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A novel regional collision risk assessment method considering aggregation density under multi-ship encounter situations

Published online by Cambridge University Press:  19 November 2021

Rong Zhen Open the ORCID record for Rong Zhen [Opens in a new window] ,
Ziqiang Shi ,
Zheping Shao  and
Jialun Liu
Rong Zhen
Affiliation:
Navigation College, Jimei University, Xiamen, China. Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China
Ziqiang Shi
Affiliation:
Navigation College, Jimei University, Xiamen, China.
Zheping Shao
Affiliation:
Navigation College, Jimei University, Xiamen, China.
Jialun Liu*
Affiliation:
Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China National Engineering Research Center for Water Transportation Safety, Wuhan, China
*
*Corresponding author. E-mail: [email protected]
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Abstract

The regional ship collision risk assessment for multiple ships in restricted waters is of great significance to the early warning of ship collision risk and the intelligent supervision of maritime traffic. Given the existed method of regional ship collision risk assessment without considering the impact of ship aggregation density, this paper proposes a novel regional ship collision risk assessment method that considers the aggregation density (AD) of the clusters of encounter ships (CES) for intelligent surveillance and navigation. The effectiveness of the proposed method has been examined by the experimental case study in the waters of Xiamen, China, and analysis has been compared with other existed studies to show the advantages of the new proposed algorithm. The results show that the study method can more intuitively and effectively quantify the temporal and spatial distribution of regional collision risks in the restricted sea area. The proposed method can improve the efficiency of traffic management when monitoring the ship collision risks in macroscopic view, and assist the safety of manned and unmanned ship navigation.

Keywords

ship collision riskship aggregation densityclusters of encounter shipsmaritime surveillance
Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 1 , January 2022 , pp. 76 - 94
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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