The emerging low-altitude economy (LAE) hinges on effectively managing high-density aerial traffic flows. Establishing a system of low-altitude public air routes offers a feasible solution to handle this congestion. In this context, these routes are conceptualized as foundational “sky–road” infrastructure, and it is proposed that they be treated as fixed assets endowed with tradable or transferable property rights. Previous analysis suggests that building a public low-altitude air-route network can generate significant socioeconomic benefits, potentially beyond those of conventional ground transportation. Although “building sky roads” poses technological and regulatory challenges, extending the principles of terrestrial road networks into low-altitude airspace allows existing planning standards and governance mechanisms to be largely adapted to this new domain. This approach can transform many of these challenges into opportunities, laying the groundwork for a robust LAE in the future.
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Open Access
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The successful application of new technologies such as remotely piloted aircraft systems, distributed electric propulsion systems, and automatic control systems on electric vertical take-off and landing(eVTOL) aircraft has prompted Urban Air Mobility (UAM) to be mentioned frequently. UAM is a newly raised transport mode of using eVTOL aircraft to transport people and cargo in urban areas, which is thought to share some of the traffic on the ground. One of the prerequisites for UAM to operate on a regular basis is that its demand can support the operating costs, so forecasting UAM demand is necessary. We conduct UAM demand forecasting based on the four-step method, focusing on improving the third-step modal split, and propose a demand forecasting model based on the logit model. The model combines a nested logit (NL) model with a multinomial logit (MNL) model to solve the problem of non-existent UAM sharing rates. We use Chengdu, China as an example, and focus on forecasting the UAM traffic demand in 2030 with the help of the four-step method. The results show that UAM is suitable for shared operation during the early stages. With a fully shared operation, the UAM share rate increases by 0.73% for every kilometer increase in distance. Moreover, UAM is more competitive than other modes for delivery distances exceeding 15 km. Finally, using the distributions of the share rate and traffic flow pattern from the simulation, we propose the routes that can be prioritized for UAM operations in Chengdu.
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