A predictive road traffic management system based on vehicular ad-hoc network

With an increasing number of vehicles on the road, demand for intelligent transportation systems is on the rise. In this paper, we present a predictive road traffic management system (PRTMS) based on the Vehicular Ad-hoc Network (VANET) architecture. The proposed PRTMS uses a novel communications scheme to estimate the future traffic intensities at different intersections based on a modified linear prediction algorithm. Based on the prediction, a central controller reduces the congestion level by re-routing the vehicles and adaptively changing the signaling cycles. An IEEE 802.11p based vehicle to-infrastructure communications system is used to collect trip information and transmit control signals to enforce multi-junction traffic flow control. Simulations are conducted using an integrated OPNET model comprised of road infrastructure, vehicular mobility management and communications networking to jointly examine the performances of the proposed PRTMS and the VANET. The results indicate that the proposed scheme provides a significant performance improvement in terms of total journey time and waiting time of the vehicles. In addition, the performance of the prediction algorithm is also investigated.