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Data Acquisition in a Manoeuver Auto-negotiation System

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EN
Abstrakty
EN
Typical approach to collision avoidance systems with artificial intelligence support is that such systems assume a central communication and management point (such as e.g. VTS station), usually located on shore. This approach is, however, not applicable in case of an open water encounter. Thus, recently a new approach towards collision avoidance has been proposed, assuming that all ships in the encounter, either restricted or open water, communicate with each other and negotiate their maneuvers, without involving any outer management or communication center. Usually the negotiation process is driven by the collision avoidance software and called auto-negotiation. This paper elaborates on data acquisition problem in case of the maneuver auto-negotiation. It focuses on ships' initialization in the system and data gathering.
Twórcy
  • Gdynia Maritime University, Gdynia, Poland
Bibliografia
  • 1 Brcko T., Svetak J., Fuzzy Reasoning as a Base for Collision Avoidance Decision Support System. Promet – Traffic & Transportation, Vol. 25, No. 6, str. 555‐564, 2013.
  • 2 Cheng, X., Liu, Z., Trajectory Optimization for Ship Navigation Safety Using Genetic Annealing Algorithm. ICNC 2007. Third International Conference on Natural Computation. vol. 4, str. 385 – 392, 2007.
  • 3 COLREGS, Convention on the International Regulations for Preventing Collisions at Sea. International Maritime Organization, 1972 (with amendments on Dec 2009).
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  • 6 Hu Q., Yang C., Chen H., Xiao B., Planned Route Based Negotiation for Collision Avoidance Between Vessels. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 2, No. 4, str. 363‐368, Gdynia Maritime University, 2008.
  • 7 Ito, M., Feifei Z., Yoshida, N., Collision avoidance control of ship with genetic algorithm. Proceedings of the 1999 IEEE International Conference on Control Applications, vol. 2, str. 1791 – 1796, 1999.
  • 8 Kolendo P., Śmierzchalski R., Jaworski B., Experimental Research on Evolutionary Path Planning Algorithm with Fitness Function Scaling for Collision Scenarios. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 5, No. 4, str. 489‐495, Gdynia Maritime University, 2011.
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  • 14 Smierzchalski, R., Evolutionary trajectory planning of ships in navigation traffic areas. Journal of Marine Science and Technology, vol. 4, Issue 1, str. 1–6, Springer, 1999.
  • 15 Szlapczynska J.: Propozycja systemu auto‐negocjacji manewrów statków korzystającego z metod optymalizacji wielokryterialnej oraz Matematycznej Teorii Ewidencji (in Polish), Logistyka vol. 6/2014, pp. 10375‐10384, 2014.
  • 16 Szlapczynski R.: Fuzzy Collision Threat Parameters Area (FCTPA) – A New Display Proposal. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 2, No. 4, pp. 359‐362, 2008
  • 17 Szlapczynski R., Solving Multi‐Ship Encounter Situations by Evolutionary Sets of Cooperating Trajectories. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 4, No. 2, str. 185‐190, Gdynia Maritime University, 2010.
  • 18 Szlapczynski R., Szlapczynska J., On Evolutionary Computing in Multi‐Ship Trajectory Planning. Applied Intelligence, Volume 37, Issue 2, str. 155‐174, Springer, 2012.
  • 19 Tam, C., Bucknall, R., Path‐planning algorithm for ships in close‐range encounters. Journal of Marine Science and Technology, vol. 15, Issue 4, str.395‐407, Springer, 2010.
  • 20 Tsou, M. C., Hsueh, C. K. The study of ship collision avoidance route planning by ant colony algorithm. Journal of Marine Science and Technology, 18(5), 746– 756, Springer, 2010.
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  • 23 WWW_AIS, http://www.aisreporter.com/?news=aisvulnerabilities‐ subject‐of‐scientific‐research, web page accessed on 2015.02.01, 2015.
Typ dokumentu
Bibliografia
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