WORKING PRINCIPLE AND PERFORMANCE EVOLUTION OF CAMERA-BASED INTELLIGENT SIGNALIZED INTERSECTIONS: SAMSUN CITY, TÜRKIYE EXAMPLE

Abstract

In the current literature, it is clearly seen that most of the traffic chaos is generally observed at intersections of the urban roads in cities. On the other hand, many current traffic studies and research prove that fixed-time signalized intersections cannot have a good ability to control and manage current traffic flow at signalized intersection legs. For this aim, intelligent intersections were developed and started to be used in many cities all over the world in the last decade. These new intelligent intersection systems suggest dynamic signal times for all intersection legs by using real-time measured traffic data. These systems generally use cameras or loop detectors, which are located in the proper places on a signalized intersection leg and record vehicle movements. Within the scope of this study, a performance comparison was made for before and after the camera-based intelligent intersection applications at three isolated pilot signalized intersections within the scope of the "Smart City Traffic Safety" project, which is one of the largest Intelligent Transportation System projects in Turkey. After the system was activated, it was observed that the drivers had impatient behaviors in the beginning and had difficulty getting used to these new systems. After the signal cycle was regulated with the learning of artificial intelligence, it was seen that the drivers had more patience and more observant behaviors. It was also obtained from the analysis results that these new intelligent systems resulted in an average 16% decrease in control delays and a 20% decrease in vehicle speeds.