研究基于轨迹数据的船舶交通密度计算方法，利用精准的船舶交通密度计算结果提升海上交通规划水平。利用 AIS 设备采集船舶航行轨迹数据，利用均匀参数化方法对所采集的航行轨迹数据重采样处理。将通过重采样处理获取的航行轨迹数据，划分为静止轨迹数据点以及移动轨迹数据点，依据数据点间的欧式距离，以及船舶航行方向、航行速度的相似性，选取基于密度的 DBSCAN 聚类算法完成轨迹数据聚类。依据船舶航行轨迹数据聚类结果，选取多维密度方法，通过更新船舶经过总数、船舶经过总时间等参数，计算船舶交通密度。实验结果表明，该方法可以依据船舶航行轨迹数据，精准计算船舶交通密度，为海上交通规划提供有效支撑。
The ship traffic density calculation method of trajectory data is studied, and the accurate ship traffic density calculation results are used to improve the level of maritime traffic planning. AIS equipment is used to collect ship trajectory data, and uniform parametric method is used to resampling the collected ship trajectory data. The ship trajectory data obtained through resamping were divided into static trajectory data points and moving trajectory data points. According to the Euclidean-style distance between data points, as well as the similarity of ship sailing direction and sailing speed, density-based DBSCAN clustering algorithm was selected to complete the trajectory data clustering. Based on the clustering results of ship trajectory data, the multi-dimensional density method is selected to calculate ship traffic density by updating parameters such as the total number of ship passes and the total time of ship passes. Experimental results show that the proposed method can accurately calculate ship traffic density based on ship trajectory data, and provide an effective basis for marine traffic planning.
2023,45(3): 149-152 收稿日期：2022-09-01
DOI：10.3404/j.issn.1672-7649.2023.03.028
分类号：TP391
基金项目：河南省科学技术厅项目（[2014]第1069号）
作者简介：孙豫(1984-),女,讲师,主要从事数学应用研究
