Development of a traffic decongestion model at Constantine city to improve urban mobility: case of the Zouaghi Slimane crossroad (Algeria)

Authors

DOI:

https://doi.org/10.15587/2706-5448.2024.319674

Keywords:

traffic road, modelling traffic congestion, critical flows, traffic dynamic management, regulate traffic urban

Abstract

The object of the study is modeling traffic congestion. For modeling traffic congestion in the aim to get better fluidity of road traffic mainly in urban areas, it is necessary to use powerful computers, ahead the complexity of the task. Because, road traffic is a complex phenomenon especially at crossroads, firstly due to the high number of users who use it, secondly the nature of the crossroads which have a complex mesh network. In this paper, a mathematical approach based on the Greenshield model who interested in the study of traffic performance at crossroads is developed. This model permit to control and regulate traffic urban which must meet various objectives like: minimizing wait times for vehicles at crossroads, optimization of traffic flows on the road network. The application treated in this papier is the Zouaghi Slimane crossroads of Constantine city (Algeria). According obtained results, the time spent at crossroads Zouaghi Slimane can reach more than 45 minutes and more for day. This situation brings to asking the following question: how to reduce the travel time lost at this crossroads? To give the answer at this last question, the first step is to considering the different variables that characterize the progressive movement of vehicles on a road. In the objective to give a mathematical formulation, which links, the number of vehicles present at time t over a length L of the road. Speed is one of the basic parameters of traffic flow, the relationship between the fundamental parameters of traffic considers the different variables that characterize the progressive movement of vehicles on a road permit to give a mathematical formulation which links the number of vehicles present at time “t” over a length “L” of the road. The main objective is to bring out indicators such as speeds, density and critical flows allowing to set up a dynamic management of the traffic, for a decongestion the crossroads Zouaghi Slimane.

