Collision risk assessment for ships’ routeing waters: An information entropy approach with Automatic Identification System (AIS) data
The ship's routing was adopted to organise marine traffic flow and reduce the risk of collision between ships in crowded waters. With the expansion of the world's fleet, ship traffic in shipping bottleneck and chokepoint areas became more and more busy and complex creating serious challeng...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/380402 |
| Acceso en línea: | https://hdl.handle.net/2117/380402 https://dx.doi.org/10.1016/j.ocecoaman.2022.106184 |
| Access Level: | acceso abierto |
| Palabra clave: | Nautical instruments Automatic identification system (AIS) Ship collision risk assessment Information entropy K-means clustering Ningbo-zhoushan port Navegació--Aparells i instruments Navegació--Accidents Àrees temàtiques de la UPC::Nàutica::Navegació marítima::Instrumentació i equipament per a la navegació Àrees temàtiques de la UPC::Nàutica::Seguretat marítima::Accidents marítims |
| Sumario: | The ship's routing was adopted to organise marine traffic flow and reduce the risk of collision between ships in crowded waters. With the expansion of the world's fleet, ship traffic in shipping bottleneck and chokepoint areas became more and more busy and complex creating serious challenges for navigational safety. Therefore, quantitative collision risk assessment is significantly important for the ships' routeing waters. In this paper, the information entropy method which integrates the K-means clustering based on Automatic Identification System (AIS) data is introduced to quantitatively evaluate the collision risks in the ships' routeing waters. As a case study, the information entropy of Courses Over Ground (COG) for Ningbo-Zhoushan Port (the largest port in the world since 2009) is calculated by using historical AIS data. Then the K-means clustering is used to group the bytes of information entropy of the different legs in the shipping route. We find that in Ningbo-Zhoushan port Precautionary Area (PA) 2, 4 and 7 are the highest risk legs; PA 1, 5 and 6, Traffic Separation Scheme (TSS) 16, and 17 are medium-high risk areas. Therefore, ship collision risk prevention measures should be prioritised in those legs. Our contributions provide a novel approach to quantitatively assess ship collision risks in busy waters. |
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