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Comparative risk analysis of autonomous systems implementation in A2-B0 and A3-B1 ships

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EN
Abstrakty
EN
This article concerns the development of autonomous ship technology in maritime navigation, which entails safety and risk management challenges. This study aims to compare the risk analyses of two levels of autonomy of seagoing ships – A3-B1 (ships with limited crew) and A2-B0 (ships fully unmanned) – based on the results of a project named SAFEMASS developed by DNV GL company for the European Maritime Safety Agency. In addition, identifying new, emerging risks relating to the functioning of MASS is another research goal. The article uses hazard identification methods (HAZID) and fault tree analysis (FTA). In the case of A3-B1 vessels, the main threats result from reduced situational awareness of operators and dependence on automatic systems. In the A2-B0 model, the most significant risks are communication system failures and a lack of physical supervision of processes. The research results indicate the need to implement additional risk control measures, such as system optimization and improvement of human-machine interfaces (HMI). It is suggested that autonomous and low-emission technologies will develop conceptually in the coming years. Still, the widespread implementation of these technologies will take a long time due to the complexity of the processes and high operating costs. This article emphasizes that implementing autonomous technologies is a promising path for the sustainable development of maritime transport. Still, further research is required, investment in infrastructure is needed, and legal regulations must be adjusted.
Rocznik
Strony
88--97
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
  • Warsaw University of Life Sciences ‒ SGGW, 1Faculty of Economics, 2Department of Logistics 166 Nowoursynowska St., 02-787 Warszawa, Poland
  • Warsaw University of Life Sciences ‒ SGGW, 1Faculty of Economics, 2Department of Logistics 166 Nowoursynowska St., 02-787 Warszawa, Poland
Bibliografia
  • 1. Alamoush, A.S. & Ölçer, A.I. (2025) Maritime autonomous surface ships: Architecture for autonomous navigation systems. Journal of Marine Science and Engineering 13 (1), 122, doi: 10.3390/jmse13010122.
  • 2. Bogusławski, K., Gil, M., Nasur, J. & Wróbel, K. (2022) Implications of autonomous shipping for maritime education and training: the cadet’s perspective. Maritime Economics & Logistics 24, pp. 327‒343, doi: 10.1057/s41278-022- 00217-x.
  • 3. Dittmann, K., Hansen, P.N., Papageorgiou, D., Jensen, S., Lützen, M. & Blanke, M. (2021) Autonomous surface vessel with remote human on the loop: System design for STCW compliance. IFAC-PapersOnLine 54 (16), pp. 224‒231, doi: 10.1016/j.ifacol.2021.10.097.
  • 4. DNV GL (2020a) Study of the risks and regulatory issues of specific cases of MASS – Part 1 (Report No. 2019-1296, Rev. 0). European Maritime Safety Agency (EMSA).
  • 5. DNV GL (2020b) Study of the risks and regulatory issues of specific cases of MASS – Part 2 (Report No. 2019-0805, Rev. 0). European Maritime Safety Agency (EMSA).
  • 6. EMSA (2020) Safety and risk assessment of autonomous ships: Annual report. Available from: https://www.emsa. europa.eu/mass/safemass.html [Accessed: April 25, 2025].
  • 7. Hannaford, E., Maes, P. & Van Hassel, E. (2022) Autonomous ships and the collision avoidance regulations: a licensed deck officer survey. WMU Journal of Maritime Affairs 21, pp. 233–266, doi: 10.1007/s13437-022- 00269-z.
  • 8. Huang, Y., Chen, L., Chen, P., Negenborn, R.R., Van Gelder, P.H.A.J.M. (2020) Ship collision avoidance methods: State-of-the-art. Safety Science 121, pp. 451‒473, doi: 10.1016/j.ssci.2019.09.018.
  • 9. Humphries, F., Horne, R., Olsen, M., Dunbabin, M. & Tranter, K. (2023) Uncrewed autonomous marine vessels test the limits of maritime safety frameworks. WMU Journal of Maritime Affairs 22, pp. 317–344, doi: 10.1007/ s13437-022-00295-x.
  • 10. IMO (2019) MSC 100/20/Add.1. Annex 2. Framework for the regulatory scoping exercise for the use of Maritime Autonomous Surface Ships (MASS). International Maritime Organization.
  • 11. IMO (2021) Interim guidelines for MASS trials. MSC.1/ Circ.1604. International Maritime Organization.
  • 12. Kepesidi, A. (2022) Maritime Autonomous Surface Ships: A critical ‘MASS’ for legislative review. [Online]. Available from: https://unctad.org/news/transport-newsletter-articleno-97-fourth-quarter-2022 [Accessed: April 25, 2025].
  • 13. Kurt, I. & Aymelek, M. (2022) Operational and economic advantages of autonomous ships and their perceived impacts on port operations. Maritime Economics & Logistics 24, pp. 302‒326, doi: 10.1057/s41278-022-00213-1.
  • 14. Lu, H., Zhang, Y., Zhang, C., Niu, Y., Wang, Z. & Zhang, H. (2025) A multi-sensor fusion approach for maritime autonomous surface ships berthing navigation perception, Navigation College, Dalian Maritime University. Ocean Engineering 316, 119965, doi: 10.1016/j.oceaneng.2024.119965.
  • 15. Min, H. (2022) Developing a smart port architecture and essential elements in the era of Industry 4.0. Maritime Economics & Logistics 24, pp. 189‒207, doi: 10.1057/s41278- 022-00211-3.
  • 16. Niu, Y.H., Zhu, F.X., Wei, M.X., Du, Y.F. & Zhai, P.Y. (2023) A multi-ship collision avoidance algorithm using data-driven multi-agent deep reinforcement learning. Journal of Maritime Science and Engineering 11 (11), 2101, doi: 10.3390/jmse11112101.
  • 17. Porathe, T., Prison, J. & Man, Y. (2014) Situation awareness in remote control centers for unmanned ships. Proceedings of the 5th International Conference on Applied Human Factors and Ergonomics AHFE 2014, Kraków, Poland 19‒23 July 2014, Edited by T. Ahram, W. Karwowski and T. Marek, doi: 10.3940/rina.hf.2014.12.
  • 18. Tam, K. & Jones, K. (2019) Cyber-risk assessment for autonomous ships. 2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security), Glasgow, UK, pp. 1‒8, doi: 10.1109/CyberSecPODS. 2018.8560690.
  • 19. UNCTAD (2024) Review of Maritime Transport 2024 Navigating maritime chokepoints UNCTAD/RMT/2024. [Online]. Available from: https://unctad.org/publication/review-maritime-transport-2024 [Accessed: April 25, 2025].
  • 20. Wróbel, K., Montewka, J. & Kujala, P. (2017) Towards the assessment of potential impact of unmanned vessels on maritime transportation safety. Reliability Engineering & System Safety 165, pp. 155‒169, doi: 10.1016/j. ress.2017.03.029.
  • 21. Zhua, F., Niu, Y., Wei, M., Du, Y. & Zhai, P. (2025) A highrisk test scenario adaptive generation algorithm for ship autonomous collision avoidance decision-making based on Reinforcement Learning. Ocean Engineering 320, 120344, doi: 10.1016/j.oceaneng.2025.120344.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-ba33d803-bd90-4ec6-b5d2-b9a8f4eb8c4f
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