桥区水域船舶行为识别与可视化应用研究

项目名称： 桥区水域船舶行为识别与可视化应用研究

项目编号： No.51479155

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 其他

项目作者： 初秀民

作者单位： 武汉理工大学

项目金额： 83万元

中文摘要： 项目以桥区水域水上交通大数据为基础、以可视分析为手段，针对桥区水域船舶航行安全风险大、安全监管压力大、海事人员工作繁重亟需提升安全监管的科学化与智能化的现状，开展船舶行为模式识别、桥区水域船舶航行安全风险分析以及可视化呈现等海事安全科学基础问题的研究。首先提出桥区水域船舶行为数据精确性、一致性、完整性、同一性、时效性的质量保障方法，建立基于概率密度估计的船舶行为时空模型。其次提出基于距离函数船舶行为聚类算法，设计船舶异常行为模式非线性分类器，建立桥区水域船舶行为预测模型和航行安全风险分析模型。最后，提出船舶行为可视化呈现与人机交互方法，设计船舶行为可视化处理系统框架，构建不同地区桥区水域安全监管可视分析实证平台，验证研究方法的有效性。 通过上述研究，提出基于大数据的船舶行为可视分析的基础理论，解决桥区水域船舶通航安全风险防控关键技术，保障桥区水域通航安全，服务智慧海事的发展。

中文关键词： 大数据；可视化分析；船舶行为识别；交通安全；桥区水域

英文摘要： This project researchs basic maritime safty science about vessel behavior recognition,risk analysis of navigation and traffic information visulization in the bridge waterway,based on maritime traffic big data in the bridge waterway and visual techniqes for alleviating vessel navigation risk,safety supervising pressure and maritime official's heavy workload and improving scientific and intelligent satety supervision.Firstly, a method is present to improve accuracy, consistency, integrity, identity and timeliness of vessel behavior data in the bridge waterway and temporal-spatial models of vessel behavior are built based on probability density estimation. Secondly, this project also presents clustering algorithm of vessel behavior based on distance functions and structures prediction model of vessel behavior and risk analysis model of navigation safety. Finally, methods of visual presenting and human-computer interaction for vessel behavior visualization are introduced; the system framework of visualizing vessel behavior is designed; and the visual experiment platform of safety supervision for different bridge waterway is constructed to validate the research methods. The above researchs present the basic theory of vessel behavior visualization; solve the key technology of vessel navigation safety risk control; ensure navigation safety in the bridge waterway and promote the development of intelligence maritime.

英文关键词： big data;visual analytics;vessel behavior Recognication;traffic safety;bridge waterway