Integrating UAM operations into controlled airport airspace via a data-informed complexity framework

Urban air mobility (UAM) is a transformative and emerging trend in urban transportation. To ensure safe separation, many preliminary studies restrict UAM traffic from operating within controlled airport airspace, such as ICAO Class B and Class C airspace surrounding major airports. However, many controlled airport airspaces sit adjacent to urban centers, where strict prohibitions on UAM operations may ultimately lead to systemic inefficiencies and undermine UAM’s competitiveness. In this study, we explore the methods and effects of integrating UAM traffic into controlled terminal airspace. By combining 4D flight trajectory data analysis with two complementary traffic complexity metrics, the objective is to identify ‘redundant’ sectors within controlled airspace that could be allocated for UAM operations. We demonstrate the proposed data-informed complexity approach through two real-world case studies: the Dallas Class B airspace and the Milwaukee Class C airspace. The results indicate that even during peak traffic hours, 50% and 80% of their controlled airspace sectors remain at a low complexity level, respectively. Allowing UAM routes to pass through these sectors can substantially shorten route distances while avoiding areas associated with historically high traffic complexity. Further research and investigation into relevant airspace integration problems merit continued exploration.