Composition ship collision risk based on fuzzy theory

Shu Chen , Rashid Ahmad , Byung-Gil Lee , DoHyeun Kim

Journal of Central South University ›› 2014, Vol. 21 ›› Issue (11) : 4296 -4302.

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Journal of Central South University ›› 2014, Vol. 21 ›› Issue (11) : 4296 -4302. DOI: 10.1007/s11771-014-2428-z
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Composition ship collision risk based on fuzzy theory

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Abstract

Despite of modern navigation devices, there are problems in navigation of vessels in waterways due to the geographical structures, disturbances in water, dynamic nature, and heavily environmental influenced sea traffic. Even though all vessels are equipped with modern navigation devices, the accidents are reported caused by various reasons and mainly by human factor according to investigation. We propose an effective and efficient composition collision risk calculation method for finding the collision probability and avoiding the collision between ships in possible collision situations. The proposed composition collision risk calculation method at ship’s position using combination of fuzzy and fuzzy comprehensive evaluation methods. The algorithm is straightforward to implement and is shown to be effective in automatic ship handling for ships involved in complex navigation situations. Experiments are carried out with indigenous data and the results show the effectiveness of the proposed approach.

Keywords

automatic ship navigation / collision risk / fuzzy theory

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Shu Chen, Rashid Ahmad, Byung-Gil Lee, DoHyeun Kim. Composition ship collision risk based on fuzzy theory. Journal of Central South University, 2014, 21(11): 4296-4302 DOI:10.1007/s11771-014-2428-z

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References

[1]

AhnaJ-H, RheeK-P, YouY-jun. A study on the collision avoidance of a ship using neural networks and fuzzy logic [J]. Applied Ocean Research, 2012162-173

[2]

GoodwinE M. A statistical study of ship domains [J]. The Journal of Navigation, 1975, 28(3): 328-344

[3]

XuQ, MengX, WangN. Intelligent evaluation system of ship management [J]. International Journal on Marine Navigation and Safety of Sea Transportation, 2010, 4(4): 479-482

[4]

ShiG-y, JiaC-ying. Algorithms of DCPA, TCPA for marine simulator [J]. Journal of Dalian Maritime University, 1999, 25(3): 17-20

[5]

BukhariA C, TusseyevaI, LeeB-g, KimY-Gi. An intelligent real-time multi-vessel collision risk assessment system from VTS view point based on fuzzy inference system [J]. Expert Systems with Applications, 20131220-1230

[6]

HasegawaK, FukutoJ. An intelligent ship handling simulator with automatic collision avoidance function of target ships [C]. INSLC 17-International Navigation Simulator Lecturers’ Conference. Rostock, Germany, 2012F23-1-10

[7]

FengM-k, LiY-jin. Ship intelligent collision avoidance based on maritime police warships simulation system [C]. IEEE Symposium on Electrical & Electronics Engineering (EEESYM). Kuala Lumpur, Malaysia, 2012293-296

[8]

KoikeT, OkazakiT. Development of ship simulator system for designing auto-pilot [C]. World Automation Congress (WAC). Kobe, Japan, 20101-5

[9]

SuiJ-hua. An AND-OR fuzzy neural network, ant colony optimization-methods and applications [C]. IEEE International Conference on Robotics and Biomimetic. Sanya, China, 20071194-1199

[10]

XueY-z, ClellandD. Automatic simulation of ship navigation [J]. Ocean Engineering, 2011, 38(17/18): 2290-2305

[11]

LiL-n, YangS-h, CaoB-g, LiZ-fu. A summary of studies on the automation of ship collision avoidance intelligence [J]. Journal of Jimei University (Natural Science), 2006, 11(2): 188-192

[12]

HasegawaK. Automatic collision avoidance system for ship using fuzzy control [C]. Proc Eighth Ship Control Systems Symposium (SCSS). The Hague, Netherlands, 198734-58

[13]

FukutoJ, HasegawaK, MiyakeR, YamazakiM. Ship handling simulator for assessing onboard advanced navigation support systems and services [C]. Introduction of Intelligent Ship Handling Simulator, Proc MARSIM 2012, 2012159-166

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