New Framework Optimizes Urban Air Mobility Vertiport Siting and Fleet Design

Hossein Z. Saghazadeh, Yonas Ayalew, Reza Ahmari, Parham Kebria, Abdollah Homaifar· August 18, 2026 View original

Key takeaways

  • A new framework optimizes UAM network design by linking demand, vertiport siting, and fleet simulation.
  • Spatial demand imbalance remains a key operational challenge for UAM, even with larger fleets.
  • UAM offers the most significant travel time savings for longer or congestion-heavy trips.
  • Data-driven simulation is crucial for evaluating UAM network performance and scalability.

Who benefits

Urban PlanningAerospaceLogisticsTransportationReal Estate

Summary

This paper introduces a demand-driven framework for designing Urban Air Mobility (UAM) networks, integrating vertiport placement, fleet simulation, and door-to-door travel time analysis. A case study in Greater Los Angeles demonstrates how the system scales vertiport and eVTOL numbers based on demand, highlighting the persistent challenge of spatial demand imbalance.

Researchers have developed a comprehensive framework to optimize the design of Urban Air Mobility (UAM) networks. This system considers various factors, including the strategic placement of vertiports, the simulation of eVTOL fleets, and the overall feasibility of door-to-door travel times. By analyzing commuter and passenger activity data, the framework uses clustering techniques to identify optimal vertiport locations and then evaluates these networks through discrete-event simulations that model multi-vehicle dispatch, battery swaps, and service regularity. A practical application of this framework in the Greater Los Angeles area showed how the network design adapts to varying demand levels, from a small initial setup to a larger system with more vertiports and eVTOLs. The study revealed that while larger fleets improve service, spatial demand imbalances continue to pose operational challenges, leading to deadhead flights. The analysis also suggests that UAM offers the most significant travel time savings for longer or highly congested trips, where the flight time contributes substantially to overall efficiency.

Why it matters

Professionals in urban planning, logistics, and aerospace can use this research to inform strategic decisions for developing efficient and sustainable Urban Air Mobility infrastructure and services. It provides a data-driven approach to tackle complex network design challenges.

How to implement this in your domain

  1. 1Integrate demand modeling techniques into future UAM infrastructure planning.
  2. 2Utilize discrete-event simulation tools to evaluate proposed vertiport locations and fleet sizes.
  3. 3Conduct feasibility studies focusing on door-to-door travel times for specific urban corridors.
  4. 4Develop strategies to mitigate deadhead flights caused by spatial demand imbalances.
  5. 5Prioritize UAM service development for routes with significant congestion or longer distances.

Original post by Hossein Z. Saghazadeh, Yonas Ayalew, Reza Ahmari, Parham Kebria, Abdollah Homaifar

"arXiv:2608.14974v1 Announce Type: new Abstract: This paper presents a demand-driven framework for on-demand Urban Air Mobility (UAM) network design that links vertiport siting, fleet simulation, and door-to-door travel-time feasibility. Demand is estimated from commuter and passe…"

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Originally posted by Hossein Z. Saghazadeh, Yonas Ayalew, Reza Ahmari, Parham Kebria, Abdollah Homaifar on X · view source

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