한국항해항만학회지 (Journal of Navigation and Port Research)

  • 제48권5호
  • /
  • Pages.368-375
  • /
  • 2024
  • /
  • 1598-5725(pISSN)
  • /
  • 2093-8470(eISSN)
한국항해항만학회 (Korean Institute of Navigation and Port Research)
권호 표지
DOI QR코드

DOI QR Code

A Study of Development a Big Data-based CS Model for Maritime Traffic Assessment

  • Eui-Jong Lee (SafeTechResearch,) ;
  • Hyun-suk Kim (SafeTechResearch,) ;
  • Seung-yeon Kim (Division of Navigation Science, Mokpo National Maritime University) ;
  • Young-Joong Ahn (Division of Navigation Convergence Studies, Korea Maritime and Ocean University) ;
  • Yun-sok Lee (Division of Coast Guard Studies, Korea Maritime and Ocean University)
  • 투고 : 2024.10.14
  • 심사 : 2024.10.25
  • 발행 : 2024.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This research develops a big data-based CS model for maritime traffic assessment, motivated by global shipping growth, the impact of COVID-19, changes in consumer culture, and Industry 4.0 expansion in maritime sectors. Maritime traffic, crucial for global trade, demands effective management for safety and efficiency. This study aims to quantitatively and objectively evaluate maritime traffic smoothness by analyzing ship operation data. The CS model focuses on unique maritime characteristics, leveraging big data to enhance traffic management solutions and safety. The research methodology includes analyzing domestic and international trends and data to reflect maritime spatiality and continuity. The model's efficacy is tested through case studies on major port routes, comparing it with existing models to suggest improvements. This new approach provides a framework for optimizing maritime traffic routes and supports autonomous, unmanned, and smart ship operations, setting a new paradigm for maritime traffic management.

키워드

과제정보

This research was supported by the "2024 Research Project on the Safety Assessment of Ship Routes" from the Ministry of Oceans and Fisheries.

참고문헌

  1. BIMCO(2023), Container Shipping Market Overview & Outlook Q4 2023.
  2. Clarkson PLC(2023), 2023 Annual Report.
  3. Do, C. U.(2017), Transportation Engineering.
  4. Gazis, Denos C.(2006), Traffic Theory, Springer Science & Business Media, Vol. 50.
  5. Grech, Michelle, T. Horberry, and T. Koester(2008), Human Factors in the Maritime Domain, CRC Press.
  6. Kim, J. K., Ahn, Y. J., Kim, S. W. and Lee, Y. S.(2016), "A Normal Distribution Test of Passing Main Fairway for Dangerous Goods Tanker on Busan Port", The Korean Society of Marine Environment & Safety, Vol. 11.
  7. Lee, E. J.(2024), "A Study of Development a Big Data-based CS Model for Maritime Traffic Assessment", Korea Maritime and Ocean University, Department of Coast Guards Studies Graduate School, PhD Dissertation.
  8. Lee, E. J., Kim, H. S., Lee, E. K., Kim, K. S., Yu, Y. U. and Lee, Y. S.(2023), "Improving the Maritime Traffic Evaluation with the Course and Speed Model", Applied Sciences, Vol. 13, No. 23, p. 12955.
  9. Ministry of Land, Transport and Maritime Affairs and Korea Institute of Marine Science and Technology Promotion(2009), Planning Research for the Development of Maritime Traffic Safety Evaluation Model and Integrated Risk Assessment and Analysis Technology for Coastal Waters.
  10. Ministry of Oceans and Fisheries(2024), Maritime Traffic Safety Act, Enforcement Decree of the Maritime Traffic Safety Act, Enforcement Rules of the Maritime Traffic Safety Act, Guidelines for Implementing Maritime Traffic Safety Diagnostics.
  11. Mitsui & Co(2019), Maritime Autonomous Surface Ships: Development Trends and Prospects.
  12. Freightwaves, "Tidal Wave of New Container Ships: 2023-24 Deliveries to Break Record", https://www.freightwaves.com/news/tidal-wave-of-new-container-ships-2023-24-deliveries-to-break-record.
  13. United Nations Conference on Trade and Development (2023), Review of Maritime Transport 2023, Geneva, Switzerland.