Improving the Maritime Traffic Evaluation with the Course and Speed Model

Recent projections from marine transportation experts highlight an uptick in maritime traffic, attributed to the fourth industrial revolution’s technological strides and global economic rebound. This trend underscores the need for enhanced systems for maritime accident prediction and traffic managem...

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Main Authors: Eui-Jong Lee, Hyun-Suk Kim, Eunkyu Lee, Kyungsup Kim, Yongung Yu, Yun-Sok Lee
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/13/23/12955
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author Eui-Jong Lee
Hyun-Suk Kim
Eunkyu Lee
Kyungsup Kim
Yongung Yu
Yun-Sok Lee
author_facet Eui-Jong Lee
Hyun-Suk Kim
Eunkyu Lee
Kyungsup Kim
Yongung Yu
Yun-Sok Lee
author_sort Eui-Jong Lee
collection DOAJ
description Recent projections from marine transportation experts highlight an uptick in maritime traffic, attributed to the fourth industrial revolution’s technological strides and global economic rebound. This trend underscores the need for enhanced systems for maritime accident prediction and traffic management. In this study, to analyze the flow of maritime traffic macroscopically, spatiality and continuity reflecting the output of ships are considered. The course–speed (CS) model used in this study involved analyzing COG, ROT, speed, and acceleration, which can be obtained from the ship’s AIS data, and calculating the deviation from the standard plan. In addition, spatiality and continuity were quantitatively analyzed to evaluate the smoothness of maritime traffic flow. A notable finding is that, in the target sea area, the outbound and inbound CS indices are measured at 0.7613 and 0.7501, suggesting that the outbound ship flows are more affected than inbound ship flows to the liquidity of maritime traffic flow. Using the CS model, a detailed quantitative evaluation of the spatiality and continuity of maritime traffic is presented. This approach facilitates robust comparisons over diverse scales and periods. Moreover, the research advances our understanding of factors dictating maritime traffic flow based on ship attributes. The study insights can catalyze the development of a novel index for maritime traffic management, enhancing safety and efficiency.
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spelling doaj.art-cd906842ca0e43a0a2936be01c88c7f82023-12-08T15:12:17ZengMDPI AGApplied Sciences2076-34172023-12-0113231295510.3390/app132312955Improving the Maritime Traffic Evaluation with the Course and Speed ModelEui-Jong Lee0Hyun-Suk Kim1Eunkyu Lee2Kyungsup Kim3Yongung Yu4Yun-Sok Lee5SafeTechResearch, Deajeon 34050, Republic of KoreaSafeTechResearch, Deajeon 34050, Republic of KoreaAutonomous Ship Research Center, Samsung Heavy Industries, Daejeon 34051, Republic of KoreaDepartment of Computer Engineering, Chungnam National University, Daejeon 34134, Republic of KoreaDepartment of Coast Guards Studies, Korea Maritime & Ocean University, Busan 49112, Republic of KoreaDepartment of Coast Guards Studies, Korea Maritime & Ocean University, Busan 49112, Republic of KoreaRecent projections from marine transportation experts highlight an uptick in maritime traffic, attributed to the fourth industrial revolution’s technological strides and global economic rebound. This trend underscores the need for enhanced systems for maritime accident prediction and traffic management. In this study, to analyze the flow of maritime traffic macroscopically, spatiality and continuity reflecting the output of ships are considered. The course–speed (CS) model used in this study involved analyzing COG, ROT, speed, and acceleration, which can be obtained from the ship’s AIS data, and calculating the deviation from the standard plan. In addition, spatiality and continuity were quantitatively analyzed to evaluate the smoothness of maritime traffic flow. A notable finding is that, in the target sea area, the outbound and inbound CS indices are measured at 0.7613 and 0.7501, suggesting that the outbound ship flows are more affected than inbound ship flows to the liquidity of maritime traffic flow. Using the CS model, a detailed quantitative evaluation of the spatiality and continuity of maritime traffic is presented. This approach facilitates robust comparisons over diverse scales and periods. Moreover, the research advances our understanding of factors dictating maritime traffic flow based on ship attributes. The study insights can catalyze the development of a novel index for maritime traffic management, enhancing safety and efficiency.https://www.mdpi.com/2076-3417/13/23/12955spatialitycontinuityCS modelmaritime traffic flow
spellingShingle Eui-Jong Lee
Hyun-Suk Kim
Eunkyu Lee
Kyungsup Kim
Yongung Yu
Yun-Sok Lee
Improving the Maritime Traffic Evaluation with the Course and Speed Model
Applied Sciences
spatiality
continuity
CS model
maritime traffic flow
title Improving the Maritime Traffic Evaluation with the Course and Speed Model
title_full Improving the Maritime Traffic Evaluation with the Course and Speed Model
title_fullStr Improving the Maritime Traffic Evaluation with the Course and Speed Model
title_full_unstemmed Improving the Maritime Traffic Evaluation with the Course and Speed Model
title_short Improving the Maritime Traffic Evaluation with the Course and Speed Model
title_sort improving the maritime traffic evaluation with the course and speed model
topic spatiality
continuity
CS model
maritime traffic flow
url https://www.mdpi.com/2076-3417/13/23/12955
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