SP surveys to estimate Airport Shuttle demand in an Urban Air Mobility context

Abstract

Electric vertical take-off and landing vehicles (eVTOL) are expected to be the key drivers for Urban Air Mobility (UAM) scenarios, by satisfying on-demand air travel needs in the short or mid-term. Despite the high number of eVTOL prototypes, nowadays only few studies have focused on UAM travel demand estimation, in particular Airport Shuttle demand estimation. The aim of this work is to use Stated Preference methods to collect data necessary to understand the main features of the potential UAM Airport Shuttle trip demand, also by calibrating some discrete choice models. Data were collected by both on-line surveys and face-to-face interviews, which captured mainly the Italian context. Three different Multinominal Logit models and a Mixed Logit model have been calibrated in order to identify the main variables driving people's choices for Airport Shuttle services. The results show the positive impact of income, air travel frequency and shared ride in increasing the willingness to use Airport Shuttle services. On the other hand, user that still prefers the ground transportation modes to reach the airport, high ratio between the number of cars and the driving licenses per family unit and the lack of experience with autonomous systems (i.e., driving assistance systems) seem to have a negative impact on people intention to use Airport Shuttle services.