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Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel

Although the International Regulations for Preventing Collision at Sea (COLREGs) provide guidelines for determining the encounter relations between vessels and assessing collision risk, most collision accidents occur in crossing situations. Accordingly, prior studies have investigated methods to ide...

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Autores principales: Namgung, Ho, Ohn, Sung-Wook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269705/
https://www.ncbi.nlm.nih.gov/pubmed/35808477
http://dx.doi.org/10.3390/s22134983
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author Namgung, Ho
Ohn, Sung-Wook
author_facet Namgung, Ho
Ohn, Sung-Wook
author_sort Namgung, Ho
collection PubMed
description Although the International Regulations for Preventing Collision at Sea (COLREGs) provide guidelines for determining the encounter relations between vessels and assessing collision risk, most collision accidents occur in crossing situations. Accordingly, prior studies have investigated methods to identify the relation between the give-way and stand-on vessels in crossing situations to allow the stand-on vessel to make the optimal collision-avoidance decision. However, these studies were hindered by several limitations. For example, the collision risk at the current time (t) was evaluated as an input variable obtained at the current time (t), and collision-avoidance decisions were made based on the evaluated collision risk. To address these limitations, a collision risk prediction system was developed for stand-on vessels using a fuzzy inference system based on near-collision (FIS-NC) and a sequence model to facilitate quicker collision avoidance decision making. This was achieved by predicting the future time point (t + i) collision risk index (CRI) of the stand-on vessel at the current time point (t) when the own-ship is determined to be the stand-on vessel in different encounter relations. According to the performance verification results, navigators who use the developed system to predict the CRI are expected to avoid collisions with greater clearance distance and time.
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spelling pubmed-92697052022-07-09 Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel Namgung, Ho Ohn, Sung-Wook Sensors (Basel) Article Although the International Regulations for Preventing Collision at Sea (COLREGs) provide guidelines for determining the encounter relations between vessels and assessing collision risk, most collision accidents occur in crossing situations. Accordingly, prior studies have investigated methods to identify the relation between the give-way and stand-on vessels in crossing situations to allow the stand-on vessel to make the optimal collision-avoidance decision. However, these studies were hindered by several limitations. For example, the collision risk at the current time (t) was evaluated as an input variable obtained at the current time (t), and collision-avoidance decisions were made based on the evaluated collision risk. To address these limitations, a collision risk prediction system was developed for stand-on vessels using a fuzzy inference system based on near-collision (FIS-NC) and a sequence model to facilitate quicker collision avoidance decision making. This was achieved by predicting the future time point (t + i) collision risk index (CRI) of the stand-on vessel at the current time point (t) when the own-ship is determined to be the stand-on vessel in different encounter relations. According to the performance verification results, navigators who use the developed system to predict the CRI are expected to avoid collisions with greater clearance distance and time. MDPI 2022-07-01 /pmc/articles/PMC9269705/ /pubmed/35808477 http://dx.doi.org/10.3390/s22134983 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Namgung, Ho
Ohn, Sung-Wook
Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel
title Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel
title_full Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel
title_fullStr Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel
title_full_unstemmed Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel
title_short Fuzzy Inference and Sequence Model-Based Collision Risk Prediction System for Stand-On Vessel
title_sort fuzzy inference and sequence model-based collision risk prediction system for stand-on vessel
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269705/
https://www.ncbi.nlm.nih.gov/pubmed/35808477
http://dx.doi.org/10.3390/s22134983
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