An intelligent real-time multi-vessel collision risk assessment system from VTS view point based on fuzzy inference system

Expert Systems with Applications

Volumn 40, Issue 4, 2013, Pages 1220-1230

  Bukhari, Ahmad C ^a   Tusseyeva, Inara ^a   Lee, Byung Gil ^b   Kim, Yong Gi ^a  

^a Gyeongsang National University   (South Korea)

^b Electronics and Telecommunications Research Institute (ETRI)   (South Korea)

Author keywords

Calculation of real time collision; DCPA TCPA calculation; Intelligent vessel simulators; Vessels collision risk assessment

Indexed keywords

COLLISION RISK ASSESSMENT; COLLISION RISKS; FUZZY INFERENCE SYSTEMS; INDUSTRIAL GROWTH; INTELLIGENT DECISION MAKING; INTELLIGENT SOFTWARE; INTELLIGENT SOLUTIONS; LABORATORY EXPERIMENTS; MARINE TRAFFIC; PERFORMANCE EFFICIENCY; POINT-BASED; SMART SYSTEM; TRAFFIC MANAGEMENT; VEHICLE TRAFFIC; VESSEL NUMBER;

DISPLAY DEVICES; FUZZY SYSTEMS; OCEAN ENGINEERING; SHIPS;

RADAR;

EID: 84870249094     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.08.016     Document Type: Article

References (31)

1. C.B. Ahmad, and G.K. Yong Integration of a secure type-2 fuzzy ontology with a multi-agent platform: A proposal to automate the personalized flight ticket booking domain Information Sciences 198 2012 24 47
2. S.L. Andrzej Manoeuvringto required approach parameters - CPA distance and time Annual of Navigation 23 1999 99 108
3. Anvar, A. M. (2003). Intelligent navigation process for autonomous underwater vehicles (AUVs) using time-based fuzzy temporal reasoning. In Proceedings of the 10th international symposium on temporal representation and reasoning (pp. 56-61). Australia.
4. Chun, Y.; Qinyou, H.; Chaojian, Sh. (2007). Automated collision resolution for vessel traffic management by using cCooperative multi-agent negotiation. In Proceedings of the 7th international conference on ITS (pp. 455-459).
5. J.O. Flower, and N. Vijeh Design, performance and assessment of a self-organising fuzzy-logic controller applied to the level control of a highly non-linear fluid supply system International Maritime Technology 3 109 1997 209 231
6. Hao, J. L.; Zhao, L. N.; Hu, J. F.; Yang, X. B. (2007). Decision-making model for multi-ship collision avoidance based on adaptive genetic algorithm. In International conference on transportation, engineering (pp. 606-611).
7. K. Hara, and A. Hammer A safe way of collision avoidance maneuver based on maneuvering standard using fuzzy reasoning model 93 1993 163 170
8. Hogström, P.; Ringsberg, J. W. (Submitted for publication in Ocean Engineering). Assessment of the crashworthiness of a selection of innovative ship structures. Marine Structures.
9. H. Imazu, and T. Koyama The optimization of the criterion for collision avoidance action The Journal of Japan Institute of Navigation 71 1984 123 130
10. Jianghua, S.; Guang, R. (2006). An AND-OR fuzzy neural network and ship application. In Proceedings of IEEE international conference on information acquisition (pp. 605-610).
11. Kayano, J.; Imazu, H. (2009). A study of a collision avoidance support system. In Proceedings of IEEE international conference on systems, man, and cybernetics. San Antonio.
12. Lee, H. J.; Rhee, K. P. (2001). Development of collision avoidance system by using expert system and research algorithm. In Proceedings of international shipbuilding programming conference (pp. 197-212).
13. Liu, Y. H.; Liu, H. X. (2006). Case learning base on evaluation system for vessel collision avoidance. Machine learning and cybernetics. In Proceedings of international conference on, china.
14. E.H. Mamdani, and S. Assilian Experiment in linguistic synthesis with a fuzzy logic controller International Journal of Human Computer Studies 2 51 1999 135 147
15. Mitomo, N.; Hikida, K.; Murai, K.; Hayashi, Y.; Okazaki, T. (2008). A few comments on visual system of ship handling simulator based on arriving port. Systems, man and cybernetics. In IEEE international conference on SMC (pp. 1890-18940).
16. Okazaki, T.; Koike, T.; Hirai, Y.; Kayano, J. (2010). Development of ship simulator system for designing auto-pilot. In World automation congress (WAC).
17. Perera, L. P.; Carvalho, J. P.; Guedes, S. C. (2009). Autonomous guidance and navigation based on the COLREGs rules and regulations of collision avoidance. In Proceedings of the international workshop "Advanced ship design for pollution prevention" (pp. 205-216).
18. Perera, L. P.; Carvalh, o. J. P.; Guedes, S. C. (2009). Decision making system for the collision avoidance of marine vessel navigation based on COLREGs rules and regulations. In Proceedings of 13th congress of intelligent maritime association of mediterranean (pp. 121-1128). Istanbul, Turkey.
19. Perera, L. P.; Carvalho, J. P.; Guedes, S. C. (2011). Mamdani type fuzzy inference failures in navigation. In Proceedings of 9th IEEE international conference on industrial informatics (pp. 99-104). Lisbon, Portugal.
20. Qinyou, H.; Qiaoer, H.; Chaojian, S. H. (2006). A negotiation framework for automatic collision avoidance between vessels. In Proceedings of 9th IEEE international conference on industrial informatics (pp. 99-104). Lisbon, Portugal.
21. Ren, Y.; Mou, J.; Yan, Q.; Zhang, F. (2011). Study on assessing dynamic risk of ship collision. Multimodal approach to sustained transportation system development - Information, technology, implementation. In Proceedings of 1st international conference on transportation information and safety (pp. 2751-2757).
22. Shi, L.; Peng. (2008). A new approach for ARPA display and collision danger assessment. In Proceedings of international radar symposium. Wroclaw.
23. R. Smierzchalski, and Michalewicz Adaptive modeling of a ship trajectory in collision situations at sea IEEE Transactions on Evolutionary Computation 3 2000 227 241
24. C.M. Su, K.Y. Chang, and C.Y. Cheng Fuzzy decision on optimal collision avoidance measures for ships in vessel traffic service Journal of Marine Science and Technology 1 20 2012 38 48
25. Sui, J.; Ren, G. (2006). An AND-OR fuzzy neural network ship controller design. In Proceedings of 13th international conference on neural information processing (Vol. LNCS - III 4234, pp. 616-625). Hong Kong.
26. Szlapczynski, R.; Smierzchalski, R. (2009). Supporting navigator's decisions by visualizing ship collision risk. Vol. 16(1). ISSN: 12332585.
27. Q. Xiaobo, M. Qiang, and S. Li Ship collision risk assessment for the Singapore strait Accident Analysis and Prevention 43 6 2011 2030 2036
28. YaLei, R.; JinMin, M.; Qing, X. Y.; Fan, Z. h. (2011). Study on assessing risk of ship collision. In ICTIS 2011, ASCE (pp. 2751-2757).
29. G.K. Yong An autonomous navigation system for unmanned underwater vehicle Underwater Vehicles 2009 279 294
30. L.A. Zadeh Fuzzy sets. Information Control 3 8 1965 338 353
31. Zhang, X. F.; Xia, Z.; Kang, C. (2011). Tow ship interference cancelling based on blind source separation algorithm. In Proceedings of 2011 3rd international conference on awareness, science and technology (pp. 465-468).