A Maximal Covering Approach for Vertiport Location Problem

Urban Air Mobility (UAM) revolutionizes transportation and provides solution to urban congestion by enabling efficient aerial transit within metropolitan areas using electric vertical take-off and landing (eVTOL) vehicles. The successful deployment of UAM systems relies heavily on the optimal placement of vertiports, which serve as critical nodes connecting air and ground transport networks. This study addresses the vertiport location problem by developing optimization models aimed at maximizing the coverage of demand points with a limited number of vertiports. Specifically, we formulate the problem as a maximal coverage location problem (MCLP) and propose two distinct models: (i) a binary coverage model, which assumes full coverage within a predefined range, and (ii) a discrete gradual coverage model, where coverage decreases as the distance from demand points increases. While prior studies have largely focused on binary coverage, this research incorporates a gradual coverage perspective, which may offer greater alignment with real-world UAM demands. We demonstrate the applicability of the approach on a case study of 50 cities selected from counties within OH.