Determination of the psychotypes of drivers using machine learning algorithms using twostage cluster analysis
  IJCTT-book-cover
 		          
 
© 2020 by IJCTT Journal
Volume-68 Issue-9
Year of Publication : 2020
Authors : Chantieva Milana, Gematudinov Rinat, Dzhabrailov Khizar, Gorodnichev Mikhail
DOI :  10.14445/22312803/IJCTT-V68I9P101

How to Cite?

Chantieva Milana, Gematudinov Rinat, Dzhabrailov Khizar, Gorodnichev Mikhail, "Determination of the psychotypes of drivers using machine learning algorithms using twostage cluster analysis," International Journal of Computer Trends and Technology, vol. 68, no. 9, pp. 1-10, 2020. Crossref, 10.14445/22312803/IJCTT-V68I9P101

Abstract
This article examines the literature on mathematical methods, and the theory of traffic flows in the 1930s. These problems, both complex sociotechnical systems, particularly, and in general, still attract the attention of researchers studying traffic in megacities. A number of researchers, based on practical data, prove that the results of the hydrodynamic approach to solving traffic problems were more modest than in the original environment, that is, in a liquid. This has previously been noticed by researchers who have noticed the limited usefulness of the entered relationships. Despite numerous attempts to reduce the model to mathematical physics equations, their authors rarely examined the proposed approaches for applicability. Often there are no strict definitions and sufficient conditions for their operation. It is noted that the problem of micro-vibrations in liquids - and especially cavitation - is rather complicated and remains open for further research. As a socio-technical system, generally speaking, the flow of cars has no relation of speed to density in a wide range of partially connected states: an increase in the number of vehicles per unit of carriageway does not have much effect on speed.
The work considered the problem of recognizing the psychotypes of drivers - a very urgent task today. The solution to such a problem as car accidents and fatal accidents is the interest of many, if not everyone. There are already braking systems that can detect objects around the car, road tracking systems that follow the markings using video cameras.
RFBR, project number 19-29-06036, funded the reported study.

Reference
[1] Ilyukhin A.V., Chantieva M.E., Gematudinov R.A., Shukhin V.V. “Cluster structures and the theory of percolation in computational materials science of construction composite materials”./Bulletin of the Moscow automobile and road state technical university (Moscow Administrative Road Inspectorate). 2011. No. 4 (27). Page 97-101.
[2] M. E. Chantieva, K. A. Dzhabrailov, A. V. Iluhin and R. A. Gematudinov, "Software Optimization Methods for Composite Materials," 2019 Systems of Signals Generating and Processing in the field of on Board Communications, Moscow, Russia, 2019, pp. 1-4, https://doi.org/10.1109/SOSG.2019.8706771
[3] Dzhabrailov K., Gorodnichev M., Gematudinov R., Chantieva M. (2020) “Development of a Control System for the Transportation of Asphalt Mix with the Maintenance of the Required Temperature”. In: Popovic Z., Manakov A., Breskich V. (eds) VIII International Scientific Siberian Transport Forum. TransSiberia 2019. Advances in Intelligent Systems and Computing, vol 1116. Springer, Cham. https://doi.org/10.1007/978-3-030-37919-3_35
[4] “Development of a method of calculation of fractional composition of the filtering materials”. Ilyukhin A.V., Chantieva M.E., Gematudinov R.A., Hakimov Z.L. Bulletin of the Moscow automobile and road institute (State technical university). 2009. No. 4 (19). Page 117-123.
[5] “Use of the porous permeable ceramics received by method of the burning-out additives as the filtering elements of ceramic filters for water purification”. Ilyukhin A.V., Chantieva M.E. Bulletin of the Moscow automobile and road state technical university (Moscow Administrative Road Inspectorate). 2010. No. 2 (21). Page 75-79
[6] “The integrated systems of automation of the industrial enterprises”. Abdulkhanova M.Yu., Gematudinov R.A., Chantieva M.E. Bulletin of the Moscow automobile and road state technical university (Moscow Administrative Road Inspectorate). 2010. No. 3 (22). Page 103-108.
[7] Chantieva, M.E. “Use of the theory of the effective environment for modeling of the filtering properties of composite materials of matrix structure”. // Collection of scientific works the 67th scientific and methodical and research conference. – M.: Moscow Administrative Road Inspectorate, 2009
[8] Chantieva M., Dzhabrailov K., Gematudinov R., Suvorov D. (2021) “Modern Method of Computer Simulation of Structures and Physical Properties of Composite Materials”. In: Murgul V., Pukhkal V. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019. EMMFT 2019. Advances in Intelligent Systems and Computing, vol 1259. Springer, Cham. https://doi.org/10.1007/978-3-030-57453-6_53
[9] Chantieva, M.E. “Automation of selection of fractional composition of the filtering materials for the industrial enterprises” (Report)//the 30th Moscow international exhibition "Education and Career — the 21st Century". – Moscow: Gostiny Dvor, 2009.
[10] Ilyukhin, A.V., Chantieva, M.E. Mintsaev M.Sh. “Automation of selection of fractional composition of the filtering materials.” Construction bulletin of the Russian engineering academy: Works of the section "Construction" of RIA. - M.: 2010, No. 11, Page 280-283
[11] Srinivasan Suresh, "Prediction of Average Annual Daily Traffic Using Machine Learning Methods" SSRG International Journal of Computer Science and Engineering 6.11 (2019): 51-54.

Keywords
Machine learning model, deep learning, neural network, probabilistic modeling, input processing, data analysis, clustering algorithms, computer software, speed mode, cluster, and recognition of drivers` psychotypes.