Decision support system for collision avoidance at sea

Lazarowska, Agnieszka

doi:10.2478/v10012-012-0018-2

Abstract

The paper presents design and realization of computer decision support system in collisionsituations of passage with greater quantity of met objects. The system was implementedinto the real ship electro-navigational system onboard research and training ship m/vHORYZONT II. The radar system with Automatic Radar Plotting Aid constitutes a sourceof input data for algorithm determining safe trajectory of a ship. The article introducesradar data transmission details. The dynamic programming algorithm is used for thedetermination of safe optimal trajectory of own ship. The system enables navigationaldata transmission from radar system and automatic determining of safe manoeuvre or safetrajectory of a ship. Further development of navigator’s decision support system is also presented. PathPlanning Subsystem is proposed for the determination of global optimal route between harbours with theuse of Ant Colony Optimization algorithms.

References

1. Wołejsza P., Szewczuk T.: Analysis of navigational dataavailability on the basis of m/s Nawigator XXI. Scientific Journals, Maritime University of Szczecin. No. 13(85), 2008, p.115-119.
Search in Google Scholar
2. Bole A., Dineley B: Radar and ARPA manual. Butterworth- Heinemann Ltd, Oxford, 2000.
Search in Google Scholar
3. Rothblum A.M., Wheal D., Withington S., Shappell S.A., Wiegmann D.A., Boehm W., Chaderjian M.: Key to successfulincident inquiry. In: Proceedings 2nd international workshop on human factors in offshore operations, HFW2002, Houston, TX, p.1-6.
Search in Google Scholar
4. Cockcroft A.N., Lameijer J.N.F.: a guide to collision avoidancerules. Elsevier, Amsterdam-Tokyo, 2004.
Search in Google Scholar
5. Lisowski J.: Computational intelligence methods in the safe shipcontrol process. Polish Maritime Research. No. 1,Vol. 8, 2001, p. 18-24.
Search in Google Scholar
6. IEC 61162-1 International Standard: Maritime navigationand radio communication equipment and systems - Digitalinterfaces - Part 1: Single talker and multiple listeners.
Search in Google Scholar
7. Documents for Operators and Engineers: Operating InstructionsRADARPILOT 1100, Service Manual IEC-Interface. SAM Electronics, 2005.
Search in Google Scholar
8. Daniluk A.: RS 232C - practical programming. From Pascaland C++ to Delphi and Builder, Helion, Warszawa, 2007 (in Polish).
Search in Google Scholar
9. Lisowski J.: Optimal and game ship control algorithmsfor avoiding collisions at sea. In C.A. Brebbia (Ed), Risk Analysis VI: Simulation and Hazard Mitigation, WIT Press Computational Mechanics Inc., Southampton-Boston, 2008, p. 525-534.10.2495/RISK080511
Search in Google Scholar
10. Lisowski J.: Sensitivity of Safe Game Ship Control. 16th Mediterranean Conference on Control and Automation Congress Centre, Ajaccio, France, 2008, p.220-225.10.1109/MED.2008.4601979
Search in Google Scholar
11. Lisowski J.: The Dynamic Game Models of Safe Navigation. TransNav - International Journal of Marine Navigation and Safety of Sea Transportation, Vol.1, No.1, 2007, p. 11-18.
Search in Google Scholar
12. Lisowski J.: The dynamic game theory methods applied toship control with minimum risk of collision. In C.A. Brebbia and V.Popov (Ed), Risk Analysis V: Simulation and Hazard Mitigation, WIT Press Computational Mechanics Inc., Southampton-Boston, 2006, p. 293-302.10.2495/RISK060281
Search in Google Scholar
13. Lisowski J.: Multi-step matrix game with the risk of shipcollision. In C.A. Brebbia (Ed), Risk Analysis IV: Simulation and Hazard Mitigation, WIT Press Computational Mechanics Inc., Southampton-Boston, 2004, p. 669-680.
Search in Google Scholar
14. Pietrzykowski Z., Uriasz J..: Knowledge Representation ina Ship’s Navigational Decision Support System. TransNav - International Journal of Marine Navigation and Safety of Sea Transportation, Vol.4, No.3, 2010, p. 265-270.
