Development and experimental study of analyzer to enhance maritime safety

Nosov, Pavlo; Zinchenko, Serhii; Plokhikh, Viktor; Popovych, Ihor; Prokopchuk, Yurii; Makarchuk, D. V.; Mamenko, Pavlo; Moiseienko, Vladyslav; Ben, Andrii

doi:10.15587/1729-4061.2021.239093

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…One of the main tasks of the scientific analysis considered in the article is the construction of a map of the mental motivational states of navigators. This aspect will make it possible to structurally and accurately determine the initial cause of the emergence of critical situations and navigational hazards [23].…”

Section: The Study Materials and Methodsmentioning

confidence: 99%

Devising an approach to safety management of vessel control through the identification of navigator’s state

Nosov,

Koretsky,

Zinchenko

et al. 2023

EEJET

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The object of this study is the processes of automated management of maritime safety by analyzing the manifestations of the human factor of sea navigators. The task solved is justified by the need for formal and logical analysis and intelligent identification of mental motivational states (MMS) of marine navigators whose actions can cause dangerous situations during the control of the ship’s movement. High accident rates due to the fault of the navigators, in the absence of automated means of monitoring their condition, cause a contradiction between the existing means of safety control in controlling the movement of the vessel and the modern requirements of navigation, which needs to be resolved. A safety management approach was devised that takes into account the specificity of navigational tasks and the p-adic classification of dangerous MMS for navigators. This has made it possible to create three security modes that are activated depending on the detected state of the navigator’s MMS. Features of the results are the combination of analysis by means of p-adic systems and intelligent methods of data processing. As a result, sufficient identification accuracy was obtained for more than 75 % of MMS through neural network training. Experimental data collected during the navigation watch, as well as on the Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Finland), became the basis for simulation by means of neural networks. In turn, the training of neural networks made it possible to obtain sufficient identification accuracy by performing up to 3000 iterations. Overall, the learning rate of the neural network was 0.98, which indicates a high level of identification. From a practical point of view, the results could be used for the automated management of shipping safety, as well as for evaluating the level of adaptation of the navigator to dynamically changing conditions. The proposed approach provides opportunities for the application of modern intelligent technologies in the field of maritime transport safety, namely artificial neural network tools that determine notification modes or activation of automatic ship traffic control modules. The specified contradiction requires the design of specialized systems for automated safety management of ship traffic control based on the identified states of navigators

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Section: The Study Materials and Methodsmentioning

confidence: 99%

Devising an approach to safety management of vessel control through the identification of navigator’s state

Nosov,

Koretsky,

Zinchenko

et al. 2023

EEJET

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show abstract

“…where Gs is the global system, εAg are local features or agents. Manifestation: an intuitive understanding of the features of the navigation area, namely the failure to take into account the small attributes of the navigation area, including coastal currents, depths, and other local conditions affecting safety [22].…”

Section: Cognitive Processes Formal Description (3)mentioning

confidence: 99%

Devising an approach for the automated restoration of shipmaster’s navigational qualification parameters under risk conditions

Ponomaryova,

Nosov,

Ben

et al. 2024

EEJET

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The object of this study is the safety control system of ship management, by identifying and restoring the qualification parameters of shipmasters in critical situations. The task solved in the study is the timely determination of an insufficient level of qualification for the performance of certain operations in controlling the movement of the ship, by applying a formal-logical model of detecting the intuitive actions of the operator-shipmaster and gradually restoring his/her qualification parameters using the devised method. The stages of development and the formal-logical structure of the model and method in terms of cognitive automation were described in detail as the study results. It was possible to ensure early detection of risks when controlling the movement of the ship in 56 % of cases, during a laboratory experiment on simulators, which in 24 % of cases turned out to be particularly dangerous. The interpretation of the results involved algorithmizing complex and formalized data on the actions of operators and the application of the method of restoring their qualification parameters, which allowed a comprehensive approach to safety management. The distinguishing features of the findings were to predict the level of danger by simulating maritime operations with input navigational and individual conditions. This made it possible to improve the effectiveness of operations to 89 %, reduce the phenomenon of loss of control over the course to 32 %, reduce critical situations to 7 % and the cost of resources. The scope and conditions of practical use involve a comprehensive assessment of external and internal influences on the level of danger, delay in decision-making by operators, as well as sailing conditions. The simulation results could be used to devise strategies for planning maneuvers, predicting risks, and developing maritime security systems

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Development and experimental study of analyzer to enhance maritime safety

Cited by 2 publications

References 24 publications

Devising an approach to safety management of vessel control through the identification of navigator’s state

Devising an approach to safety management of vessel control through the identification of navigator’s state

Devising an approach for the automated restoration of shipmaster’s navigational qualification parameters under risk conditions

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