关键词: eVTOL起降场, 优化选址, GIS, 城市空中交通, 低空经济

Abstract: Addressing the lack of systematic methodologies for vertiport site selection of electric vertical take-off and landing (eVTOL)aircraft in the context of the low-altitude economy,this paper proposes a site selection approach integrating multi-factor analysis with a bi-level optimization model.Using Chengdu as a case study,candidate sites are initially screened through overlay analysis of multi-source geographic data,including population density,land use,and traffic accessibility.A bi-level optimization model is then developed to maximize the total served population,incorporating both exponential and Gaussian distance decay functions,and solved using a hybrid strategy combining mixed-integer linear programming (MILP)and genetic algorithm (GA).By comparing two initial site selection schemes(new sites and sites incorporating existing general aviation airports),the study comprehensively evaluates theoretical served population,optimal value,and coverage rate.Results show that the normalized Gaussian distance decay model achieves better performance in terms of theoretical served population (390747 people)and population coverage rate (42.84%in the 0～100k population interval),while the exponential decay model demonstrates stronger small-area coverage capability.The final selected optimal solution is the “site selection scheme based on the normalized Gaussian distance decay model with existing general aviation airports,” which balances service capacity and coverage scope.The study reveals a nonlinear relationship between the number of vertiports and the population coverage rate,and indicates that the Gaussian decay model is more suitable for site selection in densely populated areas.The research outcomes provide a scientific basis for planning low-altitude transportation networks in Chengdu and offer a referential theoretical and practical framework for eVTOL vertiport site selection in other cities.

Key words: eVTOL vertiport, optimal site selection, GIS, urban air mobility, low-altitude economy