Journal is indexed in following databases:

2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7




ISSN 2083-6473
ISSN 2083-6481 (electronic version)




Associate Editor
Prof. Tomasz Neumann

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
Ship Collision Avoidance Decision Model and Simulation Based on Collision Circle
1 Shanghai Maritime University, Shanghai, China
2 COSCO Shipping Seafarer Manangement CO, LTD, Shanghai, China
Times cited (SCOPUS): 5
ABSTRACT: In order to give consideration to both comprehensive evaluation and efficient decision-making in collision avoidance decision-making process, a collision avoidance decision-making model based on collision circle is proposed by introducing the concept of collision circle. Firstly, the factors causing ship collision are analyzed. Secondly, the static and dynamic characteristics of collision circles are analyzed and summarized by using collision circle simulation cases. Thirdly, based on the static characteristics, a reasonably distributed collision avoidance decision model of (Possible Point of Collision,PPC) was established. Finally, the spatial data operations core algorithm (Java Topology Suite, JTS) is used for logical operation and visualization, so as to realize the ship collision avoidance evaluation and decision. The decision model was used to verify the accident scenario of "SANCHI", and the results showed that the obtained collision avoidance scheme was reasonable and in line with the "International Regulations for Preventing Collisions at Sea" and safety requirements, thus providing a reference for maritime operators to avoid collisions between ships.
Huang Ying, Li Lina, Chen guoquan. Design and application of decision support module for collision avoidance of urgent danger [J]. Journal of jimei university: natural science edition, 2011, 16(6).
Wu Zhaolin. Selection of collision avoidance actions based on PAD information and improvement of PAD graphics [J]. Journal of dalian maritime university, 1986(4):16-26.
Fang Xianglin, Fu Wanxuan. Danger zone model for velocity ratio circle prediction and its application in ARPA system [J]. China maritime, 1984(2):5-17.
Wang Renqiang, Zhao Yuelin, Xie Baofeng. Mathematical model of collision avoidance in ship dynamic steering [J]. Journal of dalian maritime university, 2014, 40(1):17-20.
He Yixiong, Huang Liwen, Mou Junmin, et al. Automatic collision avoidance action plan for give-way vessels in cross-encounter situation [J]. Journal of Harbin engineering university, 2015(08):1024-1029.
Xiong Yong, He Yixiong, Huang Liwen. Multi-ship automatic collision avoidance control method based on speed obstacle [J]. China maritime, 2015, 38(3).
Chen Yaojie, Li Shuang, Fan Huan, et al. Research on multi-ship automatic collision avoidance based on velocity vector coordinate system [J]. Computer simulation,2015,32(6):420-424.
Liao Bingjun. Introduction to safety situation diagram avoidance method [J]. Navigation technology,2018.
Hu Shenping. Classification and quantification of collision avoidance stage in ship encounter process [J]. China maritime industry, 2001(2):83-87.
Hu Qiaoer, Hu Qinyou. Design and analysis of ship collision avoidance simulation system based on negotiation [J]. China maritime, 2009, 32(1):54-59.
You Y, Rhee K. Development of the collision ratio to infer the time at which to begin a collision avoidance of a ship[J]. Applied Ocean Research, 2016, 60:164-175. - doi:10.1016/j.apor.2016.09.005
Ma Wenyao, Wu Zhaolin, Yang Jiaxuan, et al. Decision support for collision avoidance path planning of artificial fish swarm algorithm [J]. China maritime, 2014, 37(3):63-67.
Ni Shengke, Liu Zhengjiang, Cai Yao, et al. Collision avoidance decision support for ships based on genetic algorithm [J]. Journal of Shanghai maritime university, 2017(1).
Yu Jiagen, Liu Zhengjiang, Bu Renxiang, et al. Collision avoidance decision of ship steering based on simulation physics optimization algorithm [J]. China maritime, 2016, 39(1):36-38.
Yang Baicheng, Zhao Zhilei. Multi-ship collision avoidance decision based on improved simulated annealing algorithm [J]. Journal of dalian maritime university, 2018, 44(2).
Wang Deyan, liu Yian. Application of particle swarm optimization in multi-ship collision avoidance decision [J]. Computer engineering and design, 2009, 30(14):3380-3382.
Shen Haiqing, Guo Chen, Li Tieshan, et al. Intelligent collision avoidance navigation method for unmanned ships considering rules of navigation experience [J]. Journal of Harbin engineering university, 2018, 260(06):48-55.
Huang Y, P. H. A. J. M. van Gelder, Wen Y. Velocity obstacle algorithms for collision prevention at sea[J]. Ocean Engineering, 2018, 151:308-321. - doi:10.1016/j.oceaneng.2018.01.001
Liu Renwei, Xue Yanzhuo, Liu Yang, et al. Automatic collision avoidance model and its application in restricted waters [J]. Journal of Harbin Institute of Technology, 2018(3).
Li Lina, Xiong Zhennan, Gao Yansong, et al. Generation and optimization method of single ship collision avoidance intelligent decision [J]. Information and control, 2002, 32(2):189-192.
LAZAROWSKA A. Ant Colony Optimization based Navigational Decision Support System [J]. Procedia Computer Science, 2014, 35:1013-1022. - doi:10.1016/j.procs.2014.08.187
Zhao jin-song, wang feng-chen, et al. Collision and collision avoidance rules. Dalian maritime university press, 1997.
Citation note:
Zhang J.F., Hu Q., Liao B.J.: Ship Collision Avoidance Decision Model and Simulation Based on Collision Circle. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 13, No. 2, doi:10.12716/1001.13.02.08, pp. 325-334, 2019

Other publications of authors:

File downloaded 551 times

Important: cookie usage
The website uses certain cookies. A cookie is a text-only string of information that the TransNav.EU website transfers to the cookie file of the browser on your computer. Cookies allow the website to perform properly and remember your browsing history. Cookies also help a website to arrange content to match your preferred interests more quickly. Cookies alone cannot be used to identify you.
AkceptujÄ™ pliki cookies z tej strony