Abstract
Human factor management is crucial to the safety of maritime shipping. Whilst there has been extensive research on human factors in conventional shipping, the development of autonomous shipping necessitates the investigation of emerging human factors under the evolving landscape. Given that the research on human factor analysis for remote operation failure is limited, this study aims to enrich the literature by establishing a comprehensive human factor framework and empirically assessing the factors. Based on the literature review and expert interview, a total of ten categories and thirty-one human factors are organized under the human factor analysis and classification system. Adopting the purposive sampling, questionnaire surveys are then distributed to experts specializing in ship operations and automation to collect their degree of belief on potential human factors. A hybrid method composed of evidential reasoning and the rule-based Bayesian network is applied to analyze the data. The empirical results indicate that adverse mental states and adverse cognitive states are perceived to be the most threatening risk categories in remote operations. This study expands the academic research on human factor analysis and highlights the significance of managing psychological and cognitive factors. The findings provide managerial implications for the future safety management of autonomous ships.
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