航海智能仿真技术及应用研究综述

doi:10.16182/j.issn1004731x.joss.25-0421

系统仿真学报 ›› 2025, Vol. 37 ›› Issue (7): 1684-1709.doi: 10.16182/j.issn1004731x.joss.25-0421

航海智能仿真技术及应用研究综述

刘涛¹, 李瀚熙¹, 尹勇², 刘佳仑³

^1.上海海事大学，上海 201306
^2.大连海事大学，辽宁大连 116026
^3.武汉理工大学，湖北武汉 430060

收稿日期:2025-05-13 修回日期:2025-06-30 出版日期:2025-07-18 发布日期:2025-07-30
通讯作者: 尹勇
第一作者简介:刘涛 1988年生，上海海事大学教授，博士生导师。专注于海事数字孪生与智能仿真、计算机图形学和人工智能的研究工作，目前研究工作集中于海事场景数字孪生、航海仿真、智能识别等，在国内外知名学术期刊和会议已发表学术论文50余篇，其中包括TITS、ESWA、EAAI、OE、IJDE、JON、Siggraph Asia、CVMJ、CGF等交通和计算机知名期刊和顶会等。担任《系统仿真学报》编委、《Metaverse》青年编委、《交通运输工程学报》青年编委、中国仿真学会多模态交互与认知仿真专委会副主任和秘书、中国图象图形学学会三维视觉专委会委员、中国仿真学会仿真学科建设工委会
刘涛(1988-)，男，教授，博士，研究方向为水上交通数字孪生、智能仿真。
第一联系人：委员等学术职务。
基金资助:
国家自然科学基金(52071201)

Research Review of Intelligent Navigation Simulation Technology and Its Applications

Liu Tao¹, Li Hanxi¹, Yin Yong², Liu Jialun³

^1.Shanghai Maritime University, Shanghai 201306, China
^2.Dalian Maritime University, Dalian 116026, China
^3.Wuhan University of Technology, Wuhan 430060, China

Received:2025-05-13 Revised:2025-06-30 Online:2025-07-18 Published:2025-07-30
Contact: Yin Yong

摘要/Abstract

摘要：

航海仿真通过构建船舶航行环境和行为模型，模拟不同场景下的船舶响应，用于预判复杂干扰条件下的行为特征。随着计算机图形学、虚拟现实和人工智能技术的发展，尤其是无人船技术的发展，航海仿真技术出现了新的研究内容和应用。介绍了航海仿真技术的研究现状和发展趋势，从典型场景、关键技术和发展趋势三方面对航海仿真技术进行研究综述；剖析了多维电子海图、智能电子海图、船舶运动数学模型、航海模拟器等技术的发展趋势和重点；明确了以“数字孪生”和“虚实融合测试验证”技术为重要发展方向的未来航海智能仿真新趋势。关键技术攻关与产品研发是持续推进航海智能仿真技术发展的基础。该研究为航海智能仿真技术的研究与应用提供了系统参考。

关键词: 航海仿真, 电子海图, 船舶运动数学模型, 数字孪生, 虚实融合测试, 航海模拟器

Abstract:

Navigation simulation develops models of ship navigation environments and behavior to simulate ship responses under various scenarios, enabling the prediction of ship behavior under complex and disturbing conditions. With the development of computer graphics, virtual reality, and artificial intelligence technologies in recent years, especially the development of unmanned ship technology, new research topics and applications have emerged in navigation simulation technology. This paper introduced the current research status and development trends of navigation simulation technology and reviewed it from three aspects: typical scenarios, key technologies, and development trends. The development trends and key points of multi-dimensional electronic navigationcharts, intelligent electronic navigationcharts, ship maneuvering mathematical models, navigation simulators, and other technologies were analyzed. The new trend of future intelligent navigation simulation, with "digital twin" and "virtual-real fusion testing and verification" as important development directions, was also clarified. Key technology breakthroughs and product development are the basis for continuously advancing intelligent simulation technology. This paper provides a systematic reference for research and applications in intelligent navigation simulation.

Key words: navigation simulation, electronic navigation chart, ship maneuvering mathematical model, digital twin, virtual-real fusion testing, navigation simulator

中图分类号:

TP391.9

刘涛,李瀚熙,尹勇等 . 航海智能仿真技术及应用研究综述[J]. 系统仿真学报, 2025, 37(7): 1684-1709.

Liu Tao,Li Hanxi,Yin Yong,et al . Research Review of Intelligent Navigation Simulation Technology and Its Applications[J]. Journal of System Simulation, 2025, 37(7): 1684-1709.

