Marine traffic control based on route clustering

• Grinyak V.M.

  V. M. Grinyak. Vladivostok State University of Economics and Service Vladivostok. Russia

This paper is about navigation safety of marine traffic at sea areas. In addition to traditional approach of danger situation detection based on vessels approaching, the current paper introduces  another  metrics  de-rived  from  kinematic  parameters  of  the  vessel  itself,  to  identify
whether it follows patterns (rules) of the traffic at a certain sea area. Authors focused their efforts on analyzing existing traffic schemas in order to identify its danger level in general rather than scrutinizing on individual cases. Along  with  the  traditional  approach  of  sea  traffic  schema  identifications,  proposed  original method of automated identification of sea traffic schemes based on clustering of movement
parameters using historical AIS data. The kinematic model with additional clustering of the objects at sea area is used. Clustering is built up on identification of “typical” objects with splitting maritime area into subsets of arias with similar movement patterns. For the clustering decom-
position Mountain clustering and Subtraction clustering algorithms were considered. The model under research is built depending on the heading parameter and is applicable for both unidirectional and bidirectional traffic. The historical AIS data of sea traffic at Tsugaru strait is used for identifying traffic schema with the model designed under presented research. The  proposed  model  shows  correct  identification  of  the  traffic  schema,  accurately  identifies straight-line traffic clustering areas crossing likes traffic clustering areas and active maneuvering
areas.  As a part of the work there are analyses of relevant research with emphasizes on superior differences such as automated identification of vessel movement types and quantitative measure of overall danger for the traffic scheme based on clustering analyses. Study of proposed approach for safety measures on real navigation area proves its potential for future implementation in real applications to provide navigation schema for vessel navigators.
Keywords: navigation safety, route planning, ship track system, clustering, AIS.