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Average Waiting Time, Artificial Bee colony, Queue Length, Graphic User Interface (GUI) and Congestion
This paper proposes an adaptive traffic control system that dynamically manages traffic phases and durations at cross-intersection. The developed model optimally schedules green light timing in accordance with traffic condition on each lane in order to minimize the Average Waiting Time (AWT) at the cross intersection. A MATLAB based Graphic User Interface (GUI) traffic control simulator was developed. Three scenarios of vehicular traffic control were simulated and the results presented. The results show that scenario one and two demonstrated the variation of the AWT and Performance of the developed algorithm with changes in the maximum allowable green light timing over the simulation interval. In the third scenario, an AWT of 38sec was recorded against a maximum allowable green light duration of 120sec, during which 1382 vehicles were evacuated from the intersection, leaving 22 vehicles behind. The algorithm also had a performance of 98.43% over a simulation duration of 1800sec.
Risikat Folashade Adebiyi, Kabir Ahmad Abubilal, Muhammad Bashir Mu’azu, Busayo Hadir Adebiyi, "Development and Simulation of Adaptive Traffic Light Controller Using Artificial Bee Colony Algorithm", International Journal of Intelligent Systems and Applications(IJISA), Vol.10, No.8, pp.68-74, 2018. DOI:10.5815/ijisa.2018.08.06
Cosariu, C., L. Prodan, and M. Vladutiu. Toward traffic movement optimization using adaptive inter-traffic signaling. in Computational Intelligence and Informatics (CINTI), 2013 IEEE 14th International Symposium on. 2013. IEEE.
Subramaniam, S., M. Esro, and F. Aw, Self-Algorithm Traffic Light Controllers for Heavily Congested Urban Route. WSEAS Transactions on Circuits and Systems, 2012. 11(4): p. 115-124.
Odeh, S.M., Management of an intelligent traffic light system by using genetic algorithm. Journal of Image and Graphics, 2013. 1(2): p. 90-93.
Mittal, P.K. and Y. Singh, Analysis and designing of proposed intelligent road traffic congestion control system with image mosaicking technique. International Journal of IT, Engineering and Applied Science Research (IJIEASR) Vol, 2013. 2: p. 27-31.
Faye, S., C. Chaudet, and I. Demeure. A distributed algorithm for adaptive traffic lights control. in Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on. 2012. IEEE.
Salehi, M., I. Sepahvand, and M. Yarahmadi, TLCSBFL: A Traffic Lights Control System Based on Fuzzy Logic. International Journal of u-and e-Service, Science and Technology, 2014. 7(3).
Wang, F., et al., Simulation Analysis and Improvement of the Vehicle Queuing System on Intersections Based on MATLAB. Open Cybernetics & Systemics Journal, 2014. 8: p. 217-223.
Erwan, E.P., W. Oyas, and S. Selo, Design and Simulation of Adaptive Traffic Light Controller Using Fuzzy Logic Control Sugeno Method. International Journal of Scientific and Research Publications, 2015. 5(4): p. 6.
Alam, J., Advance traffic light system based on congestion estimation using fuzzy logic. 2014.
Gündoğan, F., et al., An Evaluation of Adaptive Traffic Control System in Istanbul, Turkey. Journal of Traffic and Logistics Engineering Vol, 2014. 2(3).
Karaboga, D., et al., A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Review, 2014. 42(1): p. 21-57.
Adebiyi, R.F., et al., Management of Vehicular Traffic System Using Artificial Bee Colony Algorithm. International Journal of Images, Graphics and Signal Processing 2017. 9(11): p. 18-28.
Priti Bansal, S.S. and Nitish Mittal, A Hybrid Artificial Bee Colony and Harmony Search Algorithm to Generate Covering Arrays for Pair-wise Testing. International Journal of Intelligent Systems and Applications (IJISA), 2017. 9(8): p. 59-70.
Aljaafreh, A. and N. Al Oudat. Optimized Timing Parameters for Real-Time Adaptive Traffic Signal Controller. in Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on. 2014. IEEE.
Pau, G. and G. Scata, Smart traffic light junction management using wireless sensor networks. WSEAS transactions on communication, 2014. 14: p. 2224-2864.