Road Traffic Forecasting through Simulation and Live GPS-Feed from Intervehicle Networks

Any disaster management requires sending emergency aids to the affected areas in an earliest possible time. In urban areas, high traffic volume is an impediment for efficient transportation of such goods and services. In this paper, we present a traffic flow forecasting model that may help emergency service delivery. In our approach, we used a microscopic traffic simulator with live vehicle statistics collected from intervehicle networks. The use of traffic simulator based technique enables repetitive exploration of different route planning options ahead of time. The simulator is also helpful for a comprehensive representation of urban road network. In this work, we have also designed and implemented necessary hardware and software tools for traffic data collection, which gives full control on the data collection mechanism. Our approach has been tested in a large university campus where all constraints of a modern city are present. The study shows promising results of our approach.