UC Irvine

The evolution of Advanced Air Mobility (AAM) requires efficient management of congested airspace and the accommodation of diverse vehicles with distinct performance capabilities. The expected increase in flight volume and density within urban environments for a mature state of AAM operations will require a revolutionary shift in air traffic management. In order to maintain the safety and fairness standards of the National Airspace System as AAM matures, decision-makers need a detailed understanding of the feasible traffic flow management (TFM) methods applicable to AAM. Spanning a spectrum from contemporary, centralized air traffic management to de-centralized self-separation methods, and relying on various levels of strategic and tactical deconfliction, the ideal method for managing the flow of AAM traffic remains unclear. Additionally, the various approaches to traffic flow management exhibit conflicting airspace performance metrics including safety, throughput, efficiency, and community noise impact; all of which are essential to the effective integration of AAM into the airspace.The airspace integration of AAM is a complex problem to solve, in part due to the significant lack of data regarding the behavior of individual AAM aircraft necessary to understand vehicle operation envelopes, but also due to the limited research of airspace integration involving a heterogeneous mix of AAM aircraft. Thus, this work presents a physics-based framework designed to analyze the airspace performance metrics of different modes of TFM for Advanced Air Mobility operations through an evaluation of individual aircraft performance envelopes. This framework provides the ability to execute tradeoff studies evaluating various TFM modes applied to a mixed AAM fleet, providing a means for informed decision-making in the development of AAM policies and regulations.This framework is applicable to diverse urban environments through the integration of defined AAM airspace constructs including demand estimation and route planning for a desired assessment region. Leveraging established AAM aircraft architectures, this methodology constructs physics-based trajectories tailored to each vehicle's performance characteristics and user-defined operational objectives, while meeting requirements defined by the airspace and TFM method. A study of AAM aircraft operation envelopes is first performed for each vehicle, defining nominal vehicle performance envelopes that meet operational objectives regarding flight duration, power consumption, and community noise impact. This study was performed on three distinct AAM aircraft including a tilt-rotor electric vertical takeoff and landing (eVTOL) vehicle, a lift plus cruise eVTOL, and an electric short takeoff and landing (eSTOL) vehicle with blown-flap technology.The framework is applied to a case study of mixed-fleet AAM operations in the Dallas/Fort Worth airspace by integrating into the open-source BlueSky air traffic management simulation platform. Strategic scheduling and tactical conflict resolution methods are evaluated across several demand levels and vehicle mixes. Results demonstrate the impact that demand levels have on the performance of conflict resolution algorithms and resulting airborne delay and excess energy consumption. Additionally, the impact of conflict resolution methods on the community noise impact of AAM vehicles is evaluated. The findings suggest the importance of considering vehicle performance and resulting community noise impact when defining airspace constructs and traffic flow management protocols. This dissertation contributes a modular simulation framework for incorporating vehicle performance into AAM airspace integration research, offering a valuable tool for informed decision making for regulators, policy-makers, and airspace planning for future AAM ecosystems.