Safe and efficient maneuvering of a Maritime Autonomous Surface Ship (MASS) during encounters at sea: A novel approach

Maritime Transport Research - Tập 3 - Trang 100077 - 2022
Andreas Nygard Madsen1, Magne Vollan Aarset1,2, Ole Andreas Alsos3
1Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Aalesund 6025, Norway
2Research Department, TERP AS, Haugesund, Norway
3Department of Design, Norwegian University of Science and Technology, Trondheim 7491, Norway

Tài liệu tham khảo

Aarset, 2022, On distributed cognition while designing an AI system for adapted learning, Front. Artif. Intell., 5, 10.3389/frai.2022.910630 Adams, S. (2014). ReVolt – next generation short sea shipping. Retrived 5 May 2022, from https://www.dnv.com/news/revolt-next-generation-short-sea-shipping-7279#. Akdağ, 2022, Collaborative collision avoidance for Maritime Autonomous Surface Ships: a review, Ocean Eng., 250, 10.1016/j.oceaneng.2022.110920 Barredo Arrieta, 2020, Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI, Inf. Fusion, 58, 82, 10.1016/j.inffus.2019.12.012 Burmeister, 2021, Autonomous collision avoidance at sea: a survey, Front. Robot. AI, 8, 297, 10.3389/frobt.2021.739013 DB Schencker. (2022). DB schenker plans to operate a zero-emission autonomous coastal container feeder for Ekornes ASA in Norway. Retrieved September 25, 2022 from https://www.dbschenker.com/global/about/press/autonomous-vessel-norway-788212. DNV. (2018). Autonomous and remotely operated ships (DNVGL-CG-0264). Retrived 20 September, from https://rules.dnv.com/docs/pdf/DNV/cg/2018-09/dnvgl-cg-0264.pdf. Fiskin, 2021, Fuzzy domain and meta-heuristic algorithm-based collision avoidance control for ships: Experimental validation in virtual and real environment, Ocean Eng., 220, 10.1016/j.oceaneng.2020.108502 IMO. (2019). Convention on the international regulations for preventing collisions at sea, 1972 (COLREGs). Retrived September 2022, from https://www.imo.org/en/About/Conventions/Pages/COLREG.aspx. IMO. (2021). Outcome of the regulatory scoping exercise for the use of Maritime Autonomous Surface Ships (MASS) MSC.1/Circ.1638. Retrived 27 August 2022, from https://wwwcdn.imo.org/localresources/en/MediaCentre/PressBriefings/Documents/MSC.1-Circ.1638%20-%20Outcome%20Of%20The%20Regulatory%20Scoping%20ExerciseFor%20The%20Use%20Of%20Maritime%20Autonomous%20Surface%20Ships...%20(Secretariat).pdf. Kaufman, 1990 Murphy, 2012 Murray, 2021, An AIS-based deep learning framework for regional ship behavior prediction, Reliab. Eng. Syst. Saf., 215, 10.1016/j.ress.2021.107819 Perera, 2019, Possible COLREGs failures under digital helmsman of autonomous ships, 1 Rødseth, 2017, From concept to reality: Unmanned merchant ship research in Norway Rutledal, 2020, It's not all about the COLREGs: a case-based risk study for autonomous coastal ferries, 929 Tam, 2009, Review of collision avoidance and path planning methods for ships in close range encounters, J. Navig., 62, 455, 10.1017/S0373463308005134 Wróbel, 2017, Towards the assessment of potential impact of unmanned vessels on maritime transportation safety, Reliab. Eng.Syst. Saf., 165, 155, 10.1016/j.ress.2017.03.029 Wu, 2020, Fuzzy logic based dynamic decision-making system for intelligent navigation strategy within inland traffic separation schemes, Ocean Eng., 197, 10.1016/j.oceaneng.2019.106909 Xu, 2022, Path planning and dynamic collision avoidance algorithm under COLREGs via deep reinforcement learning, Neurocomputing, 468, 181, 10.1016/j.neucom.2021.09.071 Yara International. (2022). Yara Birkeland, Yara International. Retrived 26 August, from https://www.yara.com/news-and-media/press-kits/yara-birkeland-press-kit.