Keywords: automated information systems, vehicle driver training, educational-training equipment, learning outcomes assessment, traffic rules


The article looks at certain aspects of using automated information systems in the professional training of drivers at Hetman Petro Sahaidachnyi National Army Academy, Ukraine. The importance of integrating the theoretical and practical components of learning and the linkage between learning outcomes and safety on the roads are emphasized. The modern educational-training equipment for training drivers (simulators) includes information program components that can be customized to suit students’ individual characteristics and priorities for consideration in real road-traffic conditions. Assessment of students' knowledge and skills with simulators is carried out by analyzing their errors on typical routes that simulate problematic traffic situations. The main types of errors correspond to the common causes of road-traffic accidents, in relation to which statistics according to regions and periods are available, which, while training, gives a possibility to quickly respond to changes in the structure of accidents in the recent years in view of their causes. The automated information system is configured by a teacher in the way of correction of penalty points for every type of error. Upon reaching the critical amount of such points, the student is directed to retake the course, which makes it possible to provide the proper level of mastering the material before starting classes in the conditions of a real road situation. In future, increasing the share of the training time on the stimulator, it will be possible to take into account the students’ individual features of assimilating the material. This can be realized by introducing increased coefficients for repetitive errors into the penalty function. For this purpose a linear model of the total penalty score is proposed in the paper, which takes into account the specific and general errors, moreover, in the latter the base price of the error is related to the share of accidents with severe consequences. The multiplier of the individual weight of the error allows increasing its value in case this type of mistake occurred earlier and the student did not heed it.


Download data is not yet available.

Author Biography

Ruslan V. Kuzmenko, Hetman Petro Sahaidachnyi National Army Academy

PhD of Technical Sciences, Deputy Chief of Combat Vehicle Driving Department


O. Saukh. "Competent approach to the training of skilled workers by the profession of" driver of motor vehicles "in the conditions of vocational schools", Innovative technologies in the production and training of specialists in technology, vocational education and services, p.125-130, 2015. [Online]. Available: Accessed on: Feb. 21, 2019. (in Ukrainian)

Y. Krasnik, O. Rimar, T. Popovich. "Substantiation of the effectiveness of the creation of training and training resources for the training of personnel of the Armed Forces on the basis of maximum use of computer technologies", Viysʹkovo-tekhnichnyy zbirnyk ASV, № 1(4), p.183-187, 2011. (in Ukrainian)

V. Kostyuk, V. Belen, P. Rusilo. "Substantiation of a rational nomenclature of modern training equipment for the training of specialists in the automobile service in the land forces of the Armed Forces of Ukraine", Viysʹkovo-tekhnichnyy zbirnyk ASV, № 1(4), p.177-182, 2011. (in Ukrainian)

K. Shevchenko, V. Gorkun, S. Kozupitsa. "Opportunities for training drivers with the help of modern computer programs and simulator-modeling complexes", Visnyk KNUTD, №3, pp. 39-43, 2011. (in Ukrainian)

Moraes, T. D., Zambroni-de-Souza, P. C., & Schwartz, Y. (2017). Usages of Simulators During Professional Training for Driving road Transportation. Psicologia: Ciência e Profissão, 37(1), 192-207. (in English)

Allen, R. W., Park, G. D., Cook, M. L., & Fiorentino, D. (2007). The effect of driving simulator fidelity on training effectiveness. DSC 2007 North America. (in English)

Bélanger, A., Gagnon, S., & Stinchcombe, A. (2015). Crash avoidance in response to challenging driving events: The roles of age, serialization, and driving simulator platform. Accident Analysis & Prevention, 82, 199-212. (in English)

Management of road safety. Accident Statistics in Ukraine. [Online]. Available: ua/static/21.htm. Accessed on: Feb. 07, 2016. (in Ukrainian)

Main statistical office in Lviv region. Road accidents and casualties in Lviv region. [Online]. Available: Accessed on: Mar. 05, 2019. (in Ukrainian)

Ministry of Education and Science of Ukraine. (Order of the Ministry of Education and Science №802 of 10.07.12). State Standard of Vocational Education and Training DSPT 8322.ОІ.00.60.24-2012 "The driver of vehicles. Specialization: driving vehicles category" C "(driving the maximum authorized mass of which exceeds 7500kh (16,500 pounds)". [Online]. Available: Accessed on: Mar. 20, 2019. (in Ukrainian)

V. Bilichenko, V. Raziborinsky. "Analysis of approaches to the classification of motor cycles for training drivers". Naukovi notatky. - 2014. Vyp. 46. – P. 29-37. [Online]. Available: _46_6. Accessed on: Feb. 20, 2019. (in Ukrainian)

S. Subbotin. Presentation and processing of knowledge in systems of artificial intelligence and decision making support. Tutorial. Zaporizhzhya: ZNTU, 2008. 341 p.

Cabinet of Ministers of Ukraine. Resolution №1306 of 10 October 2001, as amended "About the Rules of the Road". [Online]. Available: Accessed on: Mar. 04, 2019. (in Ukrainian)

A. Kashkanov, O. Hrysyuk. Safety of motor transport. Tutorial. Vinnitsa: VNTU, 2005. 177 p. (in Ukrainian)

Tran, C. C., Yan, S., Habiyaremye, J. L., & Wei, Y. (2017, December). Predicting driver’s work performance in driving simulator based on physiological indices. In International Conference on Intelligent Human Computer Interaction (pp. 150-162). Springer, Cham. (in English)

How to Cite
Kuzmenko, R. V. (2019). ADAPTIVE DRIVER TRAINING WITH THE USE OF SIMULATOR SYSTEMS. Information Technologies and Learning Tools, 74(6), 84-95.
ICT and learning tools in vocational education and training