Author Biographies

Salim Boukebbab, Constantine 1 University, Mentouri Brothers

Professor

Laboratory of Transport Engineering and Environment

Department of Engineering Transportation

Billal Soulmana, Constantine 1 University, Mentouri Brothers

Assistance Professor

Laboratory of Transport Engineering and Environment

Department of Engineering Transportation

Mounira Kelilba, Constantine 1 University, Mentouri Brothers

PhD

Laboratory of Transport Engineering and Environment

Department of Engineering Transportation

References

  1. Forstall, R. L., Greene, R. P., Pick, J. B. (2009). Which are the largest? Why lists of major urban areas vary so greatly. Tijdschrift Voor Economische En Sociale Geografie, 100 (3), 277–297. https://doi.org/10.1111/j.1467-9663.2009.00537.x
  2. Greene, R. P., Pick, J. B. (2012). Exploring the Urban Community: A GIS Approach. Pearson Prentice Hall, 432.
  3. Abdo, J. (2011). Construire de nouvelles infrastructures routières. La solution to la congestion du trafic ? Centre d’inforamtion sur le ciment et ses application. Available at: https://www.infociments.fr/route/t32-construire-de-nouvelles-infrastructures-routieres
  4. Ujjwal, J., Bandyopadhyaya, V., Bandyopadhyaya, R. (2021). Identifying key determinants for parking management to reduce road traffic congestion for congested cities-A Structural Equation Modelling approach. Advances in Transportation Studies, 54, 143–158.
  5. Pick, J. B., Azari, R. (2008). Global digital divide: Influence of socioeconomic, governmental, and accessibility factors on information technology. Information Technology for Development, 14 (2), 91–115. https://doi.org/10.1002/itdj.20095
  6. Weisbrod, G., Vary, D., Treyz, G. (2003). Measuring Economic Costs of Urban Traffic Congestion to Business. Transportation Research Record: Journal of the Transportation Research Board, 1839 (1), 98–106. https://doi.org/10.3141/1839-10
  7. Apte, J. S., Bombrun, E., Marshall, J. D., Nazaroff, W. W. (2012). Global Intraurban Intake Fractions for Primary Air Pollutants from Vehicles and Other Distributed Sources. Environmental Science & Technology, 46 (6), 3415–3423. https://doi.org/10.1021/es204021h
  8. Lighthill, M. J., Whitham, G. B. (1955). On kinematic waves I. Flood movement in long rivers. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 229 (1178), 281–316. https://doi.org/10.1098/rspa.1955.0088
  9. Richards, P. I. (1956). Shock Waves on the Highway. Operations Research, 4 (1), 42–51. https://doi.org/10.1287/opre.4.1.42
  10. Greenshields, B. D., Bibbins, J. R., Channing, W. S., Miller, H. H. (1935). A study of traffic capacity. Highway Research Board proceedings. Available at: https://www.safetylit.org/citations/index.php?fuseaction=citations.viewdetails&citationIds[]=citjournalarticle_248667_38
  11. Payne, H. J. (1971). Model of Freeway Traffic and Control. Mathematical Model of Public System, 1 (1), 51–61.
  12. Fares, B., Kechida, S., Bencheriet, C. ennehar. (2013). Modélisation d’un Reseau du Trafic Urbain par Automate Hybride. Proceedings of Conference International Conference on Systems and Information Processing. Guelma. https://doi.org/10.13140/RG.2.2.31132.90241
  13. Geroliminis, N., Sun, J. (2011). Properties of a well-defined macroscopic fundamental diagram for urban traffic. Transportation Research Part B: Methodological, 45 (3), 605–617. https://doi.org/10.1016/j.trb.2010.11.004
  14. Treiber, M., Kesting, A., Helbing, D. (2010). Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts. Transportation Research Part B: Methodological, 44 (8-9), 983–1000. https://doi.org/10.1016/j.trb.2010.03.004
  15. Khelf, M., Boukebbab, S., Boulahlib, M. S.; Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (Eds.) (2016). A Mathematical Model to Regulate Roads Traffic in Order to Decongest the Urban Areas of Constantine City. Dependability Engineering and Complex Systems. Cham: Springer International Publishing, 279–289. https://doi.org/10.1007/978-3-319-39639-2_24
  16. Guo, Y. R., Wang, X. M., Wang, M., Zhang, H. (2020). Research on prediction of urban congestion based on radial basis function network. Advances in Transportation Studies, Special Issue 1, 145–156.
  17. Wang, H. X., Zheng, H. J. (2021). Prediction method of traffic congestion volume in traffic jam road section based on genetic algorithm. Advances in Transportation Studies, Special Issue 2, 79–90.
  18. Lidbe, A., Tedla, E., Hainen, A., Sullivan, A., Jones Jr, S. (2017). Comparative assessment of arterial operations under conventional time-of-day and adaptive traffic signal control. Advances in Transportation Studies, 42, 5–22.
  19. Mathew, T. V. (2017). Fundamental Relations of Traffic Flow. Lecture Notes in Transportation Systems Engineering. IIT Bombay.
  20. Mathew, T. V., Krishna Rao, K. V. (2007). Introduction to Transportation Engineering. Lecture Notes in Transportation Systems Engineering.
  21. Greenshields, B. D., Shapiro, D., Erickson, E. L. (1947). Traffic performance at urban street intersections. Tech. Rep. No. 1, Yale Bureau of Highway Traffic. New Haven: Yale University.
Development of a traffic decongestion model at Constantine city to improve urban mobility: case of the Zouaghi Slimane crossroad (Algeria)

Downloads

Published

2024-12-31

How to Cite

Boukebbab, S., Soulmana, B., & Kelilba, M. (2024). Development of a traffic decongestion model at Constantine city to improve urban mobility: case of the Zouaghi Slimane crossroad (Algeria). Technology Audit and Production Reserves, 6(2(80), 28–34. https://doi.org/10.15587/2706-5448.2024.319674

Issue

Vol. 6 No. 2(80) (2024): Information and control systems

Section

Systems and Control Processes

License

Copyright (c) 2024 Salim Boukebbab, Billal Soulmana, Mounira Kelilba

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.