<p dir="ltr">Urban air mobility (UAM) has the potential to revolutionize the transportation industry, offering fast, convenient, and sustainable travel options for passengers and cargo. The development and operation of UAM networks, however, face significant challenges, including the need for infrastructure investments and the management of grid electricity usage. In this thesis, we present a comprehensive model of UAM network operations based on system-of-systems engineering principles and employ a data-driven simulation framework to analyze the expected performance of a UAM operation. Our approach optimizes the composition of the UAM network, including the number of vehicles, chargers, and sizing of solar microgrids, to minimize total acquisition costs while adhering to operational constraints such as maximum average passenger delay and grid usage for each vertiport. Through the application of our methodology to diverse case studies, we provide valuable insights into the optimal design and integration of on-site microgrids for UAM vertiport networks, highlighting their impact on carbon emissions, operating costs, and grid electricity usage. This research contributes to the development of sustainable and efficient UAM systems, supporting informed decision-making among stakeholders involved in the planning, deployment, and operation of urban air mobility networks.</p>

<div>The National Aeronautics and Space Administration (NASA) has a vision for Advanced Air Mobility (AAM) based on safely introducing aviation services to missions that were previously not served or under-served. Many potential AAM missions lie in metropolitan areas that are beset by various types of uncertainty and potential constraints. Radio interference from other electronic devices can render unreliable communication between flying vehicles to ground operators. Buildings have irregular surfaces that degrade GPS localization performance. Skyscrapers can induce spontaneous turbulence that degrades vehicles' navigational accuracy. However, the potential market demands for aerial passenger-carrying and package delivery services have attracted investments. For example, Google WingX, Amazon Prime Air, and Joby Aviation are well-known companies developing AAM systems and services. If the market visions are realized, how will safety be assessed and maintained with high-density AAM operations?</div><div><br></div><div>While there are multiple technology candidates for realizing high-density AAM operations in urban environments, the means to accomplish the