Unreliable Road Network Traffic Detection and Prevention

Abstract

Traffic in the road network acting a major role in the society. Everyday traffic is increased because of moving vehicles in the shortest path even though government handle traffic signal is based on the timing condition. Because of that travel time is increased from source to destination. The existing system handles the vehicular traffic using a two stage routing algorithms are time dependent landmark graph model is used to estimate travel time between two landmarks and the next stage is variance entropy based clustering model is used to estimate the distribution of travel time between two landmarks in different time slots. By using this algorithm, cannot estimate the speed pattern of the road segment and traffic has not been predicted and prohibited. To address these limitations a proposed system uses two ways are one is weight propagation model, the weights that captures the travel time and traffic can be extracted from the GPS (Global Positioning System) trajectory data collected from the network and another one ant colony optimization algorithm to estimate the optimal path apart from the traffic. Using this proposed algorithm the road network traffic has been detected and prevented.