4.7 Article

A ship domain-based model of collision risk for near-miss detection and Collision Alert Systems

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ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2021.107766

关键词

Near-miss; Ship collision risk; Collision Alert System, Ship collision avoidance; Ship domain

资金

  1. Gdynia Maritime University, Faculty of Navigation [WN/PZ/2021/02]

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The paper introduces a new model of ship collision risk, which utilizes the concept of ship domain and related domain-based collision risk parameters to describe ship encounters. The model is based on five variables representing encounters, with values that can be directly computed based on positions, courses, and speeds of the vessels. The model can be applied to near-miss detection, Collision Alert Systems, and collision avoidance decision support systems.
The paper presents a new model of ship collision risk, which utilises a ship domain concept and the related domain-based collision risk parameters. An encounter is here described by five variables representing: degree of domain violation (DDV), relative speed of the two vessels, combination of the vessels' courses, arena violations and encounter complexity. As for the first three variables, their values can be directly computed based on positions, courses and speeds of two vessels. The last two variables require decomposing a close quarters situation into phases. For this purpose the method utilizes a number of auxiliary parameters derived from the concept of ship domain: time of domain violation (TDV), time of domain exit (TDE), timespan of close quarters situation and vessels' proximity, which is quantified based on the ship arena. The formulas and algorithms for determining all variables' values are provided in detail. Once all the values are computed, the final collision risk assessment is made. Possible applications of the presented model include: AIS-based near-miss detection, Collision Alert Systems (CAS) and collision avoidance decision support systems (DSS). Case studies for those applications are provided, including examples of encounter classification and quantification of collision risk.

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