Vertiport location planning for urban air mobility under flight network connectivity uncertainty

Abstract

The successful deployment of Urban Air Mobility (UAM) depends on the strategic placement of vertiports, which is complicated by inherent uncertainties, particularly weather induced disruptions to low-altitude flight routes. This paper tackles the UAM vertiport location optimization problem, with a focus on the uncertainty arising from adverse weather to aerial route connectivity. We propose a two-stage stochastic programming formulation to tackle this challenge. In this framework, the first-stage decisions involve the strategic selection of vertiport locations from a set of candidate vertiports, while the second-stage decisions manage the flow of vehicles under a multitude of weather scenarios. A significant computational bottleneck in such models arises from the need to enumerate all possible flight routes across all scenarios, leading to a massive number of decision variables and intractable solving time for large-scale instances. The key methodological contribution of this work is the introduction of a data-preprocessing strategy, which identifies and eliminates infeasible routes a priori based on weather-impacted aerial connectivity and operational constraints in each scenario. This preprocessing step results in a substantial reduction of the decision variable space, leading to a more compact and computationally efficient model. We conduct computational studies comparing the proposed preprocessing-augmented model against the traditional exhaustive variable approach. Experimental results demonstrate a superior improvement in solving time while maintaining identical solution quality. Through sensitivity analysis, we further derive critical insights into how varying levels of weather uncertainty and different parameters influence the optimal vertiport configuration and system costs. The study concludes with policy implications for urban planners and UAM operators, highlighting how advanced modeling techniques can improve operational resilience and efficiency.

Graphical abstract

Keywords

urban air mobility / vertiport location / weather-induced uncertainty / two-stage stochastic programming / preprocessing

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