Impacts of shared automated vehicles on airport access and operations, with opportunities for revenue recovery: Case Study of Austin, Texas

Abstract

With rising use of ridesourcing apps and, eventually, self-driving vehicles, demands for airport parking spaces, rental cars, and, ultimately, air travel is expected to fall everywhere, relative to background trends. This study uses publicly available ridesourcing demand data for the Austin, Texas area to pursue simulations of a fleet of shared autonomous vehicles or “SAVs”, and quantify airport revenue and operations impacts. Results suggest that dynamic ride-sharing (DRS) of centrally-dispatched vehicles across strangers (with current travel patterns) may reduce airport-related ground travel by up to 30% while reducing airport-access revenues by 46%, assuming ridesourcing permits continue to be charged $2 per trip. A time-varying zone-based toll around the airport can help offset lost parking and car-rental (but not seat-mile) revenues and potentially double present-day airport-access revenues. Such policies can come at the cost of adding non-revenue ridesourcing and SAV miles to the rest of the network, when incentivizing SAVs to leave the airport zone after a dropoff, in order to avoid curbside congestion. A combination of DRS and use of access fees on all commercial vehicles dropping off or picking up travelers can achieve a useful middle ground.