According to the World Health Organization, the number of potential pathogens worldwide is very high, which increases the likelihood of a new pandemic. The impact of the new coronavirus infection (Covid-19) on all spheres of human activity, including the air transport industry, has shown that it is necessary to take into account the possibilities of its functioning under the new conditions. During the research, the possibility of using automated modular training systems for the air traffic controllers training in the remote access mode has been considered. The well-known simulators do not implement a justified instrumental procedure for measuring the acquired skills in air traffic services and the assessment of their development is carried out by the instructor, who reacts to the student’s actions on the basis of his experience. It is difficult for the instructor to control the development of a student’s individual skills and he has to rely on his own experience. To simulate the controller-pilot contour, pseudo-pilots are involved, manually changing the flight parameters of the aircraft and simulating R/T communication. The well-known simulators do not allow independent training. As a result, a conceptual design was formed and a promising simulator with the function of training automation and voice support was developed. The effectiveness of the proposed solutions was tested in comparison with the traditional approach to simulator training. Eventually it was found that after using a special simulator, students' mistakes decreased. Subsequently, the simulator was used for practical training of students providing the distance learning in circumstances of pandemics (Covid-19). The project showed its viability and the ability to conduct remote training of air traffic controllers, after appropriate refinement of the promising simulator.


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    Title :

    Development of advanced voice-supported simulators with the function of automated estimation of air traffic controllers skills


    Contributors:


    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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