A Spatiotemporal Approach to Portal Siting and Routing for Urban Air Mobility: A Case Study on New York City

Advances in battery technology and autonomy algorithms have unlocked potential for electric Vertical Take-off and Landing (eVTOL) aircraft to serve Urban Air Mobility (UAM) operations. As the demand for UAM services grows over time, the optimal locations of UAM ground infrastructure that satisfy dynamic trip demand in the long term must be determined. In this paper, we implement a Bass diffusion model with a price relationship curve to predict the UAM trip price as a function of UAM commuters. Next, we integrate the dynamic pricing data with a Multinomial Logit Model (MNL) to estimate the long-term spatiotemporal demand for UAM services. Subsequently, we formulate and solve a vertiport Location-Routing problem (LRP) to determine optimal UAM locations and travel networks over time that will maximize the spatiotemporal demand. We validate these approaches by conducting a case study on New York City, where we estimate the UAM demand over a series of time steps and solve a temporal vertiport LRP.