A ship optimal route automatic generation method based on AIS big data

Abstract

A ship optimal route automatic generation method based on AIS big data belongs to the technical field of big data mining, can solve the problem that an existing method cannot be applied to actual ship route planning and the like, and comprises the following steps: firstly, preprocessing massive historical AIS data, then introducing ship static data; adding ship draft in distance measurement to perform similarity measurement on AIS data; then using an improved adaptive clustering algorithm to perform clustering on ship track clusters until subclass clusters are single; and finally, using a main navigation route extraction method to extract a main navigation route from the clustered subclass clusters to realize automatic generation of an optimal ship route. The ship motion track is analyzed and processed based on historical AIS big data, the thought of referring to the specific navigation experience of other ships during ship route design is met, the new route planning method is provided, the main navigation route can be accurately extracted, and ship route planning can be provided for ships with different characteristics.

Description

technical field [0001] The invention belongs to the technical field of big data mining, and in particular relates to a method for automatically generating an optimal shipping route based on AIS big data. Background technique [0002] With the rapid development of science and technology, the proposal and promotion of the national strategy of the 21st Century Maritime Silk Road, and the prosperity of import and export trade at sea, how to plan routes to reduce transportation costs and improve navigation safety is an important research direction. Common path planning methods include A* (A-Star) algorithm, D* (Dijkstra) algorithm, probabilistic road map (Probabilistic Road Map, PRM) and some corresponding improved algorithms; ant colony algorithm, genetic algorithm, particle swarm optimization algorithm and other intelligent optimization algorithms. However, the current route planning research ignores the route design and navigation rules that actually need to be followed in na...

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Problems solved by technology

[0003] However, the above methods have defects to varying degrees, which makes the above methods unable to be applied to the actual ship route planning.

Although the above methods have achieved certain results in terms of search efficiency and path smoothing by improving the environment construction method and search algorithm, the fineness of the path planning by this type of algorithm depends heavily on the fineness of the environment model. When the fineness of the planning path is too high When the environment search space increases, the computational consumption increases exponentially

On the other hand, it is difficult for these methods to introduce expert experience, and the path out of the planned path often requires further correction by navigation experts before it can be used in actual navigation

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