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Comparison of master’s route selection criteria of vehicle carriers in North Pacific and North Atlantic using satellite AIS and Ocean wave data

Fujii M., Hashimoto H., Taniguchi Y.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2020

Vol. 14, no. 1

137--141

The operational measures in which a ship needs to avoid specified areas to escape ship stability failures were discussed at the International Maritime Organization as a part of the second generation intact stability criteria. It is necessary that the rationality and practicality of the operational measures are carefully investigated. In this study, master’s route decision-making criteria of trans-ocean vehicle carriers have been clarified by comparing the Pacific and the Atlantic data, derived from Satellite AIS and ocean wave data. Features of voyage routes of each ocean were discussed, followed by analysis of the encountered wave direction and height during a voyage. The master’s route selection criteria were defined by comparing the probability densities of the wave heights that occurred in the navigable area and that of the actual encountered waves. The navigation hours in a stormy area were also studied.

An estimation method of message receiving probability for a satellite automatic identification system using a binomial distribution model

Seta T., Matsukura H., Aratani T., Tamura K.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

2016

nr 46 (118)

101--107

Automatic identification system (AIS) data are used to analyze vessels’ positions or maritime traffic. Recently, satellites are being adopted for gathering AIS data (satellite AIS). A satellite AIS can gather AIS data from all over the world, including the center of the ocean. However, because a satellite moves around the world every day, there is a very short window of time that the satellite can receive signals from some specific area. Furthermore, because a satellite AIS receives signals simultaneously from a wider area than a terrestrial AIS does, the satellite AIS has lower rate of signal reception, especially near vessel congested areas. This may cause many unrecognized vessels. For this situation, this paper proposes a new method to estimate the number of unrecognized vessels based on a binomial distribution model. With this method, we are able to estimate the number of unrecognized vessels just from satellite AIS data themselves.