Empirical analysis of multimodal on-demand ride-hailing with urban air mobility in heterogeneous urban traffic scenarios

Multimodal on-demand ride-hailing integrated with urban air mobility has strong potential to improve transportation efficiency under diverse urban traffic scenarios. Leveraging modular flying vehicle technology that enables seamless switching between ground and air travel, such systems can provide flexible and efficient door-to-door mobility services. This study develops a multimodal on-demand ride-hailing system with urban air mobility, including a graph-partition-based vertipark siting method and a rolling-horizon joint matching model. Using empirical data from Stockholm, Sweden, and Chengdu, China, we conduct a modeling-based analysis across three representative urban traffic scenarios to evaluate the system’s performance. The results show that the proposed system substantially improves service rates, particularly in long-distance and bottleneck scenarios, while the benefits in general urban demand settings depend on vertipark densities and demand patterns. Low vertipark densities or unfavorable demand patterns can reduce these advantages, whereas incorporating an adjustable air-mobility weight helps mitigate such inefficiencies. In addition, the multimodal system reduces rider waiting times, carbon emissions, and the fleet size required to satisfy demand. These findings provide insights into how urban air mobility can enhance multimodal on-demand services and offer practical guidance for the planning and operation of future integrated urban mobility systems.