Inference processes in the automatic communication system for autonomous vessels

Authors

DOI:

https://doi.org/10.61089/aot2023.rf1py857

Keywords:

automation of communication processes, collision avoidance, autonomous ship, inference processes

Abstract

The era of autonomous ships has already begun in maritime transport. The 30-year forecast for the development of marine technologies predicts many autonomous vessels at sea. This will necessitate radical implementation of new intelligent maritime navigation systems. One of the intelligent systems that has to be implemented is a collision avoidance system. The inference process is a key element of autonomous manoeuvres. These authors propose an inference process that enables exchange of information, intentions and expectations between autonomous vessels and gives them an opportunity to negotiate a safe manoeuvre satisfying all the parties concerned. The model of inference in the communication process has been presented. Methods and algorithms for information exchange and negotiation have been developed. These models were implemented and tested under various conditions. The results of case studies indicate that it is possible to effectively communicate and negotiate used the developed method. To demonstrate the effectiveness of the presented approach over 30 random simulations have been carried out. After successful laboratory tests, over 100 scenarios were executed in quasi-real conditions and fully operational conditions. Tests were carried out in the center of the Foundation for the Safety of Navigation and Environmental Protection on Lake Silm in Iława, Poland. In the framework of project AVAL (Autonomous Vessel with an Air Look) POIR.04.01.04-00-0025-16,  82 random scenarios involving four vessels were performed and 60 random scenarios with two vessels. In 2020 tests were carried out in real conditions on the ferries Wolin and m/f Gryf. The communication and negotiation system presented in the article has been designed and developed specially for maritime navigation purposes. The authors believe that the presented solution can be one of various solutions implemented in autonomous shipping in the near future.

References

ASTAT - Autonomous Ship Transport at Trondheimsfjorden, http://astat.autonomous-ship.org/, accessed 01-06-2022.

AVAL 2021. Autonomous Vessel with an Air Look, http://212.33.90.155/ accessed 01-06-2022.

Amro A, Gkioulos V, Katsikas S., (2021). Communication architecture for autonomous passenger ship. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. https://doi.org/10.1177/1748006X211002546.

Bahamas Maritime Authority, (2016). THE COMMONWEALTH OF THEBAHAMAS, https://www.bahamasmaritime.com/wp-content/uploads/2020/10/BMA-Investigation-Report-Collision-between-the-Baltic-Ace-and-Corvus-J.pdf. accessed on 01-06-2022.

Ballstad, (2018). Concept development autonomous passenger ferry Ballstad, https://www.lofotenmatpark.no/portefoljer/53-forstudium-autonom-ferge-ballstadlandet-ballstadoya, accessed 01-06-2022.

BIMCO, (2016). BIMCO/ICS Manpower report predicts a potential shortage of almost 150,000 officers by 2025 https://www.bimco.org/news/priority-news/20160517_bimco_manpower_report , Posted: 17-05-2016, accessed 01-06-2022.

BIMCO, (2020). Contract templete for future autonomus shipping deals. https://www.maritime-executive.com/article/bimco-prepares-contract-template-for-future-autonomous-shipping-deals, published 11-09-2020, accessed 01-06-2022.

Bonarini, A., (2020). Communication in Human-Robot Interaction. Current Robotics Reports, 1(4), 279–285. https://doi.org/10.1007/s43154-020-00026-1.

Borkowski, P.; Pietrzykowski, Z.; Magaj, J., (2021). The Algorithm of Determining an Collision avoidance Manoeuvre Trajectory Based on the Interpolation of Ship’s State Vector. Sensors 2021, 21, 5332. https://doi.org/10.3390/s21165332.

Brekke, E.F., Wilthil, E.F., Eriksen, B.-O.H., Kufoalor, D.K.M, Helgesen, K., Hagen, I.B., Breivik, M., Johansen, T.A., (2019). The Autosea project: Developing closed-loop target tracking and collision avoidance systems. Journal of physics: conference series, 1357. https://doi.org/10.1088/1742-6596/1357/1/012020.