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参考文献 122

[1]	Muhammad Wahab Habibi, Jiyane Lindiwe, Özşen Zeynep. Learning Revolution: The Positive Impact of Computer Simulations on Science Achievement in Madrasah Ibtidaiyah[J]. Journal of Educational Technology and Learning Creativity, 2024, 2(1): 13-19.
[2]	Lei Zhengling, Liu Tao, Sun Xiaoming, et al. Extended State Observer Assisted Coulomb Counting Method for Battery State of Charge Estimation[J]. International Journal of Energy Research, 2021, 45(2): 3157-3169.
[3]	严新平, 吴兵, 汪洋, 等. 海事仿真研究现状与发展综述[J]. 系统仿真学报, 2015, 27(1): 13-28, 49.
	Yan Xinping, Wu Bing, Wang Yang, et al. Overview of Development and Current Progress in Maritime Simulation Research[J]. Journal of System Simulation, 2015, 27(1): 13-28, 49.
[4]	中华人民共和国海事局. 交通运输部办公厅关于发布«海港引航员适任培训大纲(2019版)»的通知[EB/OL]. (2019-06-28) [2023-12-20]. .
[5]	IMO. Recommendations on Training and Certification and on Operational Procedures for Maritime Pilots Other Than Deep-sea Pilots[EB/OL]. (2003-12-05) [2021-12-10]. .
[6]	徐言民. 基于操纵模拟的桥区水域船舶通航安全预控研究[D]. 上海: 上海交通大学, 2010.
	Xu Yanmin. Research on Simulation-based Pre-control of Ship Navigation Safety in Bridge Area[D]. Shanghai: Shanghai Jiao Tong University, 2010.
[7]	徐武雄. 基于Multi-agent的内河多桥航道船舶交通流建模与仿真研究[D]. 武汉: 武汉理工大学, 2017.
	Xu Wuxiong. Multi-agent Based Modeling and Simulation of Vessel Traffic Flow in Inland Multi-bridge Waterway[D]. Wuhan: Wuhan University of Technology, 2017.
[8]	Kong Xianwei, Ding Lei, Liu Haicheng, et al. Effects of Water Intake Layout Along the Wharf Shoreline on Ships[J]. Polish Maritime Research, 2019, 26(4): 165-171.
[9]	Yip T L. Port Traffic Risks-A Study of Accidents in Hong Kong Waters[J]. Transportation Research Part E: Logistics and Transportation Review, 2008, 44(5): 921-931.
[10]	Li Yaling, Cheng Zhiyou, Yip T L, et al. Use of HFACS and Bayesian Network for Human and Organizational Factors Analysis of Ship Collision Accidents in the Yangtze River[J]. Maritime Policy & Management, 2022, 49(8): 1169-1183.
[11]	Huang Yamin, Chen Linying, Chen Pengfei, et al. Ship Collision Avoidance Methods: State-of-the-art[J]. Safety Science, 2020, 121: 451-473.
[12]	Zhao Ming, Yao Xufei, Sun Jun, et al. GIS-based Simulation Methodology for Evaluating Ship Encounters Probability to Improve Maritime Traffic Safety[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(1): 323-337.
[13]	杨神化, 施朝健, 刘宇宏, 等. 多agent理论和技术在自动避碰决策系统中的应用[J]. 上海海事大学学报, 2007, 28(1): 121-125.
	Yang Shenhua, Shi Chaojian, Liu Yuhong, et al. Application of Multi-agent System Technology in Decision-making System for Vessel Automatic Anti-collision[J]. Journal of Shanghai Maritime University, 2007, 28(1): 121-125.
[14]	Moser D H K, Heisey S. HarborSym: A Data-driven Monte Carlo Simulation Model of Vessel Movement in Harbors [C]// Proceedings of the 7th International Conference on Hydrodynamics of Marine Systems.Trondheim, Norway: Tapir Academic Press, 2004: 231-244.
[15]	郝世杰, 杨守仁, 方祥麟. 海上交通系统GPSS模拟及应用[J]. 大连海运学院学报, 1986, 12(4): 1-11.
	Hao Shijie, Yang Shouren, Fang Xianglin. Marine Traffic System GPSS Simulation and Application[J]. Journal of Dalian Marine College, 1986, 12(4): 1-11.
[16]	Park Gyei-Kark, Fathi-Vajargah Behrouz, Hong Taeho, et al. Fuzzy Monte Carlo Clustering for Analysing the Distribution of Fishing Vessels in the Coastal Waters of South Korea[J]. International Journal of e-Navigation and Maritime Economy, 2024, 22: 26-33.
[17]	Zheng Fengfan, Jiang Zhonglian, Yu Zhen, et al. Vessel Traffic Flow Simulation: Application of Monte-Carlo Method and RS Analysis[C]//2021 6th International Conference on Transportation Information and Safety (ICTIS). Piscataway: IEEE, 2021: 713-717.
[18]	Qi Le, Ji Yuanyuan, Balling R, et al. A Cellular Automaton-based Model of Ship Traffic Flow in Busy Waterways[J]. The Journal of Navigation, 2021, 74(3): 605-618.
[19]	Liu Jingxian, Liu Yang, Qi Le. Modelling Liquefied Natural Gas Ship Traffic in Port Based on Cellular Automaton and Multi-agent System[J]. The Journal of Navigation, 2021, 74(3): 533-548.
[20]	Numano M, Itoh H, Niwa Y. Sea Traffic Simulation and Its Visualization in Multi-Pc System[C]// Proceedings of the International Congress on Modelling and Simulation (MODSIM 2001). Canberra, Australia: Modelling and Simulation Society of Australia and New Zealand, 2001: 2093-2098.
