AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development
With the advancement of satellite and 5G communication technologies, vehicles can transmit and exchange data from anywhere in the world. It has resulted in the generation of massive spatial trajectories, particularly from the Automatic Identification System (AIS) for surface vehicles. The massive AI...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Vehicular Technology |
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| Online Access: | https://ieeexplore.ieee.org/document/10636246/ |
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| _version_ | 1832582298623541248 |
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| author | Ryan Wen Liu Shiqi Zhou Shangkun Yin Yaqing Shu Maohan Liang |
| author_facet | Ryan Wen Liu Shiqi Zhou Shangkun Yin Yaqing Shu Maohan Liang |
| author_sort | Ryan Wen Liu |
| collection | DOAJ |
| description | With the advancement of satellite and 5G communication technologies, vehicles can transmit and exchange data from anywhere in the world. It has resulted in the generation of massive spatial trajectories, particularly from the Automatic Identification System (AIS) for surface vehicles. The massive AIS data lead to high storage requirements and computing costs, as well as low data transmission efficiency. These challenges highlight the critical importance of vessel trajectory compression for surface vehicles. However, the complexity and diversity of vessel trajectories and behaviors make trajectory compression imperative and challenging in maritime applications. Therefore, trajectory compression has been one of the hot spots in research on trajectory data mining. The major purpose of this work is to provide a comprehensive reference source for beginners involved in vessel trajectory compression. The current trajectory compression methods could be broadly divided into two types, batch (offline) and online modes. The principles and pseudo-codes of these methods will be provided and discussed in detail. In addition, compressive experiments on several publicly available data sets have been implemented to evaluate the batch and online compression methods in terms of computation time, compression ratio, trajectory similarity, and trajectory length loss rate. Finally, we develop a flexible and open software, called <italic>AISCompress</italic>, for AIS-based batch and online vessel trajectory compression. The conclusions and associated future works are also given to inspire future applications in vessel trajectory compression. |
| format | Article |
| id | doaj-art-4946b25a774446e18d64c576058ed310 |
| institution | Kabale University |
| issn | 2644-1330 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-4946b25a774446e18d64c576058ed3102025-01-30T00:04:41ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302024-01-0151193121410.1109/OJVT.2024.344367510636246AIS-Based Vessel Trajectory Compression: A Systematic Review and Software DevelopmentRyan Wen Liu0https://orcid.org/0000-0002-1591-5583Shiqi Zhou1Shangkun Yin2Yaqing Shu3Maohan Liang4https://orcid.org/0000-0001-7470-3313Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan, ChinaHubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan, ChinaHubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan, ChinaHubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan, ChinaDepartment of Civil and Environmental Engineering, National University of Singapore, SingaporeWith the advancement of satellite and 5G communication technologies, vehicles can transmit and exchange data from anywhere in the world. It has resulted in the generation of massive spatial trajectories, particularly from the Automatic Identification System (AIS) for surface vehicles. The massive AIS data lead to high storage requirements and computing costs, as well as low data transmission efficiency. These challenges highlight the critical importance of vessel trajectory compression for surface vehicles. However, the complexity and diversity of vessel trajectories and behaviors make trajectory compression imperative and challenging in maritime applications. Therefore, trajectory compression has been one of the hot spots in research on trajectory data mining. The major purpose of this work is to provide a comprehensive reference source for beginners involved in vessel trajectory compression. The current trajectory compression methods could be broadly divided into two types, batch (offline) and online modes. The principles and pseudo-codes of these methods will be provided and discussed in detail. In addition, compressive experiments on several publicly available data sets have been implemented to evaluate the batch and online compression methods in terms of computation time, compression ratio, trajectory similarity, and trajectory length loss rate. Finally, we develop a flexible and open software, called <italic>AISCompress</italic>, for AIS-based batch and online vessel trajectory compression. The conclusions and associated future works are also given to inspire future applications in vessel trajectory compression.https://ieeexplore.ieee.org/document/10636246/Automatic identification system (AIS)vessel trajectorytrajectory compressionerror metricssimilarity measure |
| spellingShingle | Ryan Wen Liu Shiqi Zhou Shangkun Yin Yaqing Shu Maohan Liang AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development IEEE Open Journal of Vehicular Technology Automatic identification system (AIS) vessel trajectory trajectory compression error metrics similarity measure |
| title | AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development |
| title_full | AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development |
| title_fullStr | AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development |
| title_full_unstemmed | AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development |
| title_short | AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development |
| title_sort | ais based vessel trajectory compression a systematic review and software development |
| topic | Automatic identification system (AIS) vessel trajectory trajectory compression error metrics similarity measure |
| url | https://ieeexplore.ieee.org/document/10636246/ |
| work_keys_str_mv | AT ryanwenliu aisbasedvesseltrajectorycompressionasystematicreviewandsoftwaredevelopment AT shiqizhou aisbasedvesseltrajectorycompressionasystematicreviewandsoftwaredevelopment AT shangkunyin aisbasedvesseltrajectorycompressionasystematicreviewandsoftwaredevelopment AT yaqingshu aisbasedvesseltrajectorycompressionasystematicreviewandsoftwaredevelopment AT maohanliang aisbasedvesseltrajectorycompressionasystematicreviewandsoftwaredevelopment |