[1]Guan W, Peng H W, Zhang X K, et al. Ship Steering Adaptive CGS Control Based on EKF Identification Method[J]. Journal of Marine Science and Engineering, 2022, 10(2).
[2]Cheng X, Liu Z Y, Soc I C. Trajectory optimization for ship navigation safety using genetic annealing algorithm[C]//3rd International Conference on Natural Computation (ICNC 2007), 2007: 385．
[3]Phanthong T, Maki T, Ura T, et al. Application of A* algorithm for real-time path re-planning of an unmanned surface vehicle avoiding underwater obstacles[J]. Journal of Marine Science of Application, 2014, 13(1): 12．
[4]Liu X Y, Li Y, Zhang J, et al. Self-Adaptive Dynamic Obstacle Avoidance and Path Planning for USV Under Complex Maritime Environment[J]. IEEE Access, 2019, 7: 114945-114954．
[5]吕红光，尹 勇，尹建川. 混合智能系统在船舶自动避碰决策中的应用[J]. 大连海事大学学报， 2015, 41(4): 29-36.
LV Hong-guang,YIN Yong,YIN Jian-chuan. Application of hybrid intelligent systems in automatic collision avoidance decision-making for ships[J]. Journal of Dalian Maritime University, 2015, 41(4): 29-36. (in Chinese)
[6]苗鹏，刘克中，辛旭日，陈逸涵，吴晓烈. 基于改进NSGA-Ⅱ的船舶避碰决策辅助算法[J]. 大连海事大学学报， 2021, 47(4): 10-18.
MIAO Peng，LIU Ke-zhong，XIN Xu-ri,CHEN Yi-han，WU Xiao-lie. Ship collision avoidance decision aids based on improved NSGA-Ⅱ[J]. Journal of Dalian Maritime University, 2021, 47(4): 10-18. (in Chinese)
[7]宁君, 黄寓旸, 尤恽, 李伟, 高鉴一, 张帅. 基于混合粒子群算法的船舶避碰决策[J]. 大连海事大学学报， 2023, 49(1): 34-43.
NING Jun, HUANG Yuyang, YOU Yun, LI Wei, GAO Jianyi, ZHANG Shuai. Ship collision avoidance decision based on hybrid particle swarm algorithm[J]. Journal of Dalian Maritime University, 2023, 49(1): 34-43. (in Chinese)
[8]杨柏丞,赵志垒. 基于改进模拟退火算法的多船会遇避碰决策[J].大连海事大学学报,2018,44(2):22-26.
YANG B C, ZHAO Z L. Multi-ship encounter collision avoidance decisions based on improved simulated annealing algorithm [J]. Journal of Dalian Maritime University, 2018,44(2):22-26. (in Chinese)
[9]Shen H, Hashimoto H, Matsuda A, et al. Automatic collision avoidance of multiple ships based on deep Q-learning[J]. Applied Ocean Research, 2019, 86: 268-288.
[10]Xu X L, Lu Y, Liu X C, et al. Intelligent collision avoidance algorithms for USVs via deep reinforcement learning under COLREGs[J]. Ocean Engineering, 2020, 217.
[11]Sawada R, Sato K, Majima T. Automatic ship collision avoidance using deep reinforcement learning with LSTM in continuous action spaces[J]. Journal of Marine Science and Technology, 2021, 26(2): 509-524.
[12]Guo S Y, Zhang X G, Zheng Y S, et al. An Autonomous Path Planning Model for Unmanned Ships Based on Deep Reinforcement Learning[J]. Sensors,2020, 20(2):426.
[13]T. I. Fossen, Handbook of Marine Craft Hydrodynamics and Motion Control: Handbook of Marine Craft Hydrodynamics and Motion Control, 2011.
[14]Śmierzchalski R. Ships' domains as collision risk at sea in the evolutionary method of trajectory planning[J], In: Saeed, K., Pejaś, J. (eds) Information Processing and Security Systems. Springer, Boston, MA, 2015.
[15]Schulman, J.; Wolski, F.; Dhariwal, P.; Radford, A.; Klimov, O., Proximal Policy Optimization Algorithms. [J] Computer science, 2017.
[16]Guan W, Cui Z, Zhang X. Intelligent Smart Marine Autonomous Surface Ship Decision System Based on Improved PPO Algorithm[J]. Sensors, 2022, 22(15): 5732.
[17]Cui Z, Guan W, Luo W. Intelligent Ship Decision System Based on DDPG Algorithm[J]. 2022 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI), 2022: 700-705.
[18]B. Bingham, C. Aguero, M. Mccarrin et al., "Toward Maritime Robotic Simulation in Gazebo." MTS/IEEE OCEANS Conference, Oct, 2019.
