Ship Trajectory Online Compression Algorithm Considering Handling Patterns
With the widespread use of shipborne Automatic Identification System (AIS) and the establishment of shore-based AIS networks in the past twenty years, a large amount of AIS trajectory data has been generated and accumulated in the shore-based systems. However, big data size increases the cost of sto...
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doaj-b38e0ed03efe47a4be7087be94d4bec02021-05-27T23:01:42ZengIEEEIEEE Access2169-35362021-01-019701827019110.1109/ACCESS.2021.30786429427209Ship Trajectory Online Compression Algorithm Considering Handling PatternsFeixiang Zhu0https://orcid.org/0000-0001-9579-0874Zhihong Ma1https://orcid.org/0000-0002-6427-2959Navigation College, Dalian Maritime University, Dalian, ChinaNavigation College, Dalian Maritime University, Dalian, ChinaWith the widespread use of shipborne Automatic Identification System (AIS) and the establishment of shore-based AIS networks in the past twenty years, a large amount of AIS trajectory data has been generated and accumulated in the shore-based systems. However, big data size increases the cost of storing, querying, and processing AIS data in practical applications. AIS data includes not only the ship spatial position information but also the course, speed, heading information <italic>et al</italic>. In other words, the knowledge of ship handling behavior is hidden in AIS data. In fact, many practical applications, such as maritime accident investigation and evidence collection, route extraction, ship behavior analysis, will require a compression algorithm to retain the ship key handling points in the original trajectory. To address these research challenges, the ship trajectory compression algorithm considering handling patterns is proposed in this paper. In order to explain the implicit handling patterns of AIS trajectories, the suggested method adopts the rate of course change (ROCC) and the rate of speed change (ROSC) in the sliding window as the criterion of whether the current trajectory point can be simplified. Numerical experiments are performed to verify the effectiveness of the proposed algorithm. Compared with Douglas-Peucker (DP) algorithm, Sliding Window (SW) algorithm, Opening Window Time Ratio (OPW-TR) algorithm, the results show that the proposed algorithm can efficiently compress trajectories by considering ship behavior patterns under application requirement.https://ieeexplore.ieee.org/document/9427209/Automatic identification systemhandling patternsship trajectorysliding windowtrajectory compression |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Feixiang Zhu Zhihong Ma |
spellingShingle |
Feixiang Zhu Zhihong Ma Ship Trajectory Online Compression Algorithm Considering Handling Patterns IEEE Access Automatic identification system handling patterns ship trajectory sliding window trajectory compression |
author_facet |
Feixiang Zhu Zhihong Ma |
author_sort |
Feixiang Zhu |
title |
Ship Trajectory Online Compression Algorithm Considering Handling Patterns |
title_short |
Ship Trajectory Online Compression Algorithm Considering Handling Patterns |
title_full |
Ship Trajectory Online Compression Algorithm Considering Handling Patterns |
title_fullStr |
Ship Trajectory Online Compression Algorithm Considering Handling Patterns |
title_full_unstemmed |
Ship Trajectory Online Compression Algorithm Considering Handling Patterns |
title_sort |
ship trajectory online compression algorithm considering handling patterns |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
With the widespread use of shipborne Automatic Identification System (AIS) and the establishment of shore-based AIS networks in the past twenty years, a large amount of AIS trajectory data has been generated and accumulated in the shore-based systems. However, big data size increases the cost of storing, querying, and processing AIS data in practical applications. AIS data includes not only the ship spatial position information but also the course, speed, heading information <italic>et al</italic>. In other words, the knowledge of ship handling behavior is hidden in AIS data. In fact, many practical applications, such as maritime accident investigation and evidence collection, route extraction, ship behavior analysis, will require a compression algorithm to retain the ship key handling points in the original trajectory. To address these research challenges, the ship trajectory compression algorithm considering handling patterns is proposed in this paper. In order to explain the implicit handling patterns of AIS trajectories, the suggested method adopts the rate of course change (ROCC) and the rate of speed change (ROSC) in the sliding window as the criterion of whether the current trajectory point can be simplified. Numerical experiments are performed to verify the effectiveness of the proposed algorithm. Compared with Douglas-Peucker (DP) algorithm, Sliding Window (SW) algorithm, Opening Window Time Ratio (OPW-TR) algorithm, the results show that the proposed algorithm can efficiently compress trajectories by considering ship behavior patterns under application requirement. |
topic |
Automatic identification system handling patterns ship trajectory sliding window trajectory compression |
url |
https://ieeexplore.ieee.org/document/9427209/ |
work_keys_str_mv |
AT feixiangzhu shiptrajectoryonlinecompressionalgorithmconsideringhandlingpatterns AT zhihongma shiptrajectoryonlinecompressionalgorithmconsideringhandlingpatterns |
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1721425241702400000 |