Benjamin, M. Curcio, J. and Newman, P. (2006). Navigation of unmanned marine vehicles in accordance with the rules of the road, Proceedings of the IEEE International Conference on Robotics and Automation, Orlando, FL, USA, Vol. 70, pp. 3581–3587.10.1109/ROBOT.2006.1642249
Campbell, S. Naeem, W. and Irwin, G.W. (2002). A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance maneuvers, Annual Reviews in Control36(2): 267–283.10.1016/j.arcontrol.2012.09.008
Erol, S. Demir, M.E.B. and Eyüboǧlu, E. (2018). Analysis of ship accidents in the Istanbul strait using neuro-fuzzy and genetically optimized fuzzy classifiers, The Journal of Navigation71(2): 419–436.10.1017/S0373463317000601
Fossen, T.I. and Johansen, T.A. (2006). A survey of control allocation methods for ships and underwater vehicles, Proceedings of the 14th Mediterranean Conference on Control and Automation, Ancona, Italy, pp. 1–6.10.1109/MED.2006.328749
Kim, D. Hirayama, K. and Okimoto, T. (2017). Distributed stochastic search algorithm for multi-ship encounter situations, The Journal of Navigation70(4): 699–718.10.1017/S037346331700008X
Kvasov, D.E. and Mukhametzhanov, M. (2018). Metaheuristic vs. deterministic global optimization algorithms: The univariate case, Applied Mathematics and Computation318(1): 245–259.10.1016/j.amc.2017.05.014
Lazarowska, A. (2015). Ships trajectory planning for collision avoidance at sea based on ant colony optimization, The Journal of Navigation68(2): 291–307.10.1017/S0373463314000708
Liu, Y.H. and Shi, C.J. (2005). A fuzzy-neural inference network for ship collision avoidance, Proceedings of the International Conference on Machine Learning and Cybernetics, Guangzhou, China, pp. 4754–4759.
Mattingley, J. and Boyd, S. (2010). Real-time convex optimization in signal processing: Recent advances that make it easier to design and implement algorithms, IEEE Signal Processing Magazine27(3): 35–49.10.1109/MSP.2010.936020
Perera, L.P. Carvalho, J.P. and Soares, C.G. (2011). Fuzzy logic based decision-making system for collision avoidance of ocean navigation under critical collision conditions, Journal of Marine Science and Technology6(1): 84–99.10.1007/s00773-010-0106-x
Skjetne, R. Fossen, T.I. and Kokotovic, P.V. (2005). Adaptive maneuvering, with experiments, for a model ship in marine control laboratory, Automatica41(2): 289–298.10.1016/j.automatica.2004.10.006
Statheros, T. Howells, G. and Maier, K.M. (2008). Autonomous ship collision avoidance navigation concepts, technologies and techniques, The Journal of Navigation61(1): 129–142.10.1017/S037346330700447X
Wang, T. F. Yan, X.P. and Wang, Y. (2017). Ship domain model for multi-ship collision avoidance decision making with colregs based on artificial potential field, International Journal on Maritime Navigation and Safety of Sea Transportation11(1): 85–92.10.12716/1001.11.01.09
Xu, Q. Zhang, C. and Wang, N. (2014). Multi-objective optimization based vessel collision avoidance strategy optimization, Mathematical Problems in Engineering2014: 1–9.10.1155/2014/914689
Zhang, L. Lin, S., Zhou, J. and Papavassiliou, C. (2017). Three-dimensional underwater path planning based on modified wolf pack algorithm, IEEE Access5: 22783–22795.10.1109/ACCESS.2017.2765504