Towards a Model of Regional Vessel Near-miss Collision Risk Assessment for Open Waters based on AIS Data

The absence of a regional, open water vessel collision risk assessment system endangers maritime traffic and hampers safety management. Most recent studies have analysed the risk of collision for a pair of vessels and propose micro-level risk models. This study proposes a new method that combines de...

Full description

Saved in:
Bibliographic Details
Published inJournal of navigation Vol. 72; no. 6; pp. 1449 - 1468
Main Authors Zhang, Weibin, Feng, Xinyu, Qi, Yong, Shu, Feng, Zhang, Yijin, Wang, Yinhai
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.11.2019
Subjects
Clustering
Collision dynamics
Kinematics
Mathematical models
R&D
Regional analysis
Research & development
Risk analysis
Risk assessment
Safety management
Safety measures
Sea vessels
Studies
Traffic
Traffic management
Traffic safety
Water area
Gulf of Finland
Baltic Sea
Density complexity
AIS data
Multi-vessel collision risk
Maritime traffic safety
Regional risk assessment
Online AccessGet full text

Cover

More Information
Summary:The absence of a regional, open water vessel collision risk assessment system endangers maritime traffic and hampers safety management. Most recent studies have analysed the risk of collision for a pair of vessels and propose micro-level risk models. This study proposes a new method that combines density complexity and a multi-vessel collision risk operator for assessing regional vessel collision risk. This regional model considers spatial and temporal features of vessel trajectory in an open water area and assesses multi-vessel near-miss collision risk through danger probabilities and possible consequences of collision risks via four types of possible relative striking positions. Finally, the clustering method of multi-vessel encountering risk, based on the proposed model, is used to identify high-risk collision areas, which allow reliable and accurate analysis to aid implementation of safety measures.
ISSN:0373-4633
1469-7785
DOI:10.1017/S037346331900033X