.png){kind=icon}
返回
Ship Trajectory Online Compression Algorithm Considering Handling Patterns
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2021.3078642.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Marine vehicles
Trajectory
Artificial intelligence
Compression algorithms
Heuristic algorithms
Turning
Shape
Automatic identification system
handling patterns
ship trajectory
sliding window
trajectory compression
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
分享收藏分享收藏Self-focusing effects of dispositional self-consciousness, mirror presence, and audience presence.性格自我意识、镜像存在和观众存在的自我聚焦效应。
PREAI
分享收藏Production and partial characterization of monoclonal antibodies to Bothrops asper (terciopelo) myotoxin.png)
Toxicon
ToxiconIF0
PREAI
分享收藏
查看更多内容