[21]	杨神化, 施朝健, 关克平, 等. 基于MAS和SHS智能港口交通流模拟系统的开发与应用[J]. 系统仿真学报, 2007, 19(2): 289-292, 299.
	Yang Shenhua, Shi Chaojian, Guan Keping, et al. Intelligent Simulation of Traffic Flow in Port Area with MAS and SHS[J]. Journal of System Simulation, 2007, 19(2): 289-292, 299.
[22]	杨神化. 基于Multi-agent的船舶避碰决策支持系统[D]. 上海: 上海海事大学, 2008.
[23]	Esa J, Jonne P, Mika H, et al. Remote and Autonomous Ships the Next Steps[M]. London: Rolls-Royce-Company, 2016: 2-4.
[24]	Capt Cahit İstikbal. Maritime Autonomous Surface Ships (MASS) and the Future of Maritime Careers and Pilotage [C]// Proceedings of Pilotage/Towage Services and Technologies International Symposium. Istanbul, Turkey: TUDEV Publications, 2017: 1-21.
[25]	Zhang Ji, Hu Chen, Chadha R G, et al. Falco: Fast Likelihood-based Collision Avoidance with Extension to Human-guided Navigation[J]. Journal of Field Robotics, 2020, 37(8): 1300-1313.
[26]	Jiao Jialong, Chen Zhenwei, Chen Shuai, et al. Ship Hydroelasticity Responses in Long-crested Irregular Waves by CFD-FEM Simulation in Comparison with Segmented Model Experiment[J]. Ocean Engineering, 2025, 326: 120886.
[27]	杨晓. 水动力模型驱动下的智能船舶仿真平台研究[D]. 大连: 大连海事大学, 2020.
	Yang Xiao. Research on Simulation Platform of Intelligent Ship Driven by Hydrodynamic Model[D]. Dalian: Dalian Maritime University, 2020.
[28]	杨晓. 基于深度强化学习的船舶避碰算法研究[D]. 哈尔滨: 哈尔滨工程大学, 2023.
	Yang Xiao. Research on Ship Collision Avoidance Decisions Based on Deep Reinforcement Learning[D]. Harbin: Harbin Engineering University, 2023.
[29]	Guo Siyu, Zhang Xiuguo, Zheng Yisong, et al. An Autonomous Path Planning Model for Unmanned Ships Based on Deep Reinforcement Learning[J]. Sensors, 2020, 20(2): 426.
[30]	邹宜洋. 海上多驾驶模式船舶航行安全岸基智慧监管技术研究[D]. 大连: 大连海事大学, 2024.
	Zou Yiyang. Research on Ashore Intelligent Supervision Technology for Navigation Safety of Ships with Multiple Handling Modes at Sea[D]. Dalian: Dalian Maritime University, 2024.
[31]	李永杰, 张瑞, 魏慕恒, 等. 船舶自主航行关键技术研究现状与展望[J]. 中国舰船研究, 2021, 16(1): 32-44.
	Li Yongjie, Zhang Rui, Wei Muheng, et al. State-of-the-art Research and Prospects of Key Technologies for Ship Autonomous Navigation[J]. Chinese Journal of Ship Research, 2021, 16(1): 32-44.
[32]	Yuan Mingyong, Wang Min, Chen Zhenjia, et al. Embedded Marine Target Detection and Positioning Shipboard Terminal Based on Beidou Navigation Satellite System[C]//2024 8th International Conference on Robotics, Control and Automation (ICRCA). Piscataway: IEEE, 2024: 375-379.
[33]	郝江凌, 李超. 电子海图导航系统发展前瞻[J]. 世界海运, 2022, 45(1): 6-9.
[34]	郝江凌, 单雄飞, 赵丽宁, 等. 电子海图导航系统的研究进展与未来趋势[J]. 大连海事大学学报, 2021, 47(3): 1-7.
	Hao Jiangling, Shan Xiongfei, Zhao Lining, et al. Research Progress and Future Trend of Electronic Chart Navigation System[J]. Journal of Dalian Maritime University, 2021, 47(3): 1-7.
[35]	孙和平, 李倩倩, 鲍李峰, 等. 全球海底地形精细建模进展与发展趋势[J]. 武汉大学学报(信息科学版), 2022, 47(10): 1555-1567.
	Sun Heping, Li Qianqian, Bao Lifeng, et al. Progress and Development Trend of Global Refined Seafloor Topography Modeling[J]. Geomatics and Information Science of Wuhan University, 2022, 47(10): 1555-1567.
[36]	MacFerrin M, Amante C, Carignan K, et al. The Earth Topography 2022 (ETOPO 2022) Global DEM Dataset[J]. Earth System Science Data Discussions, 2025, 17(5): 1835-1849.
[37]	Yu Yao, Sandwell D T, Dibarboure Gerald. Abyssal Marine Tectonics from the SWOT Mission[J]. Science, 2024, 386(6727): 1251-1256.
[38]	潘明阳, 刘涛, 董华, 等. 多维数字航道模型研究[J]. 大连海事大学学报, 2013, 39(2): 29-32.
	Pan Mingyang, Liu Tao, Dong Hua, et al. Research on a Multi-dimensional Digital Waterway Model[J]. Journal of Dalian Maritime University, 2013, 39(2): 29-32.
[39]	刘涛, 潘明阳, 王德强. 数字航道空间信息应用技术研究综述[J]. 大连海事大学学报, 2015, 41(3): 59-66.
	Liu Tao, Pan Mingyang, Wang Deqiang. Survey on Spatial Information Application Technology of Digital Waterway[J]. Journal of Dalian Maritime University, 2015, 41(3): 59-66.
[40]	范中洲, 刘大刚, 刘涛, 等. 基于ECDIS的船舶-大风浪区动态显示系统[J]. 大连海事大学学报, 2012, 38(3): 11-14.
	Fan Zhongzhou, Liu Dagang, Liu Tao, et al. Dynamic Display System of Vessel-rough Sea Area Based on ECDIS[J]. Journal of Dalian Maritime University, 2012, 38(3): 11-14.
[41]	Liu Tao, Zhao Depeng, Pan Mingyang. Generating 3D Depiction for a Future ECDIS Based on Digital Earth[J]. The Journal of Navigation, 2014, 67(6): 1049-1068.