Faculty of Ocean Engineering and Ship Technology of the Gdańsk University of Technology, https://oio.pg.edu.pl/en/research (2020), accessed 01-06-2022.

Foundation for Safety of Navigation and Environment Protection in Iława. Available online: www.ilawashiphandling.com.pl, accessed on 01-06-2022.

Finin T., McKay D., Fritzson R., (1992). An Overview of KQML: A Knowledge Query and Manipulation Language, Staford University , Computer Science Department.

FIPA, (2002). The Foundation for Inteligent Physical Agents, Specyfications, www.fipa.org, accessed 01-06-2022.

Gil M., Montewka J., Krata P., Hinz T., Hirdaris S., (2020). Determination of the dynamic critical maneuvering area in an encounter between two vessels: Operation with negligible environmental disruption, Ocean Engineering, 213, 107709. https://doi.org/10.1016/j.oceaneng.2020.107709.

Hult, C., Praetorius, G., Sandberg C., (2019). On the future of maritime transport â discussing terminology and timeframes. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation, 13(2), 269–273. https://doi.org/10.12716/1001.13.02.01.

Hydrodrone, (2020). Marine Technology, https://marinetechnology.pl/hydrodron/, accessed 01-06-2022.

IMO, (2000). NAV 46/WP.3 International Maritime Organization IMO E Sub-Committee on Safety of Navigation 46th session Agenda item 9 NAV 46/INF.4 4 April 2000

Kang, Y.T., Chen, W.J., Zhu, D.Q., Wang, J.H., Xie, Q.M., (2018). Collision avoidance path planning for ships by particle swarm optimization. Journal of Marine Science and Technology, 26(6), 777–778. https://doi.org/10.3390/app12105036.

Klingspor, V., Demiris, Y., Kaiser, M., (1999). Human-Robot-Communication and Machine Learning. Applied Artificial Intelligence, 11(7), 719–746, Online ISSN: 1087-6545, Print ISSN: 0883-9514.

Kongsberg, (2018). Enable Autonomous Navigation in Close Proximity, https://www.kongsberg.com/maritime/about-us/news-and-media/news-archive/2018/kongsberg-coordinates-eu-funded-project-to-enable-autonomous-navigation-in-close?OpenDocument, accessed 01-06-2022.

Koszelew J., Karbowska-Chilinska J., Ostrowski K., Kuczynski P., Kulbiej E., Wolejsza P., (2020). Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles, Sensors 2020, 20, 4115. https://doi.org/10.3390/s20154115.

Kulbiej, E., (2018). Autonomous Vessels’ Pathfinding Using Visibility Graph. 2018 Baltic Geodetic Congress (BGC Geomatics), 107–111. https://doi.org/10.1109/BGC-Geomatics.2018.00026.

Lenart, A., (2015). Analysis of Collision Threat Parameters and Criteria. The Journal of Navigation, 68(5), 887–896. https://doi.org/10.1017/S0373463315000223.

Lin R., Kraus S., (2012). From Research to Practice: Automated Negotiations with People. Ubiquitous Display Environments. Springer, 195–212. https://doi.org/10.1007/978-3-642-27663-7_12.

Milli-Ampere, (2016). Autonomous passenger ferry, https://www.nrk.no/trondelag/foreslar-forerlos-passasjerferge-i-trondheim-1.12990523, published 09-06-2016, accessed 01-06-2022.

MUNIN, (2016). Concept study for unmanned bulk ship, http://www.unmanned-ship.org/munin/, accessed 01-06-2022.

Naeem, W., Henrique, S.C., Hu, (2016). L. A reactive COLREGs-compliant navigation strategy for autonomous maritime navigation. IFAC-PapersOnLine, 49(23), 207–213. https://doi.org/10.1016/j.ifacol.2016.10.344.

NAVDEC - Navigational Decision Support System http://navdec.com/en/ , Sup4Nav, 2014-2020. accessed on 01-06-2022.

Ocean2020, https://ocean2020.eu/mediterranean-sea/about-the-aim/, published 22-11-2019, accessed 01-06-2022.

