AUTOMATIC DETERMINATION OF THE NAVIGATORS MOTIVATION MODEL WHEN OPERATING WATER TRANSPORT

Abstract

Context. The article proposes an approach for automated identification of the navigators motivational model in the control of water transport. Algorithms for data extraction as a result of the man-machine interaction of navigator with the electronic control systems of the vessel during performing navigation operations of increased complexity are proposed.
 Objective. The purpose of research is to apply formal and algorithmic approaches to extracting data on the motivational model of navigator to prevent accidents in water transport. 
 Method. The identification of manifestation determination of navigators’ mental activity by means of the visual concept of the geometric group theory is proposed. This approach delivered the visual systematic-logical combining of diagnostic methods aimed at determining navigators motivational centers and the processes of professional activity like maneuver performing. The key indicator of identification is said to be the parameter of the navigator’s activity as “rpm_port” having an impact on the vessel speed being a marker of intensification of the navigator’s physiological activity. Such an approach is beneficial in time phase identification while maneuvering indicating explicitly at the stepping up of the navigator’s physiological motivational state. It was proven to be correct based on the results due to Ward’s dendrogram, several statistical methods and applied software. The obtained research results encourage the prediction of the navigator’ motivational states in critical situations.
 Results. In order to confirm the proposed formal-algorithmic approach, an experiment was carried out using the navigation simulator Navi Trainer 5000. Automated analysis of experimental ones made it possible to form a motivational map of the navigator and determine the decision-making model affecting in the processes of control vessel in difficult situations.
 Conclusions. The proposed research approaches made it possible to automate the processes of extracting data indicating the principles of decision-making by navigator. The effectiveness of proposed approach was substantiated by the results of experimental data automated processing and the constructed tree-like decision-making spaces.