基于AIS数据的水域航路网络提取方法  

Extraction of ship track pattern from AIS data

作　　者：牟军敏[1] 郭绍卿 张志江 陈鹏飞[1] 陈琳瑛[1] MOU Junmin;GGUO Shaoqing;ZZHANG Zhijiang;CHEN Pengfei;CHEN Linying(School of Navigation,Wuhan University of Technology,Wuhan 430070,China;Ningbo Aids to Navigation Department of Donghai Navigation Safety Administration,Ningbo 315000,China)

机构地区：[1]武汉理工大学航运学院,湖北武汉430070 [2]交通运输部东海航海保障中心宁波航标处,浙江宁波315000

出　　处：《中国航海》2023年第2期152-160,共9页Navigation of China

基　　金：国家自然科学基金资助项目(5210140252001242)。

摘　　要：随着航运业的蓬勃发展,港口间交通愈发拥挤,不仅为船舶的航行安全带来挑战,也为港航部门监管带来巨大压力。为了助力港航部门掌握船舶交通网络演化趋势,提升船舶交通精细化管理水平,基于船舶自动识别系统数据提出一种水域航路网络提取方法。通过该方法挖掘水域中的船舶航行特征,识别特征节点并进行轨迹划分;利用频繁轨迹模式识别构造水域航路网络拓扑,并采用垂线分治法确定航路范围。基于宁波-舟山港的数据开展实证研究,结果表明:所提取的航路网络结果与水域航路分布现状高度吻合,能帮助港航部门及时发现已形成的习惯航路,还能用来进行航路规划,充分验证了方法的准确性、有效性和实用性。A method of extracting ship track pattern from AIS data is developed to help the port authority to master the actual ship distribution in a water area,in turn,the evolution of traffic flow pattern.The method mines the sailing characteristics of ships and groups the tracks belong to the same ship through feature node examination.The traffic pattern in the water area is generated based on the distribution of frequent tracks.The topology of the traffic pattern is extracted.The width of each traffic flow is determined by using vertical divide-and-conquer approach.The AIS data from Ningbo-Zhoushan water area is used for verification of the method and it is proved that the extracted traffic flow pattern perfectly reflected the actual traffic flow.

关 键 词：航路网络 船舶自动识别系统 数据驱动 轨迹特征 

分 类 号：U692.31[交通运输工程—港口、海岸及近海工程]