Ozturk, U., Cicek, K., (2019). Individual collision risk assessment in ship navigation: A systematic literature review. Ocean Engineering, 180, 130–143. https://doi.org/10.1016/j.oceaneng.2019.03.042.

Ożoga, B., Montewka, J., (2018). Towards a decision support system for maritime navigation on heavily trafficked basins. Ocean Engineering, 159, 88–97. https://doi.org/10.1016/j.oceaneng.2018.03.073.

Pietrzykowski Z., Hatłas P., Wójcik A., Wołejsza P., (2016). Subontology of communication in the automation of negotiating processes in maritime navigation, Scientific Journals Maritime University of Szczecin, 46(118), 209–216. https://repository.am.szczecin.pl/handle/123456789/2703.

Pietrzykowski Z., Wołejsza P., Nozdrzykowski Ł., Borkowski P., Banaś P., Magaj J., 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. https://doi.org/10.1016/j.oceaneng.2022.112104.

Pritchard B., (2010). Nature of Maritime VHF Communications and Prospects for New Research, Communication for maritime purposes, An international and interdisciplinary issue, Universiteit Antwerpen, 43–56.

R&D Roadmap for smart & autonomous sea transport systems https://www.sintef.no/contentassets/28f5e5f64a2b477e9e35be3fefe9c7f3/rd-road-map-smart-autonomous-shipping.pdf/, published October 2020, accessed 01-06-2022.

Republic of Cyprus, (2013). Department Of Merchant Shipping Ministry Of Communications And Works, 92a/2012, 1043/2013 https://pkbwm.gov.pl/wp-content/uploads/images/uchwaly_raporty/raporty/raporty_obce/Final_report_Corvus_J_WIM_07_12_DMS_Cyprus.pdf, accessed on 01-06-2022.

Rymarz, W., (2015). Międzynarodowe Prawo Drogi Morskiej, Trademar, in Polish.

Stateczny, A., Burdziakowski, P., (2019). Universal autonomous control and management system for multipurpose unmanned surface vessel. Polish Maritime Research, 26, 30–39. https://doi.org/10.2478/pomr-2019-0004.

Szubrycht, T., (2020). Marine accidents as potential crisis situations on the Baltic Sea. Archives of transport, 54, 125–135. https://doi.org/10.5604/01.3001.0014.2972.

Tamashiro, G., Vivaldini, K.C.T., Martins, J., Becker, M., (2014). Communication architecture for robotic applications, 123–130. https://doi.org/10.14809/faim.2014.0123.

Tsou, M.C., (2016). Multi-Target collision avoidance route planning under ECDIS framework. Ocean Engineering, 121, 268–278. https://doi.org/10.1016/j.oceaneng.2016.05.040.

Wang, P., Gao, S., Li, L., Cheng, S., & Zhao, H.,(2020). Research on driving behavior decision making system of autonomous driving vehicle based on benefit evaluation model. Archives of transport, 53, 21–36. https://doi.org/10.5604/01.3001.0014.1740.

Wójcik, A., Banaś, P., (2016). Implementation of a preliminary inference algorithm for an automatic communication system. Scientific Journals Maritime University of Szczecin, 46(118), 54–57, https://doi.org/10.1515/aon-2018-0018.

Wójcik, A., Hatłas, P., Pietrzykowski, Z., (2016). Modeling communication processes in maritime transport using computing with words. Archives of Transport System Telematics, 9(4), 47–51.

Yara Birkeland, (2020). https://www.yara.com/news-and-media/press-kits/yara-birkeland-press-kit/, published November 2020, accessed 01-06-2022.

Zhao, L., Roh, M.I., (2019). COLREGs-compliant multi-ship collision avoidance based on deep reinforcement learning. Ocean Engineering, 191, 106436. https://doi.org/10.1016/j.oceaneng.2019.106436.

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Published

2023-11-24

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Original articles

How to Cite

Pańka, A., & Wołejsza, P. (2023). Inference processes in the automatic communication system for autonomous vessels. Archives of Transport, 68(4), 117-135. https://doi.org/10.61089/aot2023.rf1py857

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