UC Irvine

Integrating advanced air mobility (AAM) into existing airspace will require substantial research and development regarding how diverse vehicles can operate cooperatively and safely in congested environments. Effective integration of AAM will hinge on the ability to develop robust, alternative traffic flow management techniques tailored specifically to the unique demands of AAM. This research introduces an air traffic management simulation framework for AAM operations, implemented in the open-source platform BlueSky. The framework characterizes airspace through demand models and vertiport networks and integrates high-fidelity vehicle performance and source noise models, enabling a deeper evaluation of flow management methods and the connection between noise and aircraft operations for mixed fleets of unique AAM vehicles. Performance is assessed through metrics of efficiency, safety, energy usage, and community noise exposure. The framework is exercised for an example AAM airspace design in the Dallas–Fort Worth region, incorporating a departure scheduling algorithm and a conflict resolution method based on the speeds of aircraft in conflict. Results demonstrate that the speed-based algorithm resolves over 90% of arrival conflicts across all demands, though it increases energy use, particularly for faster aircraft. Results also show a reduction in community noise exposure with the application of the speed-based method for mixed aircraft fleets.