Autonomous shipping – a stochastic model of the process describing the safety of MASS operation

• Autorzy: Burciu Zbigniew , Abramowicz-Gerigk Teresa

Identyfikatory

DOI

10.17402/586

• Języki publikacji: EN

Abstrakty

EN

The main interest in introducing maritime autonomous surface ships (MASS) is centered on communication, autonomous navigation, and collision avoidance systems. This paper presents a more comprehensive approach, accounting for selected issues relating to navigation safety, ship operation, maritime rescue, and decision support systems for the MASS remote managing operator. The technical solutions for improving the safety of MASS operation are described, and the decision support system (DSS) for the MASS operator, based on the stochastic model of the process describing the safety of MASS operation, is proposed. The presented analysis can be used to build a computer program and an integrated decision support system that increases the safety and reliability of the MASS operator’s decision-making process.

Słowa kluczowe

EN

maritime autonomous surface ships; semi-Markov process; decision support system; search area determination; rescue platform

• Wydawca: Wydawnictwo Naukowe Politechniki Morskiej w Szczecinie
• Czasopismo: Zeszyty Naukowe Politechniki Morskiej w Szczecinie
• Rocznik: 2023
• Tom: nr 76 (148)
• Strony: 57--64
• Opis fizyczny: Bibliogr. 13 poz., rys.

Twórcy

autor

Burciu Zbigniew

• Faculty of Navigation, Gdynia Maritime University 81-87 Morska St., 81-225 Gdynia, Poland

• https://orcid.org/0000-0001-5171-1943

autor

Abramowicz-Gerigk Teresa

• Faculty of Navigation, Gdynia Maritime University 81-87 Morska St., 81-225 Gdynia, Poland

• https://orcid.org/0000-0002-0477-3161

Bibliografia

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• 2. Burciu, Z. (2012) Reliability of rescue operation in sea transport. Warsaw: Publishing House of the Warsaw University of Technology (in Polish).
• 3. Gerigk, M. (2022) Interference between land and sea logistics systems. Multifunctional building system design towards autonomous integrated transport infrastructure. TransNav – The International Journal on Marine Navigation and Safety of Sea Transportation 16(3), pp. 439–446, doi: 10.12716/1001.16.03.04.
• 4. Gerigk, M.K. & Gerigk, M. (2019) Challenges associated with development of AUV – unmanned autonomous underwater vehicles to be operated using the AI-based control systems. Per Mare Ad Astra Space Technology, Governance and Law, pp. 33–46.
• 5. Grabski, F. & Jaźwiński, J. (2001) Bayesian methods in diagnostic reliability. Warsaw: Publishing House of Communications and Communications.
• 6. Grabski, F. & Jaźwiński, J. (2009) Random-argument functions in reliability, security, and logistics. Warsaw: Communications and Communications Publishing House (in Polish).
• 7. Idzior, M. (2022) Possibilities of autonomous means of sea transport. Scientific Journals of the Maritime University of Szczecin, Zeszyty Naukowe Akademii Morskiej w Szczecinie 70 (142), pp. 20–26, doi: 10.17402/505.
• 8. Łebkowski, A. (2018) Design of an Autonomous Transport System for Coastal Areas. TansNav – The International Journal on Marine Navigation and Safety of Sea Transportation 12(1), pp. 117–124, doi: 10.12716/1001.12.01.13.
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• 11. Pietrzykowski, Z., Wołejsza, P., Nozdrzykowski, Ł., Borkowski, P., Banaś, P., Magaj, P., Chomski, J., Mąka, M., Mielniczuk, S., Pańka A., Hatłas-Sowińska, P., Kulbiej, E., Nozdrzykowska, M. (2022) The autonomous navigation system of a sea-going vessel. Ocean Engineering 261, 112104, doi: 10.1016/j.oceaneng.2022.112104.
• 12. Stewart, M. & Melchers, R.E. (1997) Probabilistic Risk Assessment of Engineering Systems. London, Weinham, New York, Tokyo, Melbourne, Madras: Chapman & Hall.
• 13. Wróbel, K., Gil, M., Krata, P., Olszewski, K. & Montewka, J. (2023) On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships. Proceedings of the Institution of Mechanical Engineers Part O: Journal of Risk and Reliability 237(2), pp. 314–331, doi: 10.1177/1748006X2110276.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).