Selection of a traffic management scheme at an intersection taking into consideration the traffic flow composition

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.195327

Keywords:

traffic composition, traffic flow, traffic management scheme, traffic delay

Abstract

Traffic flows in large cities have a non-uniformed character of origin and changes. The main parameters are often sensitive to the changes in the environmental conditions, specifically, the time of the day, season, etc. The magnitudes that characterize traffic flows have a stochastic nature and therefore they are difficult to predict. According to this, indicators such as intensity, density and traffic speed over time and space are uneven. Taking this into consideration, during the development of traffic management schemes, there arises a necessity to take into consideration additional factors which are of probabilistic nature. This approach provides more opportunities in the traffic management process and makes it possible to use appropriate ways to choose traffic management methods in certain cases. This process involves detailed studies of traffic indicators. The approaches and methods for studying the main indicators of traffic flows were given. They include both field methods and simulation, which involves accounting of mathematical and physical patterns of traffic flows. It also makes it possible to predict the situation when choosing a traffic management scheme with the use of computer equipment. The results of the studies, which were conducted according to the described methods, were analyzed. These results indicate a close relationship between the relative traffic composition for the types of vehicles and the indicators of queuing and delays within the intersections. According to the results, mathematical dependences characterizing this relationship were obtained. It was established that the choice of a road traffic scheme at intersections should be made taking into consideration the traffic flow composition, as each regulation type is effective for a particular case

Author Biographies

Taras Postranskyy, Lviv Polytechnic National University S. Bandery str., 12, Lviv, Ukraine, 79013

PhD, Assistant

Department of Transport Technologies

Mykola Boikiv, Lviv Polytechnic National University S. Bandery str., 12, Lviv, Ukraine, 79013

PhD, Associate Professor

Department of Transport Technologies

Maksym Afonin, Lviv Polytechnic National University S. Bandery str., 12, Lviv, Ukraine, 79013

Assistant

Department of Transport Technologies

Roman Rogalskyi, Lviv Polytechnic National University S. Bandery str., 12, Lviv, Ukraine, 79013

PhD, Senior Lecturer

Department of Transport Technologies

References

  1. Zambrano-Martinez, J., Calafate, C., Soler, D., Cano, J.-C., Manzoni, P. (2018). Modeling and Characterization of Traffic Flows in Urban Environments. Sensors, 18 (7), 2020. doi: https://doi.org/10.3390/s18072020
  2. Polishchuk, V. P., Bakulich, O. O., Dziuba, O. P. et. al. (2014). Orhanizatsiya ta rehuliuvannia dorozhnoho rukhu. Kyiv: Znannia Ukrainy, 467.
  3. Liu, X., Lu, J. (2013). The Technology of Road Guide Signs Setting in Large Interchanges. Procedia - Social and Behavioral Sciences, 96, 538–547. doi: https://doi.org/10.1016/j.sbspro.2013.08.064
  4. Klinkovshteyn, G. I., Afanas'ev, M. B. (2001). Organizatsiya dorozhnogo dvizheniya. Moscow: Transport, 247.
  5. Jayasinghe, A., Sano, K., Nishiuchi, H. (2015). Explaining traffic flow patterns using centrality measures. International Journal for Traffic and Transport Engineering, 5 (2), 134–149. doi: https://doi.org/10.7708/ijtte.2015.5(2).05
  6. Vasiukovych, D. B. (2013). Vybir variantiv orhanizatsiyi rukhu na kiltsevykh peretynakh. Problemy rozvytku miskoho seredovyshcha, 10, 43–47.
  7. Xi, X., ZhaoCheng, H., WenBo, S., ZhanQiu, C., JunFeng, G. (2013). Traffic Impact Analysis of Urban Intersections with Comprehensive Waiting Area on Urban Intersection based on PARAMICS. Procedia - Social and Behavioral Sciences, 96, 1910–1920. doi: https://doi.org/10.1016/j.sbspro.2013.08.216
  8. Kratkoe rukovodstvo po vypolneniyu proektov v PTV Vissim 6. Available at: https://bespalovdotme.files.wordpress.com/2017/03/quickstart_vissim_6-0.pdf
  9. Jin, S., Wang, J., Jiao, J. (2013). The Study in Diamond Interchange Traffic Organization. Procedia - Social and Behavioral Sciences, 96, 591–598. doi: https://doi.org/10.1016/j.sbspro.2013.08.069
  10. Jamshidnejad, A., Papamichail, I., Papageorgiou, M., De Schutter, B. (2018). Sustainable Model-Predictive Control in Urban Traffic Networks: Efficient Solution Based on General Smoothening Methods. IEEE Transactions on Control Systems Technology, 26 (3), 813–827. doi: https://doi.org/10.1109/tcst.2017.2699160
  11. Alex, S., Isaac, K. P. (2014). Traffic simulation model and its application for estimating saturation flow at signalised intersection. International Journal for Traffic and Transport Engineering, 4 (3), 320–338. doi: https://doi.org/10.7708/ijtte.2014.4(3).06
  12. Yu, Q., Zhou, Y. (2019). Traffic safety analysis on mixed traffic flows at signalized intersection based on Haar-Adaboost algorithm and machine learning. Safety Science, 120, 248–253. doi: https://doi.org/10.1016/j.ssci.2019.07.008
  13. Vasylieva, H. Yu. (2005). Tochnist otsinky zatrymok transportu na rehulovanykh perekhrestiakh u tsentrakh mist. Mistobuduvannia ta terytorialne planuvannia, 21, 37–52.
  14. Kovalenko, L. O. (2010). Doslidzhennia ta analiz kharakterystyk transportnykh potokiv na vulytsiakh mista. Visnyk KhNADU, 50, 80–83.
  15. Levterov, A., Denisenco, O., Yaruta, A. (2013). Determination of transport delays at signaled crossing. Vestnik Kharkivskoho natsional'nogo avtomobil'no-dorozhnogo universiteta, 61-62, 106–109.

Downloads

Published

2020-02-29

How to Cite

Postranskyy, T., Boikiv, M., Afonin, M., & Rogalskyi, R. (2020). Selection of a traffic management scheme at an intersection taking into consideration the traffic flow composition. Eastern-European Journal of Enterprise Technologies, 1(3 (103), 39–46. https://doi.org/10.15587/1729-4061.2020.195327

Issue

Section

Control processes