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The Development of Regional Vessel Traffic Congestion Forecasts Using Hybrid Data from an Automatic Identification System and a Port Management Information Systemopen accessAIS 정보와 Port MIS 정보를 활용한 특정해역 선박 교통 혼잡도 개발

Other Titles
AIS 정보와 Port MIS 정보를 활용한 특정해역 선박 교통 혼잡도 개발
Authors
Joonbae SonDong-Ham KimSang-Woong YunHye-Jin KimSewon Kim
Issue Date
12월-2022
Publisher
MDPI AG
Keywords
autonomous vessel; port arrival and departure; port MIS (port management information system); ship AIS (automatic identification system); vessel congestion forecast; vessel traffic congestion
Citation
Journal of Marine Science and Engineering , v.10, no.20
Journal Title
Journal of Marine Science and Engineering
Volume
10
Number
20
URI
https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/9476
DOI
10.3390/jmse10121956
ISSN
2077-1312
2077-1312
Abstract
The present study proposes a new method that forecasts congestion in the area near a port by combining the automatic identification systems of ships and port management information data. The proposed method achieves 85% accuracy for one-day-long ship congestion forecasts. This accuracy level is high enough to act as a reference value for both manned and unmanned operation situations for autonomous vessels in port areas. The proposed forecast algorithm achieves 95% accuracy when used for a one-hour ship congestion forecast. However, the accuracy of the algorithm is degraded to almost half when the automatic identification system or the port management system is used independently. ? 2022 by the authors.
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