Traffic Light Control Utilizing Queue Length

Road traffic congestion in modern cities has become essential problem which need to be solved. To solve this problem, we have proposed a dynamic traffic light controller system based on image processing. Images (the road-images) used in this research are taken by digital camera placed at fixed position in the traffic-light with specific resolution and distance. The taken images will be analyzed to identify the traffic load. To perform image analysis, at first, we will extract the foreground objects from the image, and remove noisy small objects. In the next step, find cars-queue length on the road depending on the distance between the two end points on the road lane. To measure the queue length, edge detection and segmentation are needed. Finally, we suggest an equation to find out the estimated time and actual time to determine the estimated time reference for optic Green. Road-Images are classified into two types, high density images and low density images, depending on number of vehicles on the road. By testing the suggested system, we found that, making control decision on the traffic-light based on the length of the cars-queue is more suitable when there is large number of vehicles on the road (high density images). To verify the efficiency of the suggested system, the experimental results of the suggested system are compared with the performance of the original traffic-light control system. The suggested cars-queue length technique proved efficient.