智能船舶安全研究的热点问题分析与展望

张笛; 李治宏; 万程鹏

doi:10.3963/j.jssn.1674-4861.2023.06.001

智能船舶安全研究的热点问题分析与展望

doi: 10.3963/j.jssn.1674-4861.2023.06.001

张笛^{1, 2,},
李治宏^{1, 2, 3},
万程鹏^{1, 2, 3, ,}

1.
武汉理工大学交通与物流工程学院武汉 430063
2.
武汉理工大学国家水路交通控制全国重点实验室武汉 430063
3.
武汉理工大学智能交通系统研究中心武汉 430063

基金项目:

国家自然科学基金项目 51920105014

国家自然科学基金项目 52372342

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，副研究员. 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: U491.5+4
计量
- 文章访问数: 180
- HTML全文浏览量: 100
- PDF下载量: 133
- 被引次数: 0
出版历程
- 收稿日期: 2023-11-27
- 网络出版日期: 2024-04-03

An Analysis and Prospects of Hot Topics on Maritime Autonomous Surface Ship Safety Research

ZHANG Di^{1, 2
,},
LI Zhihong^{1, 2, 3},
WAN Chengpeng^{1, 2, 3
, ,}

1.
School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
2.
State Key Laboratory of Waterway Traffic Control and Safety, WuhanUniversity of Technology, Wuhan 430063, China
3.
Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China

摘要

摘要: 近年来，随着自主导航、传感器、通信和网络技术的成熟，智能船舶的研究迅速发展。2023年9月，第33届欧洲安全与可靠性会议在英国南安普顿成功召开。会议主题聚焦于在互联世界中构建安全的未来，特别关注智能船舶安全性。在对514篇会议论文（其中19篇涉及智能船舶安全相关主题）进行全面分析的基础上，结合前2届会议情况，以及国内外近十年的相关研究，总结了智能船舶安全研究领域的4个热点问题：①自主性水平与相关法律法规：随着船舶自主性的提升，现有法律体系需要更新以适应新技术，研究集中在界定智能船舶的自主性水平，并探讨相应的法律和监管框架；②远程操作中的人因问题：远程操作引入了新的挑战，研究聚焦于设计远程操作系统，以减轻操作员的心理负担，提高沟通效率，并提供有效的决策支持以确保安全；③智能船舶风险评估：该研究领域致力于使用先进技术进行更精准的安全和风险评估，包括运用多维传感器数据、实时监控和多样化的数据分析模型；④人工智能与机器学习的应用：二者被视为智能船舶安全领域的创新方向，研究重点在于利用这些技术进行故障预测、航行路径优化和自动化安全监督。通过分析现有文献，从4个关键角度对未来智能船舶安全研究方向进行了展望：①通过采用基于模型的系统工程方法进行船舶安全分析，可以从设计初期开始识别并消除潜在的安全隐患，同时促进跨学科团队的协作，以提高安全与可靠性分析的精确性；②人因风险分析方面，认为功能共振分析方法更适合处理智能船舶这类复杂系统，通过评估系统功能之间的相互作用，识别故障并制定预防措施；③为了提高紧急情况下的干预效率，需要研究开发能辅助操作员迅速、准确作出决策的支持系统，同时须考虑到操作员的心理和生理状况；④应用人工智能和机器学习深化理论，开发能在复杂海洋环境中作出精确决策的自主决策模型，以及能整合多种数据源提供精确天气预报和航线优化的先进算法。
- 航行安全 /
- 智能船舶 /
- 风险和安全 /
- 热点分析
Abstract: In recent years, the maturation of technologies such as autonomous navigation, sensors, communication, and networking has spurred rapid advancements in Maritime Autonomous Surface Ship (MASS) research. In September 2023, the 33rd European Safety and Reliability Conference was successfully held in Southampton, UK. The conference them centered on building a safe future in an interconnected world, with a particular emphasis on the safety of MASS. Based on a comprehensive analysis of 514 conference papers (including 19 papers related to intelligent ship safety topics), combined with the previous two conference proceedings and relevant research from the past decade both domestically and internationally, four hot topics in the field of MASS safety research are summarized: ①Autonomy level and related regulations: As the autonomy of MASS increases, the current legal frameworks need updating to accommodate new technologies, with research focusing on defining the autonomy levels of MASS and exploring the corresponding legal and regulatory frameworks. ② Human factors in remote operations: Remote operation of MASS introduces new challenges related to human factors. Research is oriented towards designing remote operation systems to reduce the psychological burden on operators, enhance communication efficiency, and provide effective decision support to ensure safety. ③ Risk assessment of MASS: This field aims to use advanced technologies for more accurate safety and risk evaluations, incorporating the use of multi-dimensional sensor data, real-time monitoring, and diversified data analysis models. ④ Applications of artificial intelligence and machine learning in MASS: Both technologies are regarded as innovative directions in the field of MASS safety, with research primarily focusing on their application in fault prediction, route optimization, and automated safety monitoring. Through a survey of existing literature, future research directions for MASS safety are prospectively discussed from four critical perspectives. ① By adopting Model-based Systems Engineering approach for ship safety analysis, potential safety threats can be identified and eliminated from the design phase, promoting interdisciplinary collaboration, and enhancing the accuracy of safety and reliability analysis. ② In terms of human factor risk analysis, the Functional Resonance Analysis Method is considered more suitable for complex systems like MASS. By evaluating the interactions between system functions, failures can be identified, and preventive measures can be formulated. ③ To improve efficiency in emergency situations, research needs to develop support systems that assist operators in making rapid and accurate decisions, considering the psychological and physiological states of operators. ④ The application of artificial intelligence and machine learning to deepen theoretical research involves developing autonomous decision-making models capable of making accurate decisions in complex maritime environments and advanced algorithms that integrate multiple data sources for accurate weather forecasting and route optimization.
- navigation safety /
- Maritime Autonomous Surface Ship (MASS) /
- risk and safety /
- hotspot analysis

HTML全文

图 1 主要成果来源国家

Figure 1. Main source countries

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图 2 2015—2023年发文量

Figure 2. Yearly publication from 2015-2023

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图 3 研究主题聚类

Figure 3. Research topic clusters

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图 4 各研究主题占比

Figure 4. The distribution of research topics

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图 5 Bow-tie分析方法

Figure 5. Bow-tie analysis method

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图 6 用于量化训练后的PHM模型精度验证的框架

Figure 6. Framework for quantifying the validation accuracy of the trained PHM model

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图 7 人类和机器学习循环过程

Figure 7. Human and robot task learning cycle

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表 1 智能船舶自主性水平

Table 1. Level of autonomy of MASS

自主性水平	描述
等级1	具有自动化流程和决策支持的船舶，海员在船操作控制船舶系统和功能
等级2	有海员在船的遥控船舶
等级3	没有海员在船的遥控船舶
等级4	完全自主的船舶

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