Faireness-Informed Design of Urban Air Mobility Network: A Case Study of Dallas-Fort Worth Metropolitan Area

Urban air mobility (UAM) can potentially provide a transformative solution to urban transportation challenges by leveraging electric vertical takeoff and landing (eVTOL) aircraft to alleviate congestion and enhance connectivity. While existing UAM network design models prioritize cost minimization and operational efficiency, fair access for diverse socioeconomic groups remains underexplored. This study introduces a fairness-informed optimization framework for UAM network design, integrating a novel mixed-integer programming model that balances efficiency and fairness. Fairness is quantified using Conditional Value-at-Risk, a risk-aware metric that prioritizes underserved populations by minimizing disparities in transportation access costs. A case study in the Dallas-Fort Worth metropolitan area demonstrates that incorporating CVaR-based fairness significantly alters optimal vertiport placement strategies. Compared to traditional cost-minimization approaches, fairness-aware designs exhibit greater spatial dispersion of vertiports, extending service coverage to peripheral regions while maintaining competitive system-wide efficiency. The results highlight how fairness considerations lead to more geographically balanced network configurations that better serve disadvantaged communities. These findings underscore the critical trade-off between fairness and efficiency in UAM planning and provide actionable insights for policymakers and urban planners. The proposed methodology advances aerial mobility research by offering a scalable framework to address fair resource allocation in emerging transportation systems, ensuring UAM deployment aligns with broader social sustainability goals.