65.8% of marine casualties and incidents are attributed to human actions, according to European Maritime Safety Agency. It is even more worrisome given the emerging Maritime Autonomous Surface Ships (MASS) in which human factors play an increasingly important role (e.g. remote controlled vessels). Therefore, it triggers a new research question on how to effectively address human factors in the next generation of maritime transport given more complicated traffic and increased automation. One of realistic solutions is to develop a systematic and holistic methodology, capable of conducting human factor analysis under various circumstances depending on crucial influencing factors such as the nature of human behaviors (physical or psychological) and features of the available data (uncertainty level). This study pioneers this development with a new framework for the quantitative analysis of human factors in maritime transport. It first explores the common risk factors, data collection resources, and quantitative analysis methodologies in the literature. With regard to different research objectives, bespoke approaches aiming at specific purposes, i.e., risk-based accident analysis, neurophysiological analysis during navigation, and human reliability performance evaluation for a particular task, are integrated to develop the systematic analysis framework holistically. Compared to piecemeal classical methods, the results show the feasibility and beauty of systematically utilizing assembled methods in different situations and how the new methodology can better fit the increasing demand for human reliability in the maritime transport era involving MASS. The proposed framework can provide a transparent tool to quantify and evaluate human factors for a specific purpose, particularly a hybrid of both physical and psychological concerns. It also generates insights into the whole development process of MASS, from its low to high degrees of autonomation.


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    Title :

    Systematic analysis of human factors in maritime transportation


    Contributors:
    Fan, Shiqi (author) / Yang, Zaili (author)


    Publication date :

    2023-08-04


    Size :

    409998 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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