Prediction of human–machine interface (HMI) operational errors for maritime autonomous surface ships (MASS)

Abstract

The human factor is a hot topic for the maritime industry since more than 80 percent of maritime accidents are due to human error. Minimizing human error contributions in maritime transportation is vital to enhance safety levels. At this point, the Maritime Autonomous Surface Ships (MASS) concept has become one of the most significant aspects to minimize human errors. The objective of this research is to predict the human-machine interface (HMI) based operational errors in autonomous ships to improve safety control levels. At this point, the interaction between shore-based operator and controlling system (cockpits) can be monitored and potential HMI operational errors can be predicted. This research utilizes a Success Likelihood Index Method (SLIM) under an interval type-2 fuzzy sets (IT2FSs) approach. While the SLIM provides a prediction of the human-machine interface (HMI) operational errors, the IT2FSs tackles uncertainty and vagueness in the decision-making process. The findings of this paper are expected to highlight the importance of human-machine interface (HMI) operational errors in autonomous ships not only for designers but also for operational aspects.

An extended human reliability analysing under fuzzy logic environment for ship navigation

“…The comparison is exercised with SLIM under fuzzy environment since fuzzy sets cope with the vagueness of experts' judgement and expression in decision-making in prioritisation process of PSFs. The SLIM (Embrey et al 1984) is the first-generation HRA technique developed to quantify and predict the HEPs by focusing on factors called PSFs that have a considerable effect on human performance (Grozdanovic 2005;Liu et al 2021). The technique relies on the expert judgements in the data derivation process due to the lack of numerical data .…”

Using the ISM-ANP-SD combination model to explore the mechanism and intervention strategies of influencing factors of coal mine safety system

“…AHP, Entropy method, and multi-granularity non-equilibrium semantic treatment method are used to calculate the index's weight, and the suggestion of coal mine safety management is put forward ( 25 ). To sum up, scholars' studies on influencing factors of coal mine safety mostly construct index systems from individual factors ( 26 ), organizational factors ( 11 , 22 ), management factors ( 27 , 28 ), machinery and equipment ( 29 , 30 ), and environmental factors.…”