经典的DP压缩算法在AIS（Automatic Identification System）轨迹压缩时容易损失较多的船舶轨迹运动特征，考虑轨迹航速与航向的压缩算法又普遍较为复杂，为简化压缩流程，保留更多的轨迹运动特征，在Douglas-Peucker算法的基础上，引入轨迹运动特征点筛选步骤，提出一种考虑航速变化的船舶AIS轨迹改进自适应压缩算法，即根据船舶航速和航向的变化值自适应标记航速特征点和航向特征点，将原始轨迹由航向特征点分割再对子轨迹分别进行自适应压缩，最后整合数据得到压缩后的数据。以厦门港—天津港的船舶航行数据进行实验，从压缩率、压缩效果、压缩时间等多个方面对比DP算法、考虑航速的DP算法、自适应压缩算法、考虑航速变化的改进船舶AIS轨迹自适应压缩算法压缩的效果，结果证明该算法在保证效率的同时能够更好地保留轨迹的运动特征。
In traditional compression algorithms for AIS (Automatic Identification System) trajectory data, a significant amount of the vessel's motion characteristics is often lost during compression. Although algorithms that consider both speed and course changes can preserve more trajectory information, they are typically more complex. To simplify the compression process while retaining more motion characteristics, this paper proposes an improved AIS trajectory adaptive compression algorithm for ships considering speed variations based on the Douglas-Peucker (DP) algorithm. The proposed method introduces a step for filtering motion characteristic points, considering speed variations. Specifically, the algorithm adaptively marks speed feature points and heading feature points based on the vessel's speed and course changes, then segments the original trajectory at heading feature points and performs adaptive compression on the sub-trajectories. Finally, the compressed data is obtained by integrating the processed sub-trajectories. An experiment was conducted using vessel navigation data from Xiamen Port to Tianjin Port to compare the performance of four algorithms: the DP algorithm, the DP algorithm considering speed, the ADP algorithm, and the improved AIS trajectory adaptive compression algorithm for ships considering speed variations. The comparison was made in terms of compression rate, compression effect, and compression time. The results demonstrate that the proposed algorithm not only improves compression efficiency but also better preserves the motion characteristics of the vessel's trajectory.
2025,47(15): 151-158 收稿日期：2024-10-28
DOI：10.3404/j.issn.1672-7649.2025.15.025
分类号：U691+.3
基金项目：国家社会科学基金资助项目（24BGL282）
作者简介：初良勇(1973-),男,教授,博士,研究方向为交通运输规划与管理、智慧港口和智能物流
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