[42]	Liu Tao, Zhao Depeng, Pan Mingyang, et al. Fusing Multiscale Charts into 3D ENC Systems Based on Underwater Topography and Remote Sensing Image[J]. Mathematical Problems in Engineering, 2015, 2015(1): 610750.
[43]	Liu Tao, Zhao Depeng, Pan Mingyang. An Approach to 3D Model Fusion in GIS Systems and Its Application in a Future ECDIS[J]. Computers & Geosciences, 2016, 89: 12-20.
[44]	Liu Tao, Wang Shuo, Lei Zhengling, et al. Trajectory Risk Cognition of Ship Collision Accident Based on Fusion of Multi-model Spatial Data[J]. The Journal of Navigation, 2022, 75(2): 299-318.
[45]	Liu Tao, Liu Wanchang, Lei Zhengling, et al. An Approach to Point Cloud and Image Fusion Based on Geometric Features in Water Environment[C]//12th International Conference on Transportation and Traffic Engineering (ICTTE 2023). Piscataway: IEEE, 2023: 140-145.
[46]	范云生, 赵永生, 石林龙, 等. 基于电子海图栅格化的无人水面艇全局路径规划[J]. 中国航海, 2017, 40(1): 47-52, 113.
	Fan Yunsheng, Zhao Yongsheng, Shi Linlong, et al. Global Path Planning for Unmanned Surface Vehicle Based on Grid Model of Electronic Chart[J]. Navigation of China, 2017, 40(1): 47-52, 113.
[47]	Kazimierski Witold, Stateczny Andrzej. Radar and Automatic Identification System Track Fusion in an Electronic Chart Display and Information System[J]. The Journal of Navigation, 2015, 68(6): 1141-1154.
[48]	王胜正, 黄玉贵. 基于电子海图的真实感航海雷达图像仿真方法[J]. 计算机应用, 2014, 34(10): 3024-3028.
	Wang Shengzheng, Huang Yugui. Method of Marine Radar Image Simulation Based on Electronic Chart Display Information System[J]. Journal of Computer Applications, 2014, 34(10): 3024-3028.
[49]	Lin Quanbao, Gou Huaxing, Tian Peidong, et al. RL-based USV Path Planning Under the Marine Multimodal Features Considerations[J]. IEEE Internet of Things Journal, 2025, 12(11): 15274-15287.
[50]	Xue Yanzhuo, Clelland D, Lee B S, et al. Automatic Simulation of Ship Navigation[J]. Ocean Engineering, 2011, 38(17/18): 2290-2305.
[51]	吕红光. 基于电子海图的多船避碰决策及路径规划研究[D]. 大连: 大连海事大学, 2019.
	Hongguang Lü. Research on Multi-ship Collision Avoidance and Path Planning Based on Electronic Chart[D]. Dalian: Dalian Maritime University, 2019.
[52]	吕红光, 尹勇. 基于电子海图矢量数据建模的无人船路径规划[J]. 交通信息与安全, 2019, 37(5): 94-106.
	Hongguang Lü, Yin Yong. Path Planning of Autonomous Ship Based on Electronic Chart Vector Data Modeling[J]. Journal of Transport Information and Safety, 2019, 37(5): 94-106.
[53]	方祥麟, 赵艺声, 谷伟, 等. 基于电子海图技术的海上交通动态模拟[J]. 交通与计算机, 1993(6): 1-5.
	Fang Xianglin, Zhao Yisheng, Gu Wei, et al. Marine Traffic Dynamic Simulation with the Electronic Chart[J]. Computer and Communications, 1993(6): 1-5.
[54]	Hongguang Lü, Yin Yong. Fast Path Planning for Autonomous Ships in Restricted Waters[J]. Applied Sciences, 2018, 8(12): 2592.
[55]	Hongguang Lü, Yin Yong. COLREGS-constrained Real-time Path Planning for Autonomous Ships Using Modified Artificial Potential Fields[J]. The Journal of Navigation, 2019, 72(3): 588-608.
[56]	Lvov Michael S, Popova Halyna V. Simulation Technologies of Virtual Reality Usage in the Training of Future Ship Navigators[J]. Educational Dimension, 2019, 1: 159-180.
[57]	彭修全, 任鸿翔, 于建伟. 回转式甲板克令吊仿真训练系统[J]. 上海海事大学学报, 2018, 39(1): 31-36, 42.
	Peng Xiuquan, Ren Hongxiang, Yu Jianwei. Simulation Training System of Deck Cranes[J]. Journal of Shanghai Maritime University, 2018, 39(1): 31-36, 42.
[58]	彭修全, 任鸿翔, 于建伟. 船用遥控式抓斗的仿真训练系统[J]. 大连海事大学学报, 2019, 45(1): 33-39.
	Peng Xiuquan, Ren Hongxiang, Yu Jianwei. Simulation Training System of Marine Remote Control Grab[J]. Journal of Dalian Maritime University, 2019, 45(1): 33-39.
[59]	陶瑞, 任鸿翔. 基于HTC VIVE的船舶固定水灭火模拟训练系统[J]. 中国航海, 2018, 41(3): 76-80, 90.
	Tao Rui, Ren Hongxiang. Training Simulator for Fixed Water Based Ship Fire Fighting Built on HTC VIVE[J]. Navigation of China, 2018, 41(3): 76-80, 90.
[60]	邱绍杨, 任鸿翔, 尹金岗. 基于虚拟现实技术的自由降落式救生艇培训系统[J]. 大连海事大学学报, 2017, 43(3): 14-18.
	Qiu Shaoyang, Ren Hongxiang, Yin Jingang. A Free Fall Lifeboat Training System Based on Virtual Reality Technology[J]. Journal of Dalian Maritime University, 2017, 43(3): 14-18.
[61]	邱绍杨, 任鸿翔, 尹金岗. 基于虚拟现实技术的船舶救生培训系统[J]. 中国航海, 2018, 41(2): 68-72, 96.
	Qiu Shaoyang, Ren Hongxiang, Yin Jingang. Marine Life-saving Training System Based on Virtual Reality Technology[J]. Navigation of China, 2018, 41(2): 68-72, 96.
