Skip to main navigation menu Skip to main content Skip to site footer
International Journal of Robotics and Automation Technology

Articles

Vol. 9 (2022)

Design and Implementation of a Traffic Control System Based on Congestion

DOI
https://doi.org/10.31875/2409-9694.2022.09.09
Submitted
December 5, 2022
Published
05.12.2022

Abstract

Abstract: The traffic issues have garnered more and more attention on a global scale as the number of cars has grown. One of the biggest problems is the traffic congestion, also the fixed-time settings are still used by the majority of traffic systems today. These technologies are unable to dynamically alter the timing of traffic lights in response to heavy traffic. Thanks to technological advancements, sensors or cameras can now collect data on traffic volume and wait times. This study provided an illustration of a traffic light control system that can manage traffic according to the number of vehicles in each road. Additionally, it showed how the system was designed using the Proteus design suite software and how a prototype of the system was implemented using an Arduino Mega 2560 and an infrared sensor. Through the results obtained, the efficiency of the proposed system is clear by comparing it with the system that depends on the fixed time of traffic signals.

References

  1. Morten Jensen, Mark Philipsen, Andreas Møgelmose, Thomas Moeslund, and Mohan Trivedi,Vision for Looking at Traffic Lights: Issues, Survey, and Perspectives. IEEE transactions on intelligent transportation systems, 2016; 17(7). https://doi.org/10.1109/TITS.2015.2509509
  2. A. Vahidi and A. Eskandarian, "Research advances in intelligent collision avoidance and adaptive cruise control," IEEE Trans. Intel. Transport. Syst. 2003; 4(3): 143-153. https://doi.org/10.1109/TITS.2003.821292
  3. E. Brockfeld, R. Barlovic, A. Schadschneider, and M. Schreckenberg, "Optimizing traffic lights in a cellular automaton model for city traffic," Phys. Rev. E, 2001; 64(5). https://doi.org/10.1103/PhysRevE.64.056132
  4. DW. Huang and WN. Huang, "Traffic signal synchronization," Phys. Rev. E, 2003; 67(5). https://doi.org/10.1103/PhysRevE.67.056124
  5. C. Gershenson, "Self-organizing traffic lights," Complex Syst. 2005; 16(1): 29-53.
  6. K. Dresner and P. Stone, "A multiagent approach to autonomous intersection management," J. Artificial Intel. Res. 2008; 31: 591-656. https://doi.org/10.1613/jair.2502
  7. M. Van Middles worth, K. Dresner, and P. Stone, "Replacing the stop sign: unmanaged intersection control for autonomous vehicles," in Proc. 5th Workshop Agents Traffic Transport. Multiagent Syst., Estroil, Portugal, 2008; pp. 94-101.
  8. MM. Edardar and Ahmed J. Abougarair, Adaptive Traffic Light Dynamic Control Based on Road Traffic Signal from Google Maps, ICEMIS'21, October 11-13, 2021, Almaty, Kazakhsta. https://doi.org/10.1145/3492547.3492584
  9. He Z, Guan W, Ma S. A traffic-condition-based route guidance strategy for a single destination road network. Transp. Res. Part C Emerg. Technol, 2013; 32: 89-102. https://doi.org/10.1016/j.trc.2013.04.005
  10. Mekki T, Jabri I, Rachedi A, ben Jemaa M. Vehicular cloud networks: Challenges, architectures, and future directions. Veh. Comm., 2017; pp. 268-280. https://doi.org/10.1016/j.vehcom.2016.11.009
  11. Michel Ferreira and Pedro Orey.2012. On the Impact of Virtual Traffic Lights on Carbon Emissions Mitigation. IEEE transactions on intelligent transportation systems, 2012; 13(1). https://doi.org/10.1109/TITS.2011.2169791
  12. Ahmed J. Abougarair Design and implementation of smart voice assistant and recognizing academic words, International Robotics & Automation Journal 2022; 8(1): 27-32.
  13. Mohamed Edardar, Ahmed J. Abougarair, Lyapunov Redesign of Piezo-Actuator for Positioning Control, 2021 9th International Conference on Systems and Control (ICSC), PP. 499-503, France, 2021. https://doi.org/10.1109/ICSC50472.2021.9666594
  14. E. Brockfeld, R. Barlovic, A. Schadschneider, and M. Schreckenberg. Optimizing traffic lights in a cellular automaton model for city traffic. Phys. Rev. E, 2001; 64(5). https://doi.org/10.1103/PhysRevE.64.056132
  15. D. Huang and W. Huang.2003. Traffic signal synchronization. Phys. Rev. E, vol. 67, no. 5, 2003. https://doi.org/10.1103/PhysRevE.67.056124
  16. Nagmden M. Nasser and Ahmed J. Abougarair, Traffic Sign Classification Using Deep Learning Based Convolutional Neural Networks, Azzaytuna University Journal, 2022; 3(4): 2, PP. 303-326.
  17. K. Dresner and P. Stone, A multiagent approach to autonomous intersection management. J. Artificial Intel. Res., vol. 31, pp. 591-656, 2008. https://doi.org/10.1613/jair.2502
  18. M. worth, K. Dresner, and P. Stone, Replacing the stop sign: unmanaged intersection control for autonomous vehicles. in Proc. 5th Workshop Agents Traffic Transport. Multiagent Syst., Estoril, Portugal, pp. 94-101, May 2008.
  19. U. S. Department of Transportation, Washington, DC. Urban drive control. [Online]. http://www.itsbenefits.its.dot.gov/its/benecost.nsf/ID/876D690DAB8FCA6B8525733A006D5BCC?OpenDocument&Query=BApp.
  20. Mohamed K. Aburakhis, Ahmed J Abougarair, Mohammed Elmaryu, Real time traffic sign detection and recognition for autonomous vehicle, Vol. 8, Issue.2, PP. 82-87, International Robotics & Automation Journal.
  21. H. Guan.2013. A traffic-condition-based route guidance strategy for a single destination road network. Transp. Res. Part C Emerge. Technol, 32, pp. 89-102. https://doi.org/10.1016/j.trc.2013.04.005
  22. T. Mekki and T. Jabri. 2017. Vehicular cloud networks: Challenges, architectures, and future directions. Veh. Comm., pp. 268-280. https://doi.org/10.1016/j.vehcom.2016.11.009
  23. K. Hewage and J. Ruwanpura.2004. Optimization of traffic signal light timing using simulation". In WSC '04: Proceedings of the 36th conference on Winter simulation, pp. 1428-1436.
  24. L. Klein. 2001. Sensor Technologies and Data Requirements for ITS. Artech House Publishers: Norwood, MA, USA.
  25. Ahmed J. Abougarair, Intelligent control designs for linear model of active suspension system International Conference on Microelectronics (ICM), 17-20, 2018. https://doi.org/10.1109/ICM.2018.8703995
  26. Ahmed J Abougarair, Position and Orientation Control of A Mobile Robot Using Intelligent Algorithms Based Hybrid Control Strategies, Journal of Engineering Research, 2022; 34: PP. 67-86.
  27. Ahmed J. Abougarair. Model Reference Adaptive Control and Fuzzy Optimal Controller for Mobile Robot. Journal of Multidisciplinary Engineering Science and Technology (JMEST), 2019; 6(3): 9722-9728.
  28. A. Nicoli, M. Deflorio, F. Chiara and B. Spagnolini. Wireless sensor networks for traffic management and road safety. J. Intel. Transp. Syst. 2012; pp. 67-77, IET 2012. https://doi.org/10.1049/iet-its.2010.0129