Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science


DOI 10.5937/jaes17-18117
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions. 
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Volume 17 article 593 pages: 175 - 181

Alexander Novikov
Orel state university named after I.S. Turgenev
Ivan Novikov*
Belgorod state technological university named V.G. Shukhov
Anastasia Shevtsova
Belgorod state technological university named V.G. Shukhov

The high level of motorization typical for many cities gives background to the emergence of congestion situations, which largely reduces the transporting access to and unimpeded movement. To resolve occurring traffic problems are used for various kinds of activities that subunits are radical and conservative. For existing cities, quite often used the second type of events that do not require significant capital investments compared to the first one of these activities is improvement of traffic lights regulation, to reduce delays to vehicles by changing the input parameters required in the calculation. In this work the authors is proposed to model the traffic signalization traffic flow based on its qualitative composition. The growth of car ownership contributes to the change in the qualitative composition of traffic flow, that is not to be taken in determining the modes of traffic lights regulation. The authors performed a study of urban traffic, the results of which allowed to determine the values of the distributions of vehicles in the stream with regard to its composition, based on the extension of the main rolling stock type – passenger car. Based on the obtained distributions, a mathematical analysis for determining the influence of each considered class and refined method of calculation of the traffic signalization. The purpose of the proposed assessment to the development of a methodology for calculating the experimental computer simulation, the comparative analysis of the obtained data and the main conclusions of the study.

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  1. Rodrigue, J. (2013). The SAGE Handbook of Transport Studies. London: SAGE Publications. ISBN: 978-1-849-20789-8.
  2. Mishra, S., Sharma, S., Khasnabis, S., & Mathew, T.V. (2013). Preserving an aging transit fl eet: An optimal resource allocation perspective based on service life and constrained budg-et. Transportation Research Part A: Policy and Practice, 47, 111-123.
  3. Pryn, M.R., Cornet, Y., & Salling, K.B. (2015). Applying sustainability theory to transport infra-structure assessment using a multiplicative ahp decision support model. Transport, 30(3), 330-341. doi:10.3846/16484142.2015.1081281
  4. Moschovou, T.P., & Giannopoulos, G.A. (2012). Modeling Freight Mode Choice in Greece. Procedia - Social and Behavioral Sciences, 48, 597-611.doi:10.1016/j.sbspro.2012.06.1038
  5. Przhibyl, P., & Novikov, A. (2015). Associated systems and transport telematics. The world of transport and technological machines, in Russia, 2 (49): pp.96-102.
  6. Stamos, I., Salanova, G.J.M., Mitsakis, E., & Mamarikas, S. (2015). Macroscopic fundamental diagrams: simulation findings for thessaloniki’s road network. International Journal For Traffic And Transport Engineering, 5(3), 225-237. doi:10.7708/ijtte.2015.5(3).01
  7. Mitsakis, E., Stamos, I., Grau, J.M.S., Chrysochoou, E., Iordanopoulos, P., & Aifadopoulou, G. (2013). Urban Mobility Indicators for Thessaloniki. Journal of Traffic and Logistics Engineering, 1(2), 148-152. doi:10.12720/jtle.1.2.148-152
  8. Sładkowski, A., & Pamuła, W. (2015). Intelligent Transportation Systems - Problems and Pers-pectives. 316 p.
  9. Eresov, B., & Ja, V. (2001). Konfl іktnі situacії ta bezpeka ruhu pіshohodіv. Bezpeka do-rozhn'ogo ruhu. Ukraїni. Nauk. tehn. Vіsnik, 2, 10: pp. 24-30.
  10. Borovskoy, A., & Shevtsova, A. (2012). Using of a new method of calculation of a stream of saturation at definition of a cycle of svetoforny regulation. «European Applied Sciences: Modern approaches in scientific researches»: Papers of the 1st International Scientific Conference. Stuttgart, Germany, pp. 473-479.
  11. Borovskoy, A., & Shevtsova, A. (2014). Innovative technology in teaching students of the organization and road safety. In International scientific-practical conference of pedagogues and psychologists "Scientific genesis". Geneva, Switzerland. Vol. 1: pp.203-206.
  12. Olszewski, P.S. (1994). Modeling probability distribution of delay at signalized intersections. Journal of Advanced Transportation, 28(3), 253-274. doi:10.1002/atr.5670280306
  13. Allsop, R.E. (1972). Delay at a Fixed Time Traffic Signal—I: Theoretical Analysis. Transportation Science, 6(3), 260-285. doi:10.1287/trsc.6.3.260
  14. Teply, S. (1989). Evaluation of the Quality of Signal Progression by Delay Distributions. In Transportation Research Record. Washington, D.C.: National Research Council. 1225, TRB, pp. 1–7.
  15. Brilon, W. (1990). Delays at Fixed Time Traffic Signals Under Time-Dependent Traffic Condition. Traffic Engineering and Control. Vol. 31, No. 12: pp. 623-631.
  16. Webster, F. (1958). Traffic Signal Settings. London, England: Her Majesty's Stationery Office.
  17. Highway Capacity Manual, TRB. (2000). Washington, DC. 1134 p.
  18. Greenshields, B., Schapiro, D., & Ericksen, E. (1947). Traffic Performance at Urban Street Inter-sections. Technical Report, Yale Bureau of Highway Traffic, No. 1.
  19. Capelle, D., & Pinnell, S. (1961). Capacity Study of Signalized Diamond Interchanges. Highway Research Board Bulletin,291: pp. 1-25.
  20. Carstens, R. (1971). Some Traffic Parameters at Signalized Intersections. Traffic Engineering,
  21. King, G., & Wilkinson, M. (1976). Relationship of Signal Design to Discharge Headway, Approach
    Capacity, and Delay. Transportation Research Record, 615: pp. 37-44.
  22. Handbuch fuer die Bemessung von Strassenverkehrsanlagen (HBS) For-shungsgesellschaft fuer Strassen und Verkehrswesen. (2002). Koeln. Januar.
  23. Levashov, A. (2005). Improving the efficiency of traffic management at intersections regulated. Irkutsk. Author. disser-. on scientific. tech degree of Candidate of Sciences: 17 p.
  24. Kremenets, Y., Pechersky, M., & Afanasiev, M. (2005). Technical means of traffic management. M.: Akademkniga. 279 p.
  25. Shevtsova, A., Novikov, I., & Borovskoy, A. (2015). Research of influence of time of reaction of the driver on the calculation of the capacity of the highway. Transport Problems, 10(3), 53-59. doi:10.21307/tp-2015-034
  26. Novikov, A., Novikov, I., Katunin, A., & Shevtsova, A. (2017). Adaptation Capacity of the Traffic Lights Control System (TSCS) as to Changing Parametersof Traffic Flows Within Intellectual Transport Systems (ITS). Transportation Research Procedia, 20,
    455-462. doi:10.1016/j.trpro.2017.01.074
  27. Novikov, A., Katunin, A., Novikov, I., & Shevtsova, A. (2017). Research of Infl uence of Dy-namic Characteristics for Options Controlled Intersection. Procedia Engineering, 187, 664-671. doi:10.1016/j.proeng.2017.04.429
  28. TSS-Transport Simulation Systems: Aimsun Version 7.0. (1997). R10631; Copyright (C); 2011.