[62]	孙佳文, 任鸿翔, 肖方兵, 等. 基于虚拟现实的整船仿真训练平台[J]. 系统仿真学报, 2021, 33(9): 2243-2251.
	Sun Jiawen, Ren Hongxiang, Xiao Fangbing, et al. Whole Ship Simulation Training Platform Based on Virtual Reality[J]. Journal of System Simulation, 2021, 33(9): 2243-2251.
[63]	Li Fang, Huang Luofeng. A Review of Computational Simulation Methods for a Ship Advancing in Broken Ice[J]. Journal of Marine Science and Engineering, 2022, 10(2): 165.
[64]	Nie Yunli, Luan Xin, Gan Wenhao, et al. Design of Marine Virtual Simulation Experiment Platform Based on Unity3D[C]//Global Oceans 2020: Singapore – U.S. Gulf Coast. Piscataway: IEEE, 2020: 1-5.
[65]	Aylward Katie, Dahlman Joakim, Nordby Kjetil, et al. Using Operational Scenarios in a Virtual Reality Enhanced Design Process[J]. Education Sciences, 2021, 11(8): 448.
[66]	张秀凤, 王晓雪, 孟耀, 等. 船舶运动建模与仿真研究进展及未来发展趋势[J]. 大连海事大学学报, 2021, 47(1): 1-8.
	Zhang Xiufeng, Wang Xiaoxue, Meng Yao, et al. Research Progress and Future Development Trend of Ship Motion Modeling and Simulation[J]. Journal of Dalian Maritime University, 2021, 47(1): 1-8.
[67]	Nomoto Kensaku, Taguchi Kenshi, Honda Keinosuke, et al. On the Steering Qualities of Ships[J]. Journal of Zosen Kiokai, 1956, 1956(99): 75-82.
[68]	Abkowitz M A. Lectures on Ship Hydrodynamics-Steering and Manoeuvrability [EB/OL]. Copenhagen: Hydro-og Aerodynamisk Laboratorium. (2024-07-21)[2025-05-12]..
[69]	Norrbin N H. Theory and Observation on the Use of Amathematical Model for Ship Maneuvering in Deep and Confined Waters [C]// Proceedings of the 8th Symposium on Naval Hydrodynamics.Pasadena, USA: National Academy of Sciences Press, 1970: 317-376.
[70]	Ogawa A, Kasai H. On the Mathematical Model of Manoeuvring Motion of Ships[J]. International Shipbuilding Progress, 1978, 25(292): 306-319.
[71]	葛西宏直, 湯室彰規. MMG報告-III 舵に作用するカと船体・プロペラとの干渉[J]. 日本造船学会誌, 1977, 578: 358-372.
[72]	小川陽弘. 操縦運動の数学モデルの基礎[J]. 第 3回操縦性シンポジウム, 1981,3: 9-26.
[73]	Kose K. On a New Mathematical Model of Maneuvering Motions of a Ship and Its Applications[J]. International Shipbuilding Progress, 1982, 29(336): 205-220.
[74]	徐东星, 张秀凤, 刘春雷, 等. 大型LNG船舶四自由度运动建模与仿真[J]. 上海船舶运输科学研究所学报, 2015, 38(3): 15-19.
	Xu Dongxing, Zhang Xiufeng, Liu Chunlei, et al. 4-DOF Modeling and Simulation of Large LNG Ship[J]. Journal of Shanghai Ship and Shipping Research Institute, 2015, 38(3): 15-19.
[75]	曹强, 张建云, 向柱强, 等. 交互式拖轮拖带与顶推作业建模仿真[J]. 计算机仿真, 2020, 37(6): 187-190.
	Cao Qiang, Zhang Jianyun, Xiang Zhuqiang, et al. Modeling and Simulation of Tug Pushing and Pulling Operations[J]. Computer Simulation, 2020, 37(6): 187-190.
[76]	孙霄峰, 尹勇, 张秀凤. 可调螺距螺旋桨船舶的操纵运动数学模型[J]. 大连海事大学学报, 2007, 33(4): 73-76.
	Sun Xiaofeng, Yin Yong, Zhang Xiufeng. Maneuvering Mathematical Model for Ships Equipped with Controllable Pitch Propeller[J]. Journal of Dalian Maritime University, 2007, 33(4): 73-76.
[77]	张秀凤, 金一丞, 尹勇. 航海模拟器中船舶平旋推进器的数学模型[J]. 中国航海, 2010, 33(2): 27-30.
	Zhang Xiufeng, Jin Yicheng, Yin Yong. Mathematical Model of Voith Schneider Propeller in Ship Handling Simulator[J]. Navigation of China, 2010, 33(2): 27-30.
[78]	吴兴亚, 高霄鹏. 全回转双桨船舶操纵性预报[J]. 中国舰船研究, 2017, 12(1): 27-31, 62.
	Wu Xingya, Gao Xiaopeng. Maneuverability Prediction for a Ship with Full-revolving Twin Propellers[J]. Chinese Journal of Ship Research, 2017, 12(1): 27-31, 62.
[79]	张秀凤, 尹勇, 孙霄峰, 等. 吊舱推进船舶运动数学模型及其在航海模拟器中的应用[J]. 大连海事大学学报, 2013, 39(2): 9-12, 17.
	Zhang Xiufeng, Yin Yong, Sun Xiaofeng, et al. Ship Mathematical Model with POD Propellers Applied in Marine Simulator[J]. Journal of Dalian Maritime University, 2013, 39(2): 9-12, 17.
[80]	王建华, 万德成. 船舶操纵运动CFD数值模拟研究进展[J]. 哈尔滨工程大学学报, 2018, 39(5): 813-824.
	Wang Jianhua, Wan Decheng. CFD Simulations of Ship Maneuvering Motion[J]. Journal of Harbin Engineering University, 2018, 39(5): 813-824.
[81]	Phillips A B, Turnock S R, Furlong M. Accurate Capture of Propeller-rudder Interaction Using a Coupled Blade Element Momentum-RANS Approach[J]. Ship Technology Research, 2010, 57(2): 128-139.
[82]	Carrica P M, Ismail Farzad, Hyman M, et al. Turn and Zigzag Maneuvers of a Surface Combatant Using a URANS Approach with Dynamic Overset Grids[J]. Journal of Marine Science and Technology, 2013, 18(2): 166-181.
