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Transportation Analysis and Decision Science

Providing a systems view of sustainable transportation
 

The Transportation Analytics and Decision Sciences seeks to find sustainable multi-modal (air, land, water, pipelines) solutions to passenger and freight transportation challenges within the broad context of environmental, social, and economic goals. The group relies on individuals and teams with multi-disciplinary skills—mathematics, statistics, engineering, computer science, economics, operations research, data analytics, geography, psychology, and other disciplines.  Research teams apply statistical and econometric modeling, machine learning, simulation, and optimization methods to data-intensive analyses.  The resulting data sets and models seek to illuminate historical performance of the transportation system with multiple metrics, to predict future performance under various scenarios and to search for optimal pathways to sustainable futures.   

The goal is to help public and private decision makers envision the future demand for transportation, how alternative approaches along with their potential obstacles and risks address the demand, and what are the most sustainable pathways forward.  This help may come in the form of data on freight and passenger movements, predictions of the adoption rate for a new technology such as electric vehicles, or models of the optimal build-out of new transportation related infrastructure such as highways, locks and dams, electric charging stations, and intermodal infrastructure.  In addition to traditional research reports and journal articles, the group produces maps, interactive data visualizations, and a variety of online resources such as The Transportation Energy Data Book, the Freight Analysis Framework, the National Household Travel Survey, and FuelEconomy.gov.  These are used internationally by researchers, transportation planners, policy makers, and the general public.