Adaptive Traffic Control System using Modified Round Robin and Genetic Algorithm

Nasir Mohammed Sadiq*, Oluwaseun Adeniyi Ojerinde**, Solomon A. Adepoju***
*-*** Department of Computer Science, Federal University of Technology, Minna, Nigeria.
Periodicity:April - June'2018
DOI : https://doi.org/10.26634/jdp.6.2.15592

Abstract

Adaptive Traffic Control System (ATCS) serves as a main element in the constituents with which traffic control flow is achieved in fast developing, and developed urban areas. ATCS, however causes more delays on vehicles due to the fact that it is made up of intersecting points. Ensuring maximum efficiency at intersections has remained a challenge due to its dynamic nature of traffic. Additionally, a number of different methods that can be used to achieve higher performance at road traffic intersections have been recently proposed to engineers. In this study, a new and different method based on modified round robin scheduling algorithm through genetic algorithm technique to optimize the performance (in terms of timing) of a signalized intersection in one of the busiest and most crowded roads of Minna, Niger State – Nigeria (at Obasanjo shopping complex area). The technique uses an initial timing pattern to generate newer offspring (in terms of delay duration) to analyze cost function and to check if a global optimum is reached. This technique outweighs current techniques because the data upon which the nature of the system is built is relatively more phenomenal, as it puts into consideration the exact nature of the lane in many possible occurrences. In this work, a global optimum was reached at only a few number of iteration on the whole Genetic Algorithm process.

Keywords

Component, Optimization, Round Robin, Genetic Algorithm, Signalized Intersection

How to Cite this Article?

Sadiq, N. M., Ojerinde, O. A., & Adepoju, S. A. (2018). Adaptive Traffic Control System using Modified Round Robin and Genetic Algorithm. i-manager's Journal on Digital Signal Processing, 6(2), 17-23. https://doi.org/10.26634/jdp.6.2.15592

References

[1]. Nipa, L. N., & Islam, M. (2015). Intelligent Traffic Control System based on Round. Int. J. Sci. Res. Publ., 5(8),1-8.
[2]. Carr, J. (2015). An Introduction to Genetic Algorithms. senior project, 1-40.
[3]. Gündoğan, F., Karagoz, Z., Kocyigit, N., Karadag, A., Ceylan, H., & Murat, Y. Ş. (2014). An evaluation of Adaptive Traffic Control System in Istanbul. Turkey. J. Traffic Logist. Eng., 2(3), pp-198-201.
[4]. Hasan, M., Saha, G., Hoque, A., & Majumder, B. (2014). Smart Traffic Control System with application of Image Processing Techniques. 3rd Int. Conf. Informatics, Electron. Vis. (pp. 1-4).
[5]. Kabir, A. N., & Salam, K. M. A. (2016). Implementation of an Intelligent Traffic Control System: The use of FPGA and Verilog HDL. J. Mod. Sci. Technol., 4(1), 154-162.
[6]. Mahajan, S., Atiwadkar, A., Patil, K., Lande, T., & Choudhari, P. S. (2016). Universal Network for Intelligent Traffic Control System: Stolen vehicle detection, Emergency vehicle clearance, Fine Collection and Dynamic Traffic Light Control. Int. Res. J. Eng. Technol., 3(6), 543-547.
[7]. Mishra, A., & Singh, K. (2015). Density based Intelligent Traffic Control System using IR Sensors. Int. J. Sci. Res., 4(5), 2277-2278.
[8]. Ou, H., & Wang, Y. (2016). Development of Intelligent Traffic Control System based on Internet of Things and FPGA Technology in PROTEUS, Int. Conf. Educ. Manag. Comput. Soc. (EMCS) (pp. 405-409).
[9]. Pandit, V., Doshi, J., Mehta, D., Mhatre, A., & Janardhan, A. (2014). Smart traffic control system using image processing. Int. J. Emerg. Trends Technol. Comput. Sci. (IJETTCS), 3(1), 280-283.
[10]. Vahedha, & Jyothi, B. N. (2017). Smart traffic control system using ATMEGA328 micro controller and arduino software. Int. Conf. Signal Process. Commun. Power Embed. Syst. SCOPES 2016 - Proc. (pp. 1584-1587).
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.