[83]	Carrica P M. DES Simulations of KVLCC1 in Turn and Zigzag Maneuvers with Moving Propeller and Rudder [C]// Proceedings of SIMMAN 2008 Workshop on Verification and Validation of Ship Maneuvering Simulation Methods. Lyngby, Denmark: Department of Naval Architecture and Offshore Engineering, Technical University of Denmark, 2008: 8.1-8.15.
[84]	Mofidi A, Carrica P M. Simulations of Zigzag Maneuvers for a Container Ship with Direct Moving Rudder and Propeller[J]. Computers & Fluids, 2014, 96: 191-203.
[85]	Shen Zhirong, Wan Decheng, Carrica P M. Dynamic Overset Grids in OpenFOAM with Application to KCS Self-propulsion and Maneuvering[J]. Ocean Engineering, 2015, 108: 287-306.
[86]	Carrica P M, Mofidi A, Eloot Katrien, et al. Direct Simulation and Experimental Study of Zigzag Maneuver of KCS in Shallow Water[J]. Ocean Engineering, 2016, 112: 117-133.
[87]	Maritime Kongsberg. K-Sim® Navigation[EB/OL]. [2025-04-20]. .
[88]	Wärtsilä. Simulation and Training[EB/OL]. [2025-04-20]. .
[89]	王胜正, 施朝健, 石永辉, 等. 360°环形柱幕立体视景系统航海模拟器[J]. 上海海事大学学报, 2008, 29(2): 1-6.
	Wang Shengzheng, Shi Chaojian, Shi Yonghui, et al. Navigation Simulator with 360° Cylindrical Stereo Visual System[J]. Journal of Shanghai Maritime University, 2008, 29(2): 1-6.
[90]	翟小明, 尹勇, 任鸿翔. 内河船舶操纵模拟器视景系统的建模与仿真[J]. 重庆交通大学学报(自然科学版), 2018, 37(5): 112-117.
	Zhai Xiaoming, Yin Yong, Ren Hongxiang. Modeling and Simulation of Visual System in Inland River Ship Handling Simulator[J]. Journal of Chongqing Jiaotong University(Natural Science), 2018, 37(5): 112-117.
[91]	Ke Jinding. The Use of Stereoscopic Display Technology under Human-computer Interaction in Navigation Simulator[C]//2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC). Piscataway: IEEE, 2021: 617-620.
[92]	李海江, 任鸿翔, 邱绍杨. 基于物理的海洋场景模拟技术综述[J]. 大连海事大学学报, 2019, 45(1): 47-65.
	Li Haijiang, Ren Hongxiang, Qiu Shaoyang. A Survey of Physically-based Ocean Scene Simulation[J]. Journal of Dalian Maritime University, 2019, 45(1): 47-65.
[93]	Müller Matthias, Solenthaler Barbara, Keiser Richard, et al. Particle-based Fluid-fluid Interaction[C]//Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. New York: ACM, 2005: 237-244.
[94]	Becker Markus, Teschner Matthias. Weakly Compressible SPH for Free Surface Flows[C]//Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. Goslar: Eurographics Association, 2007: 209-217.
[95]	Akinci Nadir, Ihmsen Markus, Akinci Gizem, et al. Versatile Rigid-fluid Coupling for Incompressible SPH[J]. ACM Transactions on Graphics, 2012, 31(4): 62.
[96]	He Xiaowei, Liu Ning, Li Sheng, et al. Local Poisson SPH for Viscous Incompressible Fluids[J]. Computer Graphics Forum, 2012, 31(6): 1948-1958.
[97]	Bender Jan, Dan Koschier. Divergence-free Smoothed Particle Hydrodynamics[C]//Proceedings of the 14th ACM SIGGRAPH / Eurographics Symposium on Computer Animation. New York: ACM, 2015: 147-155.
[98]	李海江. 航海模拟器中基于物理模型的海洋场景建模[D]. 大连: 大连海事大学, 2020.
	Li Haijiang. Physical Model-based Ocean Scene Modeling in Marine Simulator[D]. Dalian: Dalian Maritime University, 2020.
[99]	王一丁, 任鸿翔, 李海江, 等. 船舶操纵模拟器中基于SPH的流固耦合模拟[J]. 计算机仿真, 2025, 42(1): 219-223.
	Wang Yiding, Ren Hongxiang, Li Haijiang, et al. Fluid-rigid Interaction Simulation Based on SPH in Ship Maneuvering Simulator[J]. Computer Simulation, 2025, 42(1): 219-223.
[100]	江玉玲, 彭国均. 航海模拟器中船舶数学模型仿真研究[J]. 实验室研究与探索, 2016, 35(3): 24-27, 31.
	Jiang Yuling, Peng Guojun. Mathematical Model Simulation of Ship Navigation Simulator[J]. Research and Exploration in Laboratory, 2016, 35(3): 24-27, 31.
[101]	杨鹏. 船舶六自由度运动模拟台及其控制方法研究[D]. 哈尔滨: 哈尔滨工程大学, 2007.
	Yang Peng. Research of Ship Six Degrees of Freedom Motion Simulation Platform and Its Control Method[D]. Harbin: Harbin Engineering University, 2007.
[102]	Wang Yufei, Sun Xiaofeng, Shen Helong, et al. Research on Improvement and Optimization of Washout Algorithm for Moving Platform Navigation Simulator[C]//2021 IEEE 7th International Conference on Virtual Reality (ICVR). Piscataway: IEEE, 2021: 400-406.
[103]	聂蓉梅, 周潇雅, 肖进, 等. 数字孪生技术综述分析与发展展望[J]. 宇航总体技术, 2022, 6(1): 1-6.
	Nie Rongmei, Zhou Xiaoya, Xiao Jin, et al. Analysis and Perspective on Digital Twin Technology[J]. Astronautical Systems Engineering Technology, 2022, 6(1): 1-6.
[104]	杨少龙, 孙延浩, 向先波, 等. 船舶数字孪生及其服务全生命周期研究综述[J]. 舰船科学技术, 2020, 42(21): 1-8.
