Exploring Energy-Efficient and Sustainable Urban Mobility Strategies: An Initial Framework to Curate Data/Models, Measure Performance, and Diffuse Innovation: Preprint

Many cities across the United States seek to understand the maturity of data and models that are available to help manage challenges, opportunities, and uncertainties associated with the shifts in technologies, human behaviors and sustainable urban mobility strategies. One key question identified for smart city action planning includes how to best shape continuous improvements for urban populations at the intersection of mobility, energy, and quality of life? With the emerging megatrends of urbanization (more than 70% of world population in cities by 2050), on-demand shared mobility, vehicle electrification, and automated vehicles, initial 'urban science' studies to date have demonstrated the potential and need for maturing the related data and model ecosystems and on-going performance measurement across multiple urban system goals: e.g., from more mobility, clean and efficient energy use, accessibility and safety to less air pollution, traffic, and resource-intensive urban sprawl. To build on emerging literature and understand city responses to disruptive change, this initial study engages researchers and practitioners across four smart city finalists (Columbus, Denver, Austin and Portland) that competed in the U.S. Department of Transportation (DOT) Smart City Challenge. The initial results emphasize the need for a suite of datasets and diverse analytical approaches that support U.S. Department of Energy (DOE) relevant research with cities. Considering desirable energy and mobility outcomes as a first step to advancing smart city solutions strategies, we systematically review approaches of and shortcomings in four U.S. cities, and suggest improvements in three areas: measurement, modeling effectiveness of new mobility technologies, and data-driven governance.