A Two-Level Information and Analytical Control System for Intelligent Traffic Lights

Problems that arise in the field of traffic are of great importance. To solve existing problems, various intelligent systems are being developed, one of which is the Smart City system. This work is devoted to the development of an information and analytical system (IAS) for controlling an intelligent traffic light. The presented system consists of two levels, each of which contains a set of specific operations. The first level is responsible for detecting objects, in particular pedestrians and cars at an intersection, and the second level calculates the operating time of traffic light signals for the control signal that is transmitted to the device. For comparative analysis, the combined method histogram of oriented gradients + support vector machines (HOG+SVM). HOG was chosen, based upon counting the number of gradient directions on individual image areas, and SVM were used to construct hyperplanes in n-dimensional space to separate objects belonging to different classes. The results of an experimental study, om which the recognition of objects in images was carried out, showed the superiority of the developed information and analytical system over existing methods. The average accuracy of detecting pedestrians and cars through the IAS was 69.4%. In addition, the experiment showed that the accuracy of detecting objects in images is directly proportional to the distance from the video camera to the object.