Determination and Display of Safe Ship Trajectories in Collision Situations at Sea

Abstract:

In this paper, game and optimization theory is applied to the marine navigation in congested waters. The process of game ship control is mentioned first, and then the base model and the approximated models are described with the simulation results. For each approximated model of the dynamic game, an appropriate method of safe control to support the navigator decision in a collision situations has been assigned. The considerations have been illustrated an examples of a computer simulation of several algorithms to determine the safe ship's trajectory in situations of passing many of the ships encountered, recorded on the radar screen in real navigational situation at sea.

• Periodical: Solid State Phenomena (Volume 236)
• Pages: 128-133
• DOI: https://doi.org/10.4028/www.scientific.net/SSP.236.128
• Online since: July 2015
• Authors: Józef Lisowski*
• Keywords: Game Theory, Marine Systems, Optimal Control, Safe Trajectories, Safety Navigation, Ship Control, Simulation

References

[1] N. Baba, L.C. Jain, Computational intelligence in games, Physica-Verlag, New York, (2001).

[2] T. Basar, G.J. Olsder, Dynamic noncooperative game theory, SIAM, Philadelphia, (1998).

[3] D.S. Bist, Safety and security at sea, Butter Heinemann, Oxford-New Delhi, (2000).

[4] A. Bole, B. Dineley, A. Wall, Radar and ARPA manual, Elsevier, Amsterdam-Tokyo, (2006).

[5] R.A. Cahill, Collisions and their causes, The Nautical Institute, London, (2002).

[6] A.N. Cockcroft, J.N.F. Lameijer, The collision avoidance rules, Elsevier, Amsterdam-Tokyo, (2006).

[7] H. Gluver, D. Olsen, Ship collision analysis, A.A. Balkema, Rotterdam-Brookfield, (1998).

[8] R. Isaacs, Differential games, John Wiley and Sons, New York, (1965).

[9] A. Lazarowska, Ant colony optimization based navigational decision support system, 18th International Conference in Knowledge Based and Intelligent Information and Engineering Systems KES2014, Gdynia, Elsevier Procedia Computer Science, 35 (2014).

DOI: 10.1016/j.procs.2014.08.187

[10] A. Lazarowska, Safe ship control method with the use of ant colony optimization, Solid State Phenomena. 210 (2014) 234-244.

DOI: 10.4028/www.scientific.net/ssp.210.234

[11] A. Łebkowski, Control of ship movement by the agent system, Polish Journal of Environmental Studies. 17 (2008) 16-22.

[12] M. Modares, Risk analysis in engineering, Taylor and Francis Group, Boca Raton, (2006).

[13] N. Nisan, T. Roughgarden, E. Tardos, V.V. Vaziriani, Algorithmic game theory, Cambridge University Press, New York, (2007).

[14] N.S. Nise, Control systems engineering, John Wiley and Sons, New York, (2008).

[15] M.J. Osborne, An introduction to game theory, Oxford University Press, New York, (2004).

[16] A. Rak, W. Gierusz, Reinforcement learning in discrete and continuous domains applied to ship trajectory generation, Polish Maritime Research. 19 (2012) 31-36.

DOI: 10.2478/v10012-012-0020-8

[17] M.M. Seghir, Safe ship's control in a fuzzy environment using genetic algorithm, Solid State Phenomena. 180 (2012) 70-75.

DOI: 10.4028/www.scientific.net/ssp.180.70

[18] J.L. Speyer, D.H. Jacobson, Primer on optimal control theory, SIAM, Philadelphia, (2010).

[19] E. Zio, Computational methods for reliability and risk analysis, Series on Quality, Reliability and Engineering Statistics. 14 (2009) 295-334.

DOI: 10.1142/7190