智能船舶的研究现状可视化分析与发展趋势

张笛; 赵银祥; 崔一帆; 万程鹏

doi:10.3963/j.jssn.1674-4861.2021.01.002

智能船舶的研究现状可视化分析与发展趋势

doi: 10.3963/j.jssn.1674-4861.2021.01.002

张笛^{1, 2,},
赵银祥^{1, 2},
崔一帆³,
万程鹏^{1, 2, ,}

1.
武汉理工大学智能交通系统研究中心武汉 430063
2.
武汉理工大学国家水运安全工程技术研究中心武汉 430063
3.
武汉理工大学航运学院武汉 430063

基金项目:

国家重点研发计划项目 2019YFB1600601

国家自然科学基金重点国际(地区)合作研究项目 51920105014

湖北省自然科学基金项目 2019CFA039

湖北省自然科学基金项目 2020CFB691

详细信息

作者简介:
张笛（1983—）博士，研究员.研究方向：水路运输风险管理.E-mail: zhangdi@whut.edu.cn

通讯作者:
万程鹏（1990—）博士，助理研究员.研究方向：水上交通运输风险评价.E-mail：cpwan@whut.edu.cn

中图分类号: U676.1
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- PDF下载量: 234
- 被引次数: 0
出版历程
- 收稿日期: 2020-05-23
- 刊出日期: 2021-02-28

A Visualization Analysis and Development Trend of Intelligent Ship Studies

ZHANG Di^{1, 2
,},
ZHAO Yinxiang^{1, 2},
CUI Yifan³,
WAN Chengpeng^{1, 2
, ,}

1.
Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China
2.
National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China
3.
School of Navigation, Wuhan University of Technology, Wuhan 430063, China

摘要

摘要: 为了更好地把握智能船舶研究领域的前沿问题及发展现状, 针对智能船舶领域相关主题, 基于中国知网(CNKI)和Web of Science数据库中2010-2020年的文献检索结果, 运用知识图谱从计量统计的角度从时间、作者、机构以及关键词4个方面系统地呈现了智能船舶领域发展的趋势、前沿和热点。在此基础上, 从智能船舶的态势感知、智能避碰、智能控制、网络通信和法律规则研究5个研究方向分析了智能船舶研究趋势和热点问题, 并提出了智能船舶人机共融及决策技术研究、编队航行风险研究以及传统/智能船舶混行风险评价研究这3个重点研究方向。研究结果表明, 从2015年开始, 智能船舶相关研究文章快速增长, 增长幅度在每年14篇以上, 平均增长率达58%; 国内智能船舶主要研究机构包括武汉理工大学、大连海事大学、上海交通大学等, 国外主要研究机构包括挪威科技大学和代尔夫特理工大学; 智能船舶领域的研究热点包括态势感知、智能避碰、智能控制、网络通信安全和法律安全。
- 交通工程 /
- 智能船舶 /
- 航行安全 /
- 知识图谱 /
- 热点分析
Abstract: This paper conducts a comprehensive literature review of intelligent ship based on the studies published on the China Knowledge Network (CNKI) and Web of Science databases to investigate the status quo and the cutting, edge issues in development of intelligent ship.The knowledge graphs are used to systematically present the trends, frontiers, and hot spots in intelligent ship from time, author, institution, and keywords.On this basis, the research trends and hot issues of intelligent ship are analyzed from intelligent situational awareness, collision avoidance, intelligent control, network communication, and the rule of law study. Besides, three key research directions are proposed, including human, machine integration and decision, making technology for intelligent ship, risks of formation navigation, and risk evaluation of mixing navigation of traditional/intelligent ships. The results show that since 2015, published papers related to intelligent ship have increased more rapidly than which between 2010 and 2014, with an average growth rate of 58%(more than 14 articles per year). Key research institutions in China contributing the most to this field include Wuhan University of Technology, Dalian Maritime University, and Shanghai Jiaotong University. Major foreign research institutions include Norwegian University of Science and Technology and Delft University of Technology. Research hotspots in intelligent ship refer to situational awareness, intelligent collision avoidance, intelligent control, network communication security, and legal security.
- traffic engineering /
- intelligent ship /
- navigation safety /
- knowledge graph /
- subject analysis

