An Integrated Model to Control Traffic Lights: Controlling of Traffic Lights in Multiple Intersections using Fuzzy Logic and Genetic Algorithm

Authors

  • Khaled Abdul Rahman Jomaa Faculty of Industrial Management, University Malaysia Pahang, 26300, Pahang
  • Cheng jack Kie

Keywords:

Traffic Light, Fuzzy Logic, Genetic Algorithm, Congestion, Malaysia

Abstract

In this paper we propose an integrated model combines Fuzzy Logic (FL) and Genetic Algorithm (GA), utilizing their applications in order to minimize the traffic congestion and traffic delay, through controlling traffic light system in three proposed traffic intersections. The proposed model in this paper will adjust the timing and phasing of the green traffic lights according to the current situation in the proposed traffic intersections; each intersection is supposed to be controlled by traffic signals that will apply the model. The green light interval time length shall provide at an intersection will be decided by FL. the outputs of FL will be optimized by GA, in order to obtain a higher performance. This performance can be measured considering the reduction in the waiting time and the total amount of vehicles that arrived to the Queue of the three intersections. The proposed model expected to provide a significant improvement to the traffic light system performance which might be very important to be applied in the metropolitan areas in Malaysia.

aper will adjust the timing and phasing of the green traffic lights according to the current situation in the proposed traffic intersections;each intersection is supposed to be controlled by traffic signals that will apply the model. The green light interval time length shall provide at an intersection will be decided by FL. the outputs of FL will be optimized by GA, inorder to obtain a higher performance. This performance can be measured considering the reduction in the waiting time and the total amount of vehicles that arrived to the Queue of the three intersections. The proposed model expected to provide a significant improvement to the traffic light system performance which might be very important to be applied in the metropolitan areas in Malaysia.

References

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[ ]-Khaled Abdul Rahman Jomaa, "Google Forms ." Google. 6 17, 2016. https://docs.google.com/forms/d/16VkbGXnU_eAXZ37ZbABYnN37hLs-q5tWR68bf0-Qfbw/viewform?edit_requested=true (accessed 11 15, 2016)

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[ ]-Mojtaba Salehi et. al. “TLCSBFL: A Traffic Lights Control System Based on Fuzzy Logicâ€, International Journal of u- and e- Service, Science and Technology Vol.7, No.3, pp.27-34,2014.

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[ ] A. M.Turky, M. Sh. Ahmad and M. Z. Mohd Yusoff,. "The Use of Genetic Algorithm for Traffic Light and Pedestrian Crossing Control." IJCSNS International Journal of Computer Science and Network 88 Security, VOL.9 No.2, 2009: 88-96.

[ ] Ahmed A. Ezzat, et al. “Development of a Stochastic Genetic Algorithm for Traffic Signal Timings Optimizationâ€, Industrial and Systems Engineering Research Conference, 2014.

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Published

2017-02-15

How to Cite

Jomaa, K. A. R., & Kie, C. jack. (2017). An Integrated Model to Control Traffic Lights: Controlling of Traffic Lights in Multiple Intersections using Fuzzy Logic and Genetic Algorithm. Asian Journal of Business and Management, 5(1). Retrieved from https://www.ajouronline.com/index.php/AJBM/article/view/4120