关键词: 船舶自动识别系统, 船舶轨迹, 海运网络, 复杂网络, 运输模式, 拓扑结构, 演化机制

Abstract:

With the rapid development of economic globalization, the scale of international trade has continued to be expanded. Global maritime network are attracting much attention from researchers in multidisciplinary areas, such as ocean transportation, geographical information science, mathematical physics, statistics science, complex network science, big data science, computer science and so on. The maritime network studies become hot research topics among them, which plays an important role in designing affective and sustainable macro strategies and policies for countries. This paper summarizes the data sources, theoretical models and research methods in maritime network studies, for example, the used data includes the statistics data and Automatic Identification System （AIS） traced vessel trajectory data, the used methods are from mathematics, physics and statistical theory methods, complex network science, data mining theory, etc. Then, this paper reviewed the research works of maritime network from the perspectives of maritime network transportation mode, network structure characteristics, and evolution mechanism of maritime network, and concluded the existing problems in these perspectives. Previous studies on maritime transportation mode design and optimization are useful to improve shipping service quality, assess the feasibility of new routes and improve the efficiency and capacity of the transportation system. The researches for maritime network structure reveal the static （i.e. network connectivity, clustering coefficient, mean shortest path lengths, closeness centrality, betweeness centrality, and straightness centrality） and dynamic characteristics （i.e. spatial-temporal changes, hierarchical characteristics, dynamic connectivity） through the approaches of modelling, statistical and empirical analyzing. The studies on evolution mechanism for maritime network focus on the structure evolution and traffic flow evolution, which are helpful to identify the influential factors and to predict traffic flow in the maritime network. The future promising research avenues on maritime network include involving experts from multidisciplinary areas, using the research methods from cross-domains, integrating multi-source heterogeneous data, and linking the theoretical analysis with practical application problems.

Key words: automatic identification system, vessel trajectory, maritime network, complex network, transportation mode, topological structure, evolution mechanism