Maritime accidents pose severe risks, particularly ship collision accidents that can result in catastrophic consequences, including fatalities, economic losses, and environmental pollution. To reduce the occurrence of maritime accidents and provide decision-makers in the administrative department with theoretical support, it is critical to analyze the characteristic rules of ship collision accidents and explore the causal relationships between ship factors, environmental factors, human factors, management factors, and accident severity. This paper collects the ship collision accidents occurred in the Chinese coastal waters and identifies and analyzed the major factors that affect the severity of accidents from four perspectives: ship, environment, human, and management factors by using kernel density estimation (KDE) and statistical methods. The results show that the most significant factor affecting the collision accidents severity in this area is the encounter mode, followed by the gross tonnage. Furthermore, ship type also has a significant impact. Encounter mode, gross tonnage, and ship type have a positive impact on the probability of major and severe accidents. The results of this study will contribute to improving awareness of the current danger posed by operating conditions in high-risk coastal waters in China and provide theoretical support for decision-making by relevant maritime safety management departments for controlling vessel traffic safety and improving water facilities in coastal waters.


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    Titel :

    Analyzing Influential Factors of Ship Collision Accidents Severity Using Ordered Probit Model


    Beteiligte:
    Gao, Xinjia (Autor:in) / Yu, Lu (Autor:in) / Yu, Qifeng (Autor:in) / Dai, Wei (Autor:in)


    Erscheinungsdatum :

    2023-08-04


    Format / Umfang :

    1217002 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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