Mobility Data Initiative

Supported by:
CR2C2 - Region 4 University Transportation Center (UTC)
Mobility COE - Center of Excellence on New Mobility and Automated Vehicles

High-Resolution Synthetic Travel Data for U.S. Urban Areas

Contact Us for Collaborations

We welcome opportunities to collaborate with researchers, agencies, industry partners, and community organizations. If you're interested in working with us on transportation safety, mobility innovation, or data-driven planning—especially in support of small and mid-sized communities—please reach out.

Contact: Dr. Jun Liu, jliu@eng.ua.edu

We have generated high spatial and temporal resolution synthetic trip and tour data using open-source land use, socioeconomic, and travel survey datasets. These data are designed to support small-area travel modeling and planning efforts across the United States.

The dataset can be used to:

  • Promote the adoption of agent-based modeling (ABM) in small and mid-sized urban areas

  • Support policy analysis and scenario planning at disaggregated levels

  • Facilitate the integration of emerging mobility technologies, such as electric vehicles (EVs), connected and automated vehicles (CAVs), and shared mobility services

We have produced:

  • Synthetic commuting data for over 400 urbanized areas across the U.S.

  • Comprehensive synthetic trip data (commuting and non-commuting) for over 300 small and mid-sized urban areas

These datasets offer valuable resources for researchers, planners, and policymakers working to advance next-generation mobility solutions in communities of all sizes.