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Macroscopic collision risk model based on near miss

Published online by Cambridge University Press:  01 April 2021

Yangyu Zhou
Affiliation:
Navigation College, Dalian Maritime University, Dalian, China. The Key Labouratory of Navigation Safety Guarantee, Liaoning Province, Dalian, China.
Jiaxuan Yang*
Affiliation:
Navigation College, Dalian Maritime University, Dalian, China. The Key Labouratory of Navigation Safety Guarantee, Liaoning Province, Dalian, China.
Xingpei Bian
Affiliation:
Navigation College, Dalian Maritime University, Dalian, China. The Key Labouratory of Navigation Safety Guarantee, Liaoning Province, Dalian, China.
Lingqi Ma
Affiliation:
Navigation College, Dalian Maritime University, Dalian, China. The Key Labouratory of Navigation Safety Guarantee, Liaoning Province, Dalian, China.
Zhen Kang
Affiliation:
School of Marine Science and Technology, Tianjin University, Tianjin, China
*
*Corresponding author. E-mail: yangjiaxuan@dlmu.edu.cn

Abstract

Using near miss data detected from non-accident information to analyse marine traffic risk can alleviate some of the limitations of accident-based methods. A model based on an arena for detecting scenes of near miss is proposed to detect comprehensively those ship encounters with potential collision risk. To eliminate the influence of data sampling frequency on the detection of scenes of near miss, a single near miss is defined as the whole progress of traffic state from the time the target ship sails into the arena of the subject ship to the time it leaves the arena of the subject ship. To research the geographical distribution characteristics of marine traffic risk, first, a statistical model for the scenes of near miss based on the water grid method is proposed, and then a macroscopic collision risk model based on near miss is developed. The geographical distribution characteristics of marine traffic risk in the Bohai Sea are analysed, and the water areas of high marine traffic risk are obtained. The findings can provide theoretical support for marine safety management.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2021

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