Abstract:

To improve the delivery efficiency of urban last-mile logistics and promote the development of the low-altitude economy, a hierarchical drone vertiport location method is proposed to address urban low-altitude logistics demand. First, a conditional Logit model is utilized to identify key factors and estimate urban low-altitude logistics demand. Second, a hierarchical facility polygon intersection point set method is applied to determine candidate vertiport locations for drones. Finally, a multi-objective hierarchical vertiport maximum coverage location model is established, aimed at maximizing demand coverage, minimizing construction costs, and reducing demand redundancy. An improved NSGA-III algorithm is designed to solve the model. The results show that the performance of facilities is optimal when the number of vertiport sites and points respectively reach 53 and 107 in Shanghai, with a demand coverage rate of 85.6%, construction costs amounting to 9.59 million CNY, and a demand overlap rate of 33.7%. The location scheme demonstrates a high degree of rationality and feasibility. In addition, the study found that economic development levels and traffic accessibility significantly influence the spatial distribution and performance of vertiports. Setting vertiports in areas with high GDP and abundant transportation facilities can further enhance demand coverage, although it may lead to increased construction costs and redundancy in service areas. The research findings provide scientific decision-making support for the planning and implementation of urban low-altitude logistics systems.

Key words: air transportation, hierarchical drone vertiport location, conditional logit model, maximum coverage location model, NSGA-III algorithm