International Journal of

Automation and Smart Technology

Ali Wided1*, Brek Assia1, and Bouakkez Fatima1

1Institute of science and technology, Echahid Cheikh Larbi Tebessi University, Tebessa, 12200, Algeria

 

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ABSTRACT

Traffic congestion becomes a serious problem when there are many vehicles on the roadways. The queue of vehicles waiting to be treated at intersections increases significantly as road traffic increases, and traditional traffic lights are unable to handle it. The synchronization mechanism used by traditional circulation lighting systems changes light signals after a certain interval. This method is used when the roads are nearly empty. An intelligent traffic light system detects the presence, estimates the level of traffic, and reacts appropriately. Intelligent traffic systems are designed to prevent cars from impatiently waiting at traffic lights to change their signals when there are free roads. In this study, we develop a simulator in which a traffic grille made of traffic lights is constructed at intersections resembling those in large cities, and the flow of vehicles through the grid is optimized by developing algorithms for how traffic lights change their state. To maximize vehicle movement over the grid, scheduling algorithms are being developed to control how road traffic changes. Because of the encouraging response to our models, we were able to achieve good results that reduced the waiting time by 30% compared to the default model.


Keywords: Smart city; Scheduling; Road traffic; Traffic lights; Traffic Congestion; Multi Agent system.


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REFERENCES

  1. [1] P. Chamoso, A. González Briones, S. Rodríguez, and J.M. Corchado, “Tendencies of technologies and platforms in smart cities: a state of the art review,” Wireless Communications and Mobile Computing, vol. 2018, pp. 1–17, 2018. https://doi.org/10.1155/2018/308685

  2. [2] H. Younes ,B. Omar B, Y. Mohamed ,I. Elhocein, "Application model of tasks scheduling problem in distributed systems solving problems of road traffic planning in smart cities", Third International Conference on Intelligent Computing in Data Sciences (ICDS), Marrakech, Morocco, October 28-30, 2019, pp. 1–7. https://doi.org/10.1109/ICDS47004.2019.8942310

  3. [3] N. Shahid, M.A. Shah, A. Khan, C. Maple, G. Jeon, "Towards Greener Smart Cities and Road Traffic Forecasting Using Air Pollution Data", Sustainable Cities and Society, Vol.72, no. 4 , pp. 103062 ,2021. https://doi.org/10.1016/j.scs.2021.103062

  4. [4] S.R .Shyam, R. Logesh , "Real Time Adaptive Traffic Control System for Smart Cities". International Conference on Computer Communication and Informatics, Coimbatore, India, January 27-29, 2021, pp. 1-6. https://doi.org/10.1109/ICCCI50826.2021.9402597

  5. [5] J. Hyunjin , H.A. Syed, L. Yujin ," Traffic signal control for smart cities using reinforcement learning" Computer Communications, Vol. 154, pp. 324–330, 2020. https://doi.org/10.1016/j.comcom.2020.03.005

  6. [6] B. Nabila, Z.Salah, O. Mawloud ,"Context aware negotiation, reputation and priority traffic light management protocols for VANET based smart cities", Telecommun System, Vol. 72, pp. 131–153, 2019. https://doi.org/10.1007/s11235-019-00555-x

  7. [7] M. Roopa ,S. Ayesha,B. Rajkumar ,K.R. Venugopal, S.S. Iyengard ,L.M. Patnaike, "Dynamic Management of Traffic Signals through Social IoT", Procedia Computer Science,Vol. 171, pp. 1908–1916, 2020. https://doi.org/10.1016/j.procs.2020.04.204

  8. [8] D.R. Aleko , S. Djahel , " An Efficient Adaptive Traffic Light Control System for Urban Road Traffic Congestion Reduction in Smart Cities". Information, Vol. 11, no. 2, pp.119 , 2020. https://doi.org/10.3390/info11020119

  9. [9] H. Joo , S. H. Ahmed, Y. Li m, " Traffic signal control for smart cities using reinforcement learning", Computer Communications, Vol. 154, pp. 324– 330, 2020. https://doi.org/10.1016/j.comcom.2020.03.005

  10. [10] W.H. Lee, C.Y. Chiu, "Design and Implementation of a Smart Traffic Signal Control System for Smart City Applications", Sensors, Vol.20, no.2, pp. 508, 2020. https://doi.org/10.3390/s20020508

  11. [11] S. Neelakandan, M.A. Berlin, S. Tripathi, " IoT based traffic prediction and traffic signal control system for smart city", Soft Computing, Vol. 25, pp. 12241–12248, 2021. https://doi.org/10.1007/s00500-021-05896-x

  12. [12] Simulation of urban mobility http://sumo.sourceforge.net/

  13. [13] M.B. Younes, A.Boukerche," Intelligent traffic light controlling algorithms using vehicular networks", IEEE Transaction on Vehicular Technology , Vol. 65, no. 8 ,pp. 5887–5899, 2016. https://doi.org/10.1109/TVT.2015.2472367

  14. [14] K. Pandit, D. Ghosal, H.M. Zhang,C.N. Chuah, " Adaptive traffic signal control with vehicular ad hoc networks", IEEE Transactions on Vehicular Technology, Vol. 62, no. 4, pp. 1459–1471, 2013. https://doi.org/10.1109/TVT.2013.2241460


ARTICLE INFORMATION

Received: 2023-05-02
Revised: 2023-06-04
Accepted: 2023-06-04
Available Online: 2023-06-04


Cite this article:

Wided, A., Assia, B., and Fatima, B. (2023) Traffic Management system and Traffic Light Control in Smart City to Reduce Traffic Congestion. Int. j. autom. smart technol. https://doi.org/10.5875/ausmt.v13i1.2464

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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