Xilei Zhao, University of Florida
Virginia Sisiopiku, University of Alabama at Birmingham
Ruth Steiner, University of Florida
Da Yan, University of Alabama at Birmingham
Micro-mobility, a variety of small, lightweight transportation devices such as e-scooters and dockless bikes, is an innovative transportation strategy that meets the diverse needs of various travelers by providing flexible, affordable, and accessible services (Shaheen and Cohen, 2019). Early findings have shown that micro-mobility may mitigate congestion, cut greenhouse emissions, decrease car ownership, and promote public transit.
Some studies suggest that micro-mobility has the potential to claim 8 to 15 percent of all the trips under five miles and grow to $200B to $300B in the U.S. (Shaheen and Cohen, 2019). However, there is a limited number of studies of quantifying and understanding micro-mobility’s impacts on the existing transportation system and how it will reshape people’s travel behavior in the future cities. Therefore, the project aims to: 1) Understand the usage patterns of micro-mobility and model the demand for this new travel mode; 2) Simulate and evaluate whether and when micro-mobility can ease congestion; and 3) Recommend realistic policy intervention strategies to encourage modal shift from automobile to micro-mobility.
This study integrates big data analytics, demand modeling, traffic simulation, and policy analysis to provide a comprehensive assessment of the impacts of micro-mobility on congestion mitigation. It is expected to generate new insights for key stakeholders to facilitate planning micro-mobility policies and practices. This study will create a database for historical e-scooter data, develop new methodologies to model and interpret travel demand of micro-mobility, improve activity-based traffic simulation models, develop an interactive decision-support tool for local stakeholders, and generate peer-reviewed journal/conference publications.