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

ZHANG Di; LI Zhihong; WAN Chengpeng

doi:10.3963/j.jssn.1674-4861.2023.06.001

Volume 41 Issue 6

Dec. 2023

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ZHANG Di, LI Zhihong, WAN Chengpeng. An Analysis and Prospects of Hot Topics on Maritime Autonomous Surface Ship Safety Research[J]. Journal of Transport Information and Safety, 2023, 41(6): 1-11. doi: 10.3963/j.jssn.1674-4861.2023.06.001

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ZHANG Di, LI Zhihong, WAN Chengpeng. An Analysis and Prospects of Hot Topics on Maritime Autonomous Surface Ship Safety Research[J]. Journal of Transport Information and Safety, 2023, 41(6): 1-11. doi: 10.3963/j.jssn.1674-4861.2023.06.001

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

doi: 10.3963/j.jssn.1674-4861.2023.06.001

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

Received Date: 2023-11-27
Available Online: 2024-04-03

Abstract

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

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References(55)

References

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