Towards modeling the traffic data on road networks

A spatiotemporal network is a spatial network (e.g., road network) along with the corresponding time-dependent weight (e.g., travel time) for each edge of the network. The design and analysis of policies and plans on spatiotemporal networks (e.g., path planning for location-based services) require realistic models that accurately represent the temporal behavior of such networks. In this paper, for the first time we propose a traffic modeling framework for road networks that enables 1) generating an accurate temporal model from archived temporal data collected from a spatiotemporal network (so as to be able to publish the temporal model of the spatiotemporal network without having to release the real data), and 2) augmenting any given spatial network model with a corresponding realistic temporal model custom-built for that specific spatial network (in order to be able to generate a spatiotemporal network model from a solely spatial network model). We validate the accuracy of our proposed modeling framework via experiments. We also used the proposed framework to generate the temporal model of the Los Angeles County freeway network and publish it for public use.