The Comparison of Safe Control Methods in Marine Navigation in Congested Waters

• Autorzy: Lisowski J.
• Języki publikacji: EN

Abstrakty

EN

The paper introduces comparison of five methods of safe ship control in collision situation: multi-stage positional non-cooperative and cooperative game, multi-step matrix game, dynamic and kinematics optimisation with neural constrains of state control process. The synthesis of computer navigator decision supporting algorithms with using dual linear programming and dynamic programming methods has been presented. The considerations have been illustrated an examples of a computer simulation the algorithms to determine the safe own ship's trajectory in situation of passing a many of the ships encountered at sea.

Słowa kluczowe

EN

marine navigation; Congested Waters; Collision Situation; safe ship control; Decision Supporting Algorithm; Dynamic Programming Method; Linear Programming Method; Safe Own Ship's Trajectory

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2009
• Tom: Vol. 3, no. 2
• Strony: 163--172
• Opis fizyczny: Bibliogr. 27 poz., rys., tab.

Twórcy

autor

Lisowski J.

• Gdynia Maritime University, Gdynia, Poland

Bibliografia

• 1 Baba, N. & Jain, L.C. 2001. Computational Intelligence in Games. New York: Physica-Verlag.
• 2 Cahill, R.A. 2002. Collisions and thair Causes. London: The Nautical Institute.
• 3 Cichuta, M. & Dalecki, M. 2000. Study of computer program determining safe ship’s game trajectory with consideration risk of collision. M.Sc. thesis, Gdynia Maritime Academy, (in Polish).
• 4 Engwerda, J.C. 2005. LQ Dynamic Optimization and Differen-tial Games. West Sussex: John Wiley and Sons.
• 5 Isaacs,. R. 1965. Differential games. New York: John Wiley and Sons.
• 6 Lavalle, S.M. 2006. Planning algorithm. New York: Camridge.
• 7 Lebkowski, A. 2001. Study and computer simulation of game positional control algorithm with consideration ship’s speed changes in Matlab. M.Sc. thesis, Gdynia Maritime Academy, (in Polish).
• 8 Levine, W.S. 1996. The Control Handbook. Florida: CRC Press.
• 9 Lisowski, J. 2006a. The dynamic game theory methods applied to ship control with minimum risk of collision. Risk Analy-sis V: Simulation and Hazard Mitigation. Southampton, Boston: WIT Press: 293-302.
• 10 Lisowski, J. 2006b. Game theory methods in control synthesis of marine moving objects – mathematical models and com-puter support algorithms. Proc. of the 10th IEEE Interna-tional Conference on Methods and Models in Automation and Robotics, Miedzyzdroje: 21-39.
• 11 Lisowski, J. 2007a. Intelligent safe ship control methods in col-lision avoidance. Proc. of European Control Conference, Kos: 1-6.
• 12 Lisowski, J. 2007b. The dynamic game models of safe naviga-tion. Chapter in Monograph TransNav’2007: Advances in marine navigation and safety of sea transportation. Gdynia: Gdynia Maritime University-The Nautical Institute in Lon-don: 23-30.
• 13 Lisowski, J. 2007c. Application of dynamic game and neural network in safe ship control. Polish Journal of Environmen-tal Studies. Vol. 16: 114-120.
• 14 Lisowski, J. 2008a. Optimal and game ship control algorithms avoiding collisions at sea. Risk Analysis VI: Computer Simulation Risk Analysis and Hazard Mitigation. South-ampton, Boston: WIT Press: 1-10.
• 15 Lisowski, J. 2008b. Game and optimal safe ship control. Chap-ter in monograph Recent Advances in Control and Automa-tion. Warszawa: Exit: 302-312.
• 16 Lisowski, J. 2008c. Sensitivity of safe game ship control. Proc. of 16th IEEE Mediterranean Conference on Control and Automation, Corsica: 220-225.
• 17 Lisowski, J. & Mohamed-Seghir, M. 2008d. Safe ship control methods based on fuzzy set theory. Polish Journal of Envi-ronmental Studies. Vol. 17, No 3C: 55-58.
• 18 Nisan, N., Roughgarden, T., Tardos, E. & Vazirani, V.V. 2007. Algorithmic Game Theory. New York: Cambridge Univer-sity Press: 717-733.
• 19 Nise, N.S. 2008. Control systems engineering. New York: John Wiley & Sons.
• 20 Nowak, A.S. & Szajowski, K. 2005 Advances in Dynamic Games – Applications to Economics, Finance, Optimization and Stochastic Control. Boston, Basel, Berlin: Birkhauser.
• 21 Osborne, M.J, 2004. An Introduction to Game Theory. New York: Oxford University Press.
• 22 Pachciarek, A. 2007. Comparative analysis of safe ship trajec-tory determining on computer simulation. B.Sc. thesis, Gdynia Maritime University, (in Polish).
• 23 Radzik, T. 2000. Characterization of optimal strategies in ma-trix games with convexity properties. International Journal of Game Theory. Vol. 29: 211-228.
• 24 Sandom, C. & Harvey, R.S. 2004. Human factors for engi-neers. London: The Institution of Electrical Engineers.
• 25 Segal, A. & Miloh, T. 1998. A new three dimensional differen-tial game of pursuit and evasion. Proc. of the 8th Interna-tional Symposium on Dynamic Games and Applications. Maastricht.
• 26 Skogestad, S. & Postlethwaite, I. 2005. Multivariable feedback control. New York: John Wiley & Sons.
• 27 Straffin, P.D. 2001. Game Theory and Strategy. Warszawa: Scholar (in Polish).