The experimental results reveal that the proposed method could effectively maintain the important trajectory features and significantly reduce the rate of distance loss during the online compression of vessel trajectories.Description
Publisher Copyright: © The Author(s), 2024. Published by Cambridge University Press on behalf of The Royal Institute of Navigation.
Keywords
automatic identification system, improved open window algorithm, online compression, vessel trajectory
Other note
Citation
Liu, Z, Yuan, W, Liang, M, Zhang, M, Liu, C, Liu, R W & Liu, J 2024, ' An online method for ship trajectory compression using AIS data ', Journal of Navigation, vol. 77, no. 1, pp. 37-58 . https://doi.org/10.1017/S0373463324000171