A framework for realistic vehicular network modeling using planet-scale public webcams
Realistic design and evaluation of vehicular mobility has been particularly challenging due to a lack of large-scale real-world measurements in the research community. Current mobility models and simulators rely on artificial scenarios and use small and biased samples. To overcome these challenges, we introduce a novel framework for large-scale monitoring, analysis, modeling, and visualization of vehicular traffic using freely available online webcams. We follow a data-driven approach that examine six metropolitan regions' more than 800 locations and 25 million vehicular mobility records around the world. Initial analysis of traffic densities show 80% temporal correlation during various hours of a day. The modeling of empirical traffic densities against known theoretical models show less than 5% deviation for heavy-tailed distributions such as Weibull. We believe this framework and the dataset provide a much-needed contribution to the research community for realistic and data-driven design and evaluation of vehicular networks.