Yu Yang
University of Florida, FL·Engineering
Shared e-scooters and similar new services are changing how people get around and are reshaping public transit. But who benefits, and who bears the costs?
- Fields
Engineering
Mathematics & Statistics
Social Science
- Topics
fairness
equity
emerging infrastructure systems
- Grants
- 1 known grant, through Jun 2027
What they work on
- Create a framework that scores the positive and negative effects of emerging systems such as shared e-scooters on different population groups with multi-level utility functions, combined by a social welfare function.
- Develop optimization models that preserve fairness under changing operations, solved with a customized Benders decomposition and a specialized procedure for generating and selecting strong Benders cuts.
- Estimate the price of fairness, the efficiency lost for a given fairness level, using a data-driven uncertainty set, and analyze tradeoffs in a shared micro-mobility case study with public data.
More about the research
Measuring fairness in these systems is hard because demand, vehicle locations and operations shift constantly, and different groups of people and stakeholders want conflicting things. This collaborative project develops ways to measure and preserve fairness in such emerging infrastructure, with attention to disadvantaged populations.
Why it matters
Cities and policymakers deciding how to regulate e-scooter and other micro-mobility services could use these fairness measures and tradeoff estimates to ensure services do not leave disadvantaged communities behind. They could also judge how much efficiency a fairer design would cost.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Yiling Zhang
University of Minnesota, MN·Engineering
Build a hierarchical stochastic optimization framework that links short-term adaptive user behavior to long-term infrastructure design, applied to building energy management and last-mile package delivery with parcel lockers.
Michael Levin
University of Minnesota, MN·Engineering
Develop exact solution methods for transportation network design under user equilibrium that combine high-point relaxations, value-function cuts and strong duality cuts to find provably optimal designs faster.
Zhaomiao Guo
University of Texas at Austin, TX·Engineering·Early-career
Develop network models of how decentralized transportation and power system stakeholders with incomplete information interact across space and time as electric vehicles and clean energy expand.
The school
University of Florida: 65 labs on PI Pages, $1.3B a year on research, 795 research doctorates a year.
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