HTML全文

图 1 2010—2020年国内外智能船舶研究趋势

Figure 1. Research trends of intelligent ship at home and abroad from 2010 to 2020

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图 2 智能船舶研究关键词聚类图

Figure 2. Cluster of keywords in intelligent ship studies

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图 3 智能船舶研究关键词演化趋势图

Figure 3. Evolution trends of keywords in intelligent ship research

下载: 全尺寸图片幻灯片

表 1 国外主要的研究机构

Table 1. Major foreign research institutions

机构	国家/地区	文献数量/篇
挪威科技大学/ Norwegian University of Science Technology	挪威	15
代尔夫特理工大学/ Delft University of Technology	荷兰	14
卡萨布兰卡哈桑二世大学/ Hassan II University of Casablanca	摩洛哥	7
阿尔托大学/ Aalto University	芬兰	7
VTT芬兰技术研究中心/ VTT Technical Research Center Finland	芬兰	6
格丁尼亚海事大学/ Gdynia Maritime University	波兰	5

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表 2 智能避碰相关文献

Table 2. Literature on intelligent collision avoidance

作者（年份）	题目	研究成果
李丽娜, 等^[21]（2011）	船舶拟人智能避碰决策理论的集成机器学习策略	对船舶拟人智能避碰决策的意义、目标和实现方法进行了概述，并在此基础上提出了基于机器学习构建动态避碰知识库的关键技术及智能避碰理论的机器学习机制
郑俏妍^[22]（2016）	海上多目标船物联网智能避碰辅助决策研究	基于模拟退火的粒子群优化算法应用于海上多目标船舶智能避碰辅助决策中，建立船舶转向避碰幅度目标函数模型
Li W., 等^[23]（2017）	Research on intelligent avoidance method of shipwreck based on big data analysis	提出了1种基于大数据分析的船舶智能避碰方法
薛惠，等^[24]（2017）	船舶自动智能避碰数学模型及其计算机仿真研究	基于遗传算法的自动化智能避碰策略
H.Namgung, 等^[25]（2018）	Information exchange system for efficient operations of autonomous ship	提出了1种基于模糊推理理论的碰撞风险评估系统
Wang等^[26]（2019）	Research on intelligent collision avoidance decision-making of unmanned ship in unknown environments	基于马尔可夫决策过程，建立了无人驾驶船舶的智能避碰模型
R.Zaccone，等^[27]（2019）	A collision avoidance algorithm for ship guidance applications	提出了1种基于快速搜索随机树（RRT*）算法的船舶远海航行避碰算法
Huang Y.，等^[28]（2020）	A ship collision avoidance system for human-machine cooperation during collision avoidance	概述了智能船避碰过程中现有的人机交互模式，提出了1个面向人机界面的避碰系统的框架，有助于船舶的自主避碰

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表 3 智能船智能控制相关文献

Table 3. Literature on intelligent control of intelligent ship

作者（年份）	题目	研究成果
Zhang R.L., 等^[35]（2017）	Conversion timing of seafarer's decision-making for unmanned ship navigation	构建无人驾驶船舶群监控模型，提出了1个框架来确定车载决策之间的关系和海岸监视船的过程数据检测、跟踪、分析和损失, 和应用程序的决策算法
Yao B.等^[36]（2018）	Research and comparison of automatic control algorithm for unmanned ship	将模糊算法与神经网络相结合，构建了改进的基于神经网络的PID控制器
Xue J.等^[37]（2019）	Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships' maneuvering decisions using grey and fuzzy theories	利用经验丰富的海员的实验数据，利用仿真平台，提出了1种基于灰色和模糊理论的推理模型
张显库, 等^[38]（2019）	船舶运输安全保障下的智能船舶运动控制策略	采用四维Norrbin非线性数学模型和二阶闭环增益成形算法设计控制策略
徐海祥, 等^[39]（2020）	面向智能船舶的自动靠泊鲁棒自适应控制	提出了1种鲁棒自适应控制律；设计了自适应律估计环境扰动，并引入鲁棒项补偿岸壁效应对船舶的干扰，以消除控制输出的抖振现象

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