Traffic signaling control at highway intersections using morphological image processing technique

Nowadays, the result of growing population in intercity areas vehicle traffic congestions become an important issue to be solved. For the solution of this problem various methods and techniques have been suggested in many recent studies. Any preventive measure to ease traffic flow along the roads is valuable to save time and fuel wastage, and also reducing CO and CO2 emissions. In this thesis, we attempt to implement the morphological image processing technique on the images obtained from a simulated junction model. The comparisons of different images are made from the matching score results to decide green light signaling duration for each road of the junction. During implementation of the morphological image processing technique we focus on the individual effect of each operator to improve the accuracy of matching scores. Since we are basically interested in the area occupied by the vehicles, it is observed that ignoring edge detection operator does not produce any loss in the image quality, but rather increases the accuracy of image matching scores resulted from long vehicles, daylight and seasonal variations. The results indicate that data of matching scores for each road provides a successful decision for the green signaling duration at different daytime periods. The method suffers from vehicles having dark colors, since they are accounted as a part of the road. Suggested future work involves the implementation of the procedure for live traffic at a junction and eliminating the problem resulted from colored vehicles under different weather conditions.