Search in Google Scholar
15. Zhuo Y., Hearn G.E.: a ship based intelligent anti-collisiondecision-making support system utilizing trial manoeuvers. Proceedings of 2008 Chinese control and decision conference, CCDC 2008, Yantai, China, p. 3982-3987.
Search in Google Scholar
16. Perera L.P., Carvalho J.P., Guedes Soares C.: Fuzzy logicbased decision making system for collision avoidance of oceannavigation under critical collision conditions. Journal of Marine Science and Technology, Vol. 16, No. 1, 2011, p.84-99.10.1007/s00773-010-0106-x
Search in Google Scholar
17. Lee S.-M., Kwon K.-Y., Joh J.: a Fuzzy Logic for AutonomousNavigation of Marine Vehicles Satisfying COLREG Guidelines. International Journal of Control, Automation, and Systems, Vol. 2, No. 2, 2004, p.171-181.
Search in Google Scholar
18. Hwang C.-N., Joe-Ming Yang J.-M., Chiang C.-Y.: The designof fuzzy collision-avoidance expert system implemented by H∞-autopilot. Journal of Marine Science and Technology, Vol. 9, No. 1, 2001, p. 25-37.10.51400/2709-6998.2432
Search in Google Scholar
19. Śmierzchalski R., Michalewicz Z.: Modeling of ship trajectoryin collision situations by an evolutionary algorithm. IEEE Transactions on Evolutionary Computation, Vol. 4, No. 3 , 2000, p.227-241.10.1109/4235.873234
Search in Google Scholar
20. Cheng X.D., Liu Z.Y., Zhang X.T.: Trajectory optimizationfor ship collision avoidance system using genetic algorithm. Proceedings OCEANS 2006 - Asia Pacific, Singapore, p. 1-5.10.1109/OCEANSAP.2006.4393976
Search in Google Scholar
21. Lisowski J.: Optimization decision support system for safe shipcontrol. In C.A. Brebbia (Ed), Risk Analysis VII: Simulation and Hazard Mitigation, WIT Press Computational Mechanics Inc., Southampton-Boston, 2010, p. 259-272.10.2495/RISK100231
Search in Google Scholar
22. Lisowski J.: Multistage ship’s optimal control in collisionsituations using a neural network. II International Conference Safe Navigation Beyond, 2000, p.109-119.
Search in Google Scholar
23. Lisowski J., Pachciarek A.: Navigational data transmissionin computer navigator’s decision support system in collisionsituation. Telecommunication review, No. 1, 2009, p. 33-35 (in Polish).
Search in Google Scholar
24. Pachciarek A.: Project of navigator’s decision support systemwith the use of algorithms determining safe trajectory of a ship. MSc thesis, Gdynia Maritime University, 2008, (in Polish).
Search in Google Scholar
25. Tran T., Harris C.J., Wilson P.A.: Maritime AvoidanceNavigation, Totally Integrated system (MANTIS). 12th SCSS 1999 - 12th Ship Control Systems Symposium, The Hague, The Netherlands, Royal Dutch Navy.
Search in Google Scholar
26. Blum C.: Ant colony optimization: Introduction and recenttrends. Physics of life Reviews, No. 2(4), p.353-373, 2005.10.1016/j.plrev.2005.10.001
Search in Google Scholar
27. Dorigo M., Stutzle T.: The Ant Colony OptimizationMetaheuristic: Algorithms, Applications, and Advances. Handbook of Metaheuristics, 2002.10.1007/0-306-48056-5_9
Search in Google Scholar
28. Dorigo M., Di Caro G., Gambardella L.M.: Ant Algorithms forDiscrete Optimization.Artificial Life, No. 5(2), p.137-172, 1999.10.1162/10645469956872810633574
Search in Google Scholar
29. Szłapczyńska J.: Application of evolutionary algorithms andrank-based methods for path planning of a vessel with hybridpropulsion. Doctoral thesis, West Pomeranian University of Technology, Szczecin, 2009 (in Polish).
Search in Google Scholar
30. Wiśniewski B.: Ship Ocean Route Programming. Scientific Journals, Maritime University of Szczecin. No. 2(74), 2004, p.395-406.
Search in Google Scholar

Decision support system for collision avoidance at sea

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