1374274 - A Scenario-based Methodology for UAM Demand Estimation

Urban Air Mobility (UAM) is emerging as an alternative mode to solve various problems arising from road-centered modes. Several developed countries are conducting related research such as operational strategies for introducing and commercializing UAM and design guidelines for infrastructure (ex. vertiport) construction. It starts with accurately predicting transfer demands in order to create these appropriate strategy and design guidelines. The UAM demand can be estimated differently depending on various situations, such as vertiport location-allocation, and travel influence area for each vertiport facility. This study proposes a UAM demand estimation methodology to develop a feasible UAM introduction strategy based on various scenarios. The proposed methodology can be conducted with four steps: 1) vertiport location-allocation, 2) fixing spatial influence area of each vertiport, 3) separating the level of business maturity, and 4) hourly based OD estimation with mobile-phone data. A total of 24 vertiport locations were finally selected based on the weighting factors in a metropolitan city area scale. This study uses two cut-off thresholds of 10 minutes and 15 minutes of travel time boundary to fix spatial influence area for each vertiport provided from the UAM guideline of Korean Government. Business maturity was classified into three folds: introductory, growth, and maturity phases and then the rate of transfer demand according to the maturity level was calculated, respectively. Finally, annual average OD matrix provided from the data of the house hold survey was fused with hourly OD profile calculated from the mobile phone data for estimating hourly travel demand of UAM. The result in this study shows that the demand of UAM was high, mainly in neighboring cities and large cities. It was also found that short-distance UAM demand was mainly concentrated during commuting time. It is our hope that the result of this study conveys UAM designers the essential information to develop and design regional UAM infrastructure and operational strategy in the future.