Maritime vessel collision accidents, especially the “deadly crossing” situation at a true bearing of 22.5 degrees abaft the beam, have always been a focal point of concern in maritime safety. These incidents lead to significant financial detriment and gravely endanger the well-being of the crew. This research introduces an innovative approach to decision-making that integrates the principles of fuzzy mathematics with extensive form game theory, specifically tailored to tackle the challenge of high-risk avoidance. By developing a quantitative model to evaluate collision risk and analyzing the strategic interaction between ships using game theory, this study aims to offer scientific decision support for ship operators in collision avoidance. Using the Python software, the simulation experiments were performed to validate the practicality and the efficacy of the proposed approach. The findings demonstrate that this approach can significantly enhance collision avoidance efficiency and safety for ships in “death cross” situations. This research deepens maritime collision avoidance theory and offers pragmatic direction for sea operations, making important contributions to improving maritime traffic safety.


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    Titel :

    Ship Collision Avoidance Decision-Making Based on Extensive Game Theory: Analysis of the Death Cross Situation


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Limin (Herausgeber:in) / Ou, Dongxiu (Herausgeber:in) / Liu, Hui (Herausgeber:in) / Zong, Fang (Herausgeber:in) / Wang, Pangwei (Herausgeber:in) / Zhang, Mingfang (Herausgeber:in) / Gai, Xudong (Autor:in) / Zhang, Qiang (Autor:in) / Hu, Yancai (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Erscheinungsdatum :

    31.03.2025


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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