Mathematical modeling of an automated monitoring and predicting system of the psychophysiological states of a navigator under the influence of fatigue and stress
DOI:
https://doi.org/10.18372/2073-4751.83.20548Keywords:
maritime safety, ergatic systems, ship control, on-board technical systems, human factor, psychophysiological state of the navigator, automated monitoring system, MATLAB Simulink, multiplicative model, machine learning, digital twin, transfer functionAbstract
A ship is a complex hierarchical human-machine control system (ergatic system) in which a person is a key component responsible for decision-making at all levels, and therefore the negative effects of the human factor, due to fatigue and stress, on the safety of control are possible at any of these levels, regardless of the operator's qualifications or experience.
Modern automated ship control systems are focused primarily on technical movement parameters and navigation conditions, but hardly take into account the psychophysiological state of operators. This creates additional risks for maritime safety, as stress and fatigue significantly affect the navigator's performance and ability to make the right decisions in difficult situations.
The object of the study is the process of automated monitoring and control of changes in the navigator's psychophysiological parameters under the influence of stress and fatigue during the performance of navigation watch duties.
The problem lies in the lack of effective technical solutions that would ensure the timely detection and compensation of the negative effects of stress and fatigue, which are not taken into account by modern automated navigation systems.
The study proposes the creation of an automated module for monitoring the navigator's condition, based on multiplicative modeling of time series of physiological parameters, taking into account circadian rhythms, adaptive dynamics, and fatigue factors. To improve accuracy, robust regression and transfer function analysis methods are used in the human-machine system.
The scientific novelty lies in the application of a conceptual model that decomposes physiological factors into influence coefficients and allows modeling and predicting the navigator's reactions in real time.
Experimental tests conducted using the Navi Trainer 5000 system and on a real ship confirmed the effectiveness of the model: the accuracy of the assessment exceeded 90%.
The practical significance of the results obtained lies in the possibility of integrating the model into the intelligent modules of ship control systems. This provides automatic adjustment of watch schedules, dynamic adaptation of autopilot parameters, and the formation of warning signals for the crew, which increases the level of maritime safety.
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