Scalable Combinatorial Vertiport Placement Method for an Urban Air Mobility Commuting Service

Abstract

Vertiport locations have a significant impact on the time savings provided by an urban air mobility (UAM) commuting service relative to ground transportation and, thereby, greatly affect the value proposition and demand for UAM commuting services. In this paper, we present a discrete combinatorial vertiport placement method with a flexible objective function capable of directly optimizing for commuting demand. Preprocessing and postprocessing formulations that effectively reduce problem size and increase solution quality are also described. Demand-maximizing vertiport placement results are provided for Atlanta, New York City, San Francisco, and Seattle. We also present results showing the sensitivity of potential commuting demand to number of vertiports, ticket price, and service delay. Additionally, results that illustrate the impact of limiting vertiport placement to locations with existing airport and helipad infrastructure are presented. Finally, vertiport placement results optimized using a capacitated profitability-maximization objective are outlined.