Protocol-Based Congestion Management for Advanced Air Mobility

Advanced air mobility operations (e.g., air taxis and drone deliveries) are expected to significantly increase the demand for limited airspace resources. Two key characteristics of these operations are that flights will be scheduled with short lead times, and operators may be unable or reluctant, for reasons of privacy, to share flight intent information. Consequently, there is a need for congestion management algorithms that are efficient and fair in dynamic, reduced-information settings. In this paper, we address these challenges by designing a protocol that determines the “rules-of-the-road” for airspace access under these settings. The proposed protocol centers on the construction of priority queues to determine access to each congested volume of airspace. We leverage the concepts of backpressure and cycle detection to avoid gridlock and promote efficiency, and present several flight- and operator-level prioritization schemes. We evaluate the impacts of the prioritization schemes on system-wide and operator-level efficiency and fairness through extensive simulations of three scenarios: random flight patterns, crossflows, and hub-based operations. In all scenarios, we find that backpressure prioritization yields the most efficient solution, and that accrued delay or dominant resource prioritization is the most fair depending on the user’s choice of fairness metric.