	Yang Shaolong, Sun Yanhao, Xiang Xianbo, et al. Ship Digital Twin and a Review of Life-cycle Service[J]. Ship Science and Technology, 2020, 42(21): 1-8.
[105]	李澳, 徐言民, 关宏旭, 等. 基于数字孪生的测试场景架构及应用研究[J]. 舰船科学技术, 2023, 45(24): 171-175.
	Li Ao, Xu Yanmin, Guan Hongxu, et al. Digital Twin-based Test Scenario Architecture and Application Research[J]. Ship Science and Technology, 2023, 45(24): 171-175.
[106]	张立尧, 郭梓芊, 李瑞芳, 等. 基于数字孪生与改进KD树算法的船舶运维知识推理与策略优化[J]. 中国舰船研究, 2025, 20(2): 118-130.
	Zhang Liyao, Guo Ziqian, Li Ruifang, et al. Knowledge Reasoning and Strategy Optimization for Ship Operation and Maintenance Based on Digital Twin and Improved KD Tree Algorithm[J]. Chinese Journal of Ship Research, 2025, 20(2): 118-130.
[107]	Wu Wenhao, Chen Guobing and Yang Zichun. The Application and Challenge of Digital Twin Technology in Ship Equipment[C]//Journal of Physics: Conference Series. Bristol: IOP Publishing, 2021: 012068.
[108]	王凯, 刘兴, 徐浩, 等. 数据驱动的船舶能效三维动态仿真与虚实融合验证方法[J]. 中国航海, 2024, 47(4): 190-197.
	Wang Kai, Liu Xing, Xu Hao, et al. Data-driven Three-dimensional Dynamic Simulation and Virtual-reality Fusion Verification Method of Ship Energy Efficiency[J]. Navigation of China, 2024, 47(4): 190-197.
[109]	Coraddu A, Oneto Luca, Baldi Francesco, et al. Data-driven Ship Digital Twin for Estimating the Speed Loss Caused by the Marine Fouling[J]. Ocean Engineering, 2019, 186: 106063.
[110]	Liu M, Zhou Q, Wang X, et al. Voyage Performance Evaluation Based on a Digital Twin Model[C]//IOP Conference Series: Materials Science and Engineering. Bristol: IOP Publishing, 2020: 012027.
[111]	Liu Tao, Geng Shiqi, Fu Yucheng, et al. Triplane Generator-based NeRF-GAN Framework for Single-view Ship Reconstruction[J]. International Journal of Digital Earth, 2025, 18(1): 2496406.
[112]	Liu Tao, Shen Ruiqi, Lei Zhengling, et al. Wind Resistance Aerial Path Planning for Efficient Reconstruction of Offshore Ship[J]. International Journal of Digital Earth, 2022, 15(1): 1881-1904.
[113]	Liu Tao, Jia Zi, Lei Zhengling, et al. Unsupervised Depth Estimation for Ship Target Based on Single View UAV Image[J]. International Journal of Remote Sensing, 2022, 43(9): 3216-3235.
[114]	杨帆, 刘佳仑, 于淳, 等. 虚实融合的船舶智能航行测试技术[J]. 中国航海, 2022, 45(3): 113-122.
	Yang Fan, Liu Jialun, Yu Chun, et al. Test Technology for Intelligent Navigation with Mix of Virtual and Actual Reality[J]. Navigation of China, 2022, 45(3): 113-122.
[115]	胡一鹏, 闫昭琨, 刘佳仑, 等. 智能船艇虚实融合测试验证技术现状与展望[J]. 船舶工程, 2022, 44(4): 4-13.
[116]	Huang Yi, Wang Hongdong, Ma Jilin, et al. Research and Practical Exploration of Test and Validation Technologies Applied on Unmanned Surface Vehicle Optical Recognition[C]//2021 IEEE International Conference on Unmanned Systems (ICUS). Piscataway: IEEE, 2021: 976-981.
[117]	Liu Jialun, Yang Fan, Li Shijie, et al. Testing and Evaluation for Intelligent Navigation of Ships: Current Status, Possible Solutions, and Challenges[J]. Ocean Engineering, 2024, 295: 116969.
[118]	Yang Fan, Liu Jialun, Li Shijie, et al. Virtual-real Interaction Tests for Functional Testing of Smart Ships[C]// Proceedings of the 30th International Ocean and Polar Engineering Conference (ISOPE 2020). Golden, USA: International Society of Offshore and Polar Engineers, 2020: 194-200.
[119]	刘佳仑, 杨帆, 谢玲利, 等. 面向智能航行避碰决策与规划的虚拟仿真测试技术研究[J]. 系统仿真学报, 2024, 36(8): 1780-1789.
	Liu Jialun, Yang Fan, Xie Lingli, et al. Research on Virtual Simulation Testing Technology for Intelligent Navigation Collision Avoidance Decision-making and Planning[J]. Journal of System Simulation, 2024, 36(8): 1780-1789.
[120]	Bakdi Azzeddine, Ingrid Kristine Glad, Vanem Erik. Testbed Scenario Design Exploiting Traffic Big Data for Autonomous Ship Trials Under Multiple Conflicts with Collision/Grounding Risks and Spatio-temporal Dependencies[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(12): 7914-7930.
[121]	Bolbot V, Gkerekos C, Theotokatos G, et al. Automatic Traffic Scenarios Generation for Autonomous Ships Collision Avoidance System Testing[J]. Ocean Engineering, 2022, 254: 111309.
[122]	Wang Weiqiang, Huang Liwen, Liu Kezhong, et al. Ship Encounter Scenario Generation for Collision Avoidance Algorithm Testing Based on AIS Data[J]. Ocean Engineering, 2024, 291: 116436.

