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Analysis of risk factors for narrow channel navigation of autonomous ships

Published: 24 October 2024 Publication History

Abstract

The purpose of this paper is to analyze the risk factors of autonomous ships when navigating narrow waterways, and to compare the differences and differences between these risks and conventional vessels. A model combining the SHEL model and the Fuzzy Cognitive Map (FCM) is proposed, through the systematic consideration of multiple dimensions such as software, hardware, environment and personnel, the FCM links and analyzes the complex interactions between these risk factors, and classifies the risks with different gradients, which can provide a scientific basis for the safety and risk management of narrow channel navigation of autonomous ships.

References

[1]
IMO. Outcome of the regulatory scoping exercise and gap analysis of conventions emanating from the legal committee with respect to maritime autonomous surface ships (MASS)[Z], LEG.1/Circ11. 2021.
[2]
Thieme C A, Utne I B, Haugen S. Assessing ship risk model applicability to Marine Autonomous Surface Ships[J]. Ocean Engineering, 2018, 165: 140-154.
[3]
ZHANG Feng. Analysis of navigation safety and collision accidents in the narrow waterway of the Yangtze River [J]. Journal of Qingdao Ocean Seafarer Vocational College, 2018, 39(04):10-13+20.
[4]
CHEN Fei. Risk assessment of ship navigation safety in inland waterways of Shanghai based on fuzzy comprehensive evaluation based on AHP [J]. Port technology, 2012 (02):33-38.
[5]
Bolbot V, Theotokatos G, Wennersberg L, et al. A novel risk assessment process: Application to an autonomous inland waterways ship. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. 2023; 237(2):436-458.
[6]
Cunlong Fan, Krzysztof Wróbel, Jakub Montewka, Mateusz Gil, Chengpeng Wan, Di Zhang, A framework to identify factors influencing navigational risk for Maritime Autonomous Surface Ships, Ocean Engineering, Volume 202, 2020, 107188,ISSN 0029-8018,.
[7]
Kosko B. Fuzzy cognitive maps [J]. International Journal of Man-Machine Studies, 1986, 24(1): 65-75.
[8]
Cui Junhui, Wei Ruixuan, Cui Jianru, et al. A prediction method for the causes of UAV accidents based on FCM [J]. Systems Engineering Theory and Practice, 2015, 35(12): 3258-3264.
[9]
Bueno S, Salmeron J L. Benchmarking main activation functions in fuzzy cognitive maps[J]. Expert systems with Applications, 2009, 36(3): 5221-5229.
[10]
LI Jiayue. Research on aeronautical intelligence work based on the SHEL model [J]. Tribune of Science and Technology, 2020, 28(19):38.

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    CAIBDA '24: Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms
    June 2024
    1206 pages
    ISBN:9798400710247
    DOI:10.1145/3690407
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 24 October 2024

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    Author Tags

    1. Autonomous ships
    2. Identification of risk factors
    3. Narrow waterway navigation
    4. Risk analysis

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