A novel two-phase location analytics model for determining operating station locations of emerging air taxi services

Air taxi is a new and emerging form of urban air mobility (UAM) for reducing traffic congestion in metropolitan cities by providing on-demand aviation services to millions of customers daily. These aviation services leverage the electric vertical takeoff and landing (eVTOL) technology, and hence, could operate even from building rooftops. This study aims to determine the location of infrastructure facilities for efficient eVTOL air taxi network operation in urban areas and its neighborhood. We utilize a unique two-phase procedure that integrates the multi-criteria warm start technique with an iterative k-means clustering algorithm. To evaluate the effectiveness of the proposed approach, we compare the model’s performance with the results obtained in the previous studies for various settings, such as percentage of time savings, demand satisfaction, passenger willingness to fly rate, and on-road travel limits. The results show the proposed methods yield a better solution than previous studies in terms of several metrics such as the Davies Bouldin index, number of clusters, and multi-criteria attributes.