UAM siting approach considering capacity and land use: A case study of Munich

Abstract

Rapid urbanization and escalating traffic congestion have intensified the search for innovative transportation solutions. Urban Air Mobility (UAM), utilizing electric vertical takeoff and landing (eVTOL) aircraft, offers a promising avenue to revolutionize urban transportation by leveraging aerial spaces. However, optimal placement of vertiports-the essential ground infrastructure-remains a critical challenge due to complex considerations of demand dynamics , capacity constraints, economic viability, and environmental impacts. This study operationalizes a novel multi-objective optimization framework for capacitated ver-tiport siting by developing a Controller-a software tool designed to manage and automate the intricate optimization process. The Controller enables structured, multi-period incremental siting, which the framework alone cannot handle, by automating dynamic parameter updates, managing simulation dependencies, and efficiently utilizing high-performance computing resources. This advancement allows for extensive case studies and large-scale analyses that would be impractical without such automation. Employing the Controller, we conducted a comprehensive case study in the Munich Metropolitan Area, using high-resolution land use data to generate specific, viable vertiport locations. The methodology utilizes a three-stage stochastic programming model formulated as a p-Hub Median Problem, optimized through Simulated Annealing and greedy algorithms. The Con-troller’s capabilities were essential for scaling up experiments, handling dynamic parameters, and managing extensive datasets. Results indicate that multi-phased incremental siting strategies significantly outperform single-phase approaches across various performance metrics, including optimization scores, cost savings, emissions reduction, and accessibility improvements. Specifically, the 4-phased in-cremental siting strategy emerges as optimal, balancing substantial performance gains with manageable complexity and lower risks. Sensitivity analyses highlight the importance of incorporating capacity constraints and construction costs for realistic and economically viable solutions. The study also finds that a mixed land use approach enhances system performance , and moderate subsidies on construction costs (20% to 40%) can improve outcomes without compromising economic sustainability. By operationalizing the optimization framework with the Controller, this study provides critical insights for urban planners and policymakers, emphasizing the importance of adaptive, phased infrastructure development aligned with demand growth and technological progress. The Controller was pivotal in enabling large-scale analyses, contributing to the strategic planning and implementation of sustainable UAM systems, and offering a robust methodology for optimizing vertiport placement in complex urban settings.

Shahriar Iqbal Zame

Doctoral Candidate & Research Associate

Research interests include agent-based simulations, optimization, mode choice modeling, freight electrification and automation.