建模方法	优点	缺点
蒙特卡罗建模仿真	解决多级排队模型的解析值求解困难问题；比较真实地描述系统的运行、演变及其发展过程	随机数的质量严重影响了船舶交通流仿真的精度，需要复杂的选择随机数流程
元胞自动机仿真	以简单演化规则模拟复杂的非线性交通现象，易于编程、计算	对航速、船舶长度做了整数倍的近似化处理，船舶轨迹位置离散化，对内河小范围的仿真其误差比较大
多智能体仿真	基于个体特征和行为模拟个体间相互独立又交互作用的现象；基于每个智能体自身的适应性和进化性，可以适应突发情况	体系结构、编程语言和开发工具等方面还没有统一的规范，模型的实现非常复杂；多个 Agent 的运行需要复杂的计算

探测技术	优点	缺点
多波束声纳测深	探测精度高；可达米级、技术成熟；应用广泛	探测效率较低、成本较高
机载激光雷达测深	探测精度高；可达米级；探测覆盖范围广泛	受限于物理条件，目前只能对近海浅水水域进行测绘
卫星测高重力数据反演技术	探测覆盖范围广；覆盖全球；分辨率达到1'×1'	重力数据仅对大尺度的地形起伏变化敏感，且精度依赖于先验信息

项目	版本	数据来源	精度
ETOPO	ETOPO2	卫星重力反演数据、多波束声纳	2'×2'
	ETOPO2V2	卫星重力反演数据、多波束声纳	2'×2'
	ETOPO1	卫星重力反演数据、多波束声纳	1'×1'
	ETOPO2022	激光雷达卫星重力反演数据、多波束声纳	15''
SRTM	SRTM30+	单/双波束声纳、卫星重力反演数据	2'×2'
	SRTM15+V1.0		1'×1'
	SRTM15+V2.0		15''×15''
SWOT	SWOT	卫星重力反演数据、天基雷达测高	4.3'×4.3'

特性	传统APF	改进APF(如PGHAPF)
动态适应性	支持移动障碍物	增强突发机动应对能力
路径质量	可能振荡/不平滑	平滑且符合运动学约束
缺陷解决	易陷入局部极小值/GNRON/规则缺失	通过混合策略与规则嵌入得以大幅缓解
环境建模	简化障碍物(点/凸多边形)	支持任意形状(矢量电子海图集成)

模型类型	核心思想	优点	缺点
响应式模型	舵角到运动响应(黑箱)	简单、参数少、易辨识、计算快	物理意义不清、适用范围窄、无法预测细节
MMG模型	船体+桨+舵+干扰 (模块叠加)	物理清晰、模块化、适用范围广、可析因	较复杂、参数获取难(需试验/CFD)、计算量大
整体型模型	全局泰勒展开 (整体函数)	理论基础严谨、理论完整	参数极多、辨识极其困难、物理不直观、结构复杂

航海智能仿真技术及应用研究综述

Research Review of Intelligent Navigation Simulation Technology and Its Applications

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