This is a decision-support tool for planning, designing, operating, and managing micromobility in the U.S. cities. This tool is a website that includes the datasets, programs, analysis results, visualizations, preprints, reports, and other relevant materials to help stakeholders to gain useful information for decision making and to guide policy intervention.

For any questions regarding this tool, please contact Yiming Xu (yiming.xu@ufl.edu) and/or Xilei Zhao (xilei.zhao@essie.ufl.edu).


[1] Xu, Y., Yan, X., Sisiopiku, V. P., Merlin, L. A., Xing, F., & Zhao, X. (2021). Micromobility trip origin and destination inference using General Bikeshare Feed Specification (GBFS) data. Proceedings of Transportation Research Board 100th Annual Meeting. (Accepted)

[2] Merlin, L. A., Yan, X., Xu, Y., & Zhao, X. A segment-level model of shared, electric scooter origins and destinations. (Under review)


Spatial distributions of trip origins and destinations in Washington, D.C. (Density unit: trips per day per km^2.)

Morning Peak (Left: trip origin; Right: trip destination.)


Afternoon Peak (Left: trip origin; Right: trip destination.)

Funding Sources

  • Mobility-on-Demand Transit for Smart and Sustainable Cities
  • X. Zhao (PI), X. Yan (co-PI), N. Kaza (co-PI), N. Kittner (co-PI), N. McDonald (co-PI), V. Sisiopiku (co-PI), X. Jin (co-PI), J. LaMondia (co-PI), and A. Broaddus (co-PI)
  • Sept, 2020 – Aug, 2021


  • Micromobility as a Solution to Reduce Urban Traffic Congestion
  • X. Zhao (PI), V. Sisiopiku (co-PI), and R. Steiner (co-PI)
  • Nov, 2019 – Apr, 2021