Peksa, Magdalena (Technical University of Munich), Keyvan-Ekbatani, Mehdi (University of Canterbury), Bogenberger, Klaus (Technical University of Munich)

Airspace Partitioning for Urban Air Mobility: A Macroscopic Approach with a Realistic Network

Scheduled for presentation during the Regular Session "S45a-Decision-Making for Urban Air Mobility and Autonomous Logistics" (FR-LM-T45), Friday, November 21, 2025, 12:10−12:30, Gold Coast

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

Traffic in low-altitude urban airspace is expected to grow significantly with the emergence of new air transport services, commonly referred to as Urban Air Mobility (UAM). Recent studies have shown, through simulations, that UAM operations exhibit characteristics similar to vehicular traffic and have demonstrated the potential of road traffic models, particularly the Network Macroscopic Fundamental Diagram (NMFD), to describe and manage urban airspace. The results are promising; however, similar analyses in realistic contexts remain limited. Moreover, as in large-scale road networks, airspace traffic can be distributed heterogeneously, leading to highly scattered NMFDs. To address this, the present study introduces a two-step partitioning algorithm that divides a structured airspace network, composed of air corridors, into homogeneous regions. Aircraft trajectories used by the algorithm are generated within a microscopic simulation environment developed using the open-source air traffic simulator BlueSky. The proposed partitioning method is applied to a UAM network designed for an air taxi scenario in New York City (NYC), which has been identified as one of the earliest potential implementation areas for such services. The simulated UAM traffic utilizes existing helicopter routes, and the demand is estimated based on NYC taxi data.