Self Awareness and Adaptive Traffic Signal Control System for Smart World

The intelligent and self-adaptive urban traffic signal control (TSC) system has become a development trend of intelligent transportation system (ITS). The most city dwellers are concerned with the urban traffic issues very much. So, to provide a self awareness and adaptive facilities in traffic signal control system is become more and more urgent. However, many roadway and traffic applications have not been tapped: primarily sensor networks for highway and traffic algorithms that alleviate generic problems such as roadway congestion. This is due to the fact that sensor network technology (as well as imagers and microradars) is a very recent development. Since sensor networks are relatively new, not many applications have been explored in depth. In this paper, we proposed 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 visionbased 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 improves the traffic queuing situation, we confirmed the efficiency of our vision based smart TSC approach.