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 Son; Dong-Ham Kim; Sang-Woong Yun; Hye-Jin Kim; Sewon 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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