IDENTIFICATION OF “HUMAN ERROR” NEGATIVE MANIFESTATION IN MARITIME TRANSPORT

Abstract

Context. There is a problem of identifying the subjective entropy of the navigator as an indication of negative human error in maritime transport. The aim of the study is to develop the data system to identify the negative manifestations of the human error for ensuring safety in maritime transport. Objective. The objective of the work is to design the data system consisting of two levels. Levels are targeted at detection of primary factors and secondary factors of subjective entropy of the navigator increase. Method. Within the scope of this work, the phases of the navigator’s activity are determined, in which negative manifestations of the human error arise. This most often occurs during emergency situations. It is determined that the navigator’s loss of focus leads to inadequate actions in relevant situations. Stressful situations are the second reason that affects self-control level. The factors’ expanses influencing the navigator’s subjective entropy increase as well as the vector affecting the subjective entropy at the first level of the formal system are determined. The arrangement of sets of factors was carried out. The arrangement result represents the formal system’s first level description. Multi-objective optimization problem is vital for optimal solutions identification. The patterning’s target is error evaluation on finding a vector, which is an essential stage. The lower limit of the system identification level is determined. The formal description of actions at the second level of the system is carried out and vector is specified at this level. The dependences of second-level vectors’ impacts on navigator subjective entropy increase are specified with maximum accuracy. Time input estimation for system actuation allows us to determine three operating modes of the system. The input data for operating modes specification is indicated. The matrix-based framework algorithm of navigator’s behavior during emergency situations is given. Results. Formal approaches were confirmed by simulation patterning using the navigation simulator NTPRO 5000. The data obtained allowed to build an algorithm in navigator’s shaping of in various situations. Conclusions. The proposed formal approaches, patterns and algorithms will provide a basis for navigator’s behavior analysis during emergency situations. The search of the best practice of human error data mining based on real data and simulator training data can be the direction for future research. This will allow to determine the mathematical expectation of navigator’s behavior in emergency situations, as well as when performing operations with a low coefficient of experience.