A method for compressing AIS trajectory data based on the adaptive-threshold Douglas-Peucker algorithm

The deficiencies of massive data like storage difficulty, computation inefficiency, and information redundancy call for ship trajectory compression. While most studies on ship trajectory compression have one or more of the following drawbacks: the drawback of low compression efficiency; the problem...

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Vydáno v:Ocean engineering Ročník 232; s. 109041
Hlavní autoři: Tang, Chunhua, Wang, Han, Zhao, Jiahuan, Tang, Yuanqing, Yan, Huaran, Xiao, Yingjie
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 15.07.2021
Témata:
ADP algorithm
AIS
DP algorithm
Ship trajectory
Trajectory compression
Ship trajectory
AIS
Trajectory compression
DP algorithm
ADP algorithm
ISSN:0029-8018, 1873-5258
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Shrnutí:The deficiencies of massive data like storage difficulty, computation inefficiency, and information redundancy call for ship trajectory compression. While most studies on ship trajectory compression have one or more of the following drawbacks: the drawback of low compression efficiency; the problem resulted from error ship static information when the distance threshold is set based on ship length or width; poor compression quality for some trajectories, which is caused by experience-based optimal threshold. To solve these problems, we propose the ADP (Adaptive-threshold Douglas-Peucker) algorithm based on DP (Douglas-Peucker) algorithm. By determining the key points of each trajectory through the threshold change rate, ADP no longer relies on ship static information and makes it easier to determine the threshold, which is what traditional algorithms cannot achieve. Additionally, we use the advantage of matrix operation and the method of reducing points to improve the algorithm's computation efficiency. To verify the feasibility and superiority of the proposed algorithm, we compared our algorithm with DP algorithm, Partition-DP algorithm and Sliding Window algorithm from four aspects, namely, compression rate, Synchronous Euclidean distance, Length Loss Rate and running time. The experimental results prove that our algorithm has advantages over the other three algorithms, especially in threshold setting. •The proposed algorithm solves the problem resulted by the experience-based threshold.•It solves the problem of poor or even unsuccessful compression due to incorrect ship static information.•We use the matrix operation and the method of reducing points to improve the algorithm's computation efficiency.
ISSN:0029-8018
1873-5258
DOI:10.1016/j.oceaneng.2021.109041