Self Awareness and Adaptive Traffic Signal Control System for Smart World

The most city dwellers are concerned with the urban traffic issues very much. To provide a self awareness and adaptive facilities in traffic signal control system is become more and more urgent. In this paper, we improved the video surveillance and self-adaptive urban traffic signal control system to achieve the development trend in intelligent transportation system (ITS). A self awareness and adaptive urban traffic signal control (TSC) system that could provide both the video surveillance and the traffic surveillance as smart hyperspace. We investigated the vision-based surveillance and to keep sight of the unpredictable and hardly measurable disturbances may perturb the traffic flow. We integrated and performed the vision-based methodologies that include the object segmentation, classify and tracking methodologies to know well the real time measurements in urban road. According to the real time traffic measurement, we derived a grid Agent Communication and the Adaptive Traffic Signal Control strategy to adapt the traffic signal time automatically. By comparing the experimental result obtained by traditional traffic signal control system which improved the traffic queuing situation, we confirmed the efficiency of our vision based smart TSC approach.