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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Bibliographic Details
Published in:IEEE access Vol. 9; pp. 70182 - 70191
Main Authors: Zhu, Feixiang, Ma, Zhihong
Format: Journal Article
Language:English
Published: Piscataway IEEE 2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accident investigation
Accident investigations
Algorithms
Artificial intelligence
Automatic identification system
Compression algorithms
Forensic engineering
Handling
handling patterns
Heuristic algorithms
Marine vehicles
Shape
ship trajectory
Sliding
sliding window
Trajectory
trajectory compression
Turning
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary: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 et al . 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.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3078642