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.

In this paper, an Adaptive Dynamic Scheduling Algorithm (ADSA) based on Artificial Bee Colony (ABC) was developed for vehicular traffic control. The developed model optimally scheduled green light timing in accordance with traffic condition 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. In order to demonstrate the effectiveness of the developed ADSA this paper was validated with the existing work in the literature. The result obtained for the AWT of the developed ADSA had a performance of 76.67%. While for vehicular queues cleared at the intersection the developed ADSA had a performance of 53.33%. The results clearly expressed that the developed ADSA method has been successful in minimizing the Average Waiting Time and vehicular queues at the intersection.