上海交通大学学报

上海交通大学学报 >

2017 , Vol. 51 >Issue 7: 840 - 845

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2017.07.011

兵器工业

 桥区船舶交通流可视分析系统

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  •  1. 武汉理工大学 智能交通系统研究中心， 武汉 430063； 2. 国家水运安全工程技术研究中心，
     武汉 430063； 3. 武汉理工大学  能源与动力工程学院， 武汉 430063；
    4. 闽江学院 经济与管理学院， 福州 350108

网络出版日期: 2017-07-31

基金资助

 

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 Visual Analytic System of Vessel Traffic in Bridge Waterway

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  •  1. Intelligent Transport System Research Center, Wuhan University of Technology,
     Wuhan 430063, China; 2. National Engineering Research Center for Water Transport Safety,
     Wuhan 430063, China; 3. School of Energy and Power Engineering, Wuhan University of
     Technology, Wuhan 430063, China; 4. School of Economics and Management,
    Minjiang University, Fuzhou 350108, China

Online published: 2017-07-31

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摘要

 以武汉长江大桥桥区水域为研究对象，针对数据分析能力不足而造成海量AIS(Automatic Identification System)数据不仅无法更好地助力水上交通安全，反而为监管决策带来困扰的现状，研究了多维AIS数据的可视化表达和人机交互方法.提出了以电子航道图为载体的内河船舶交通状态平行坐标图模型，并针对传统网格划分法的不足，采用高斯密度函数为核函数利用二维核密度估计法生成热力图模型.在此基础上研发了船舶交通可视化系统，通过3组实例证明该系统有助于桥区船舶数据的异常分析和船舶行为模式识别，为海事管理人员提供有效的决策依据.

关键词：  ; 桥区船舶交通; 可视分析; 自动识别系统可视化; 水路运输

本文引用格式

雷进宇1,2,3，初秀民1,2，何伟4，周映萍1,2 .  桥区船舶交通流可视分析系统[J]. 上海交通大学学报, 2017 , 51(7) : 840 -845 . DOI: 10.16183/j.cnki.jsjtu.2017.07.011

Abstract

 Current practice shows that working with bridge waterway automatic identification system (AIS) data often does not lead to insight but rather confusion because large data volume without further being processed is hard to understand. In order to deal with this issue, bridge waterway of Wuhan section in Yangtze River was selected as research area for the study of AIS visualization model and humancomputer interaction method. Additionally, two dimensional kernel density estimation approach was adopted in the heatmap generation to overcome the defects of traditional grid method. Furthermore, based on electric navigation charts, a visual analytics system was built. Finally, three instances were illustrated and results demonstrated that it is conductive to the users in maritime department to make decisions depending on the knowledge they discovered from the visual analytics system.

Key words：  
vessel traffic in bridge waterway; visual analytics; automatic identification system (AIS) visualization; waterway transportation

参考文献

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