Abstract

The development of Advanced Air Mobility and integration into the existing airspace infrastructure will require substantial research and development regarding how vehicles with diverse performance capabilities will operate cooperatively and safely in congested airspace. The density of air traffic for AAM is projected to increase substantially, requiring a dependency on reliable traffic flow management methods for efficient and safe operations. Effective integration of AAM will hinge on the ability to develop robust, alternative flow management techniques tailored specifically to the unique demands of AAM. This research presents the development and application of an air traffic management simulation framework designed for integrating Advanced Air Mobility (AAM) operations within a defined airspace, using the open-source simulation platform, BlueSky. By characterizing an AAM airspace with a demand model, vertiport network, and cooperative area definitions, the framework is capable of evaluating different methods of traffic flow management applied to a mix fleet of unique AAM vehicles. This framework enables assessment of airspace performance metrics—including operational efficiency, safety, energy usage, and community noise exposure, of which are governed by the heterogeneous performance envelopes of the distinct vehicles within a mixed fleet. The framework was exercised for an example AAM airspace design in the Dallas/Fort Worth region, incorporating a departure scheduling algorithm and a speed-based conflict resolution method. System efficiency, safety, energy use, and community noise were assessed across varying demand levels. Results show that the speed-based algorithm resolves over 90% of arrival conflicts across all demands, though it increases energy consumption, particularly for faster aircraft. A method for modeling community noise exposure is developed and suggests that the conflict resolution algorithm reduces exposure regions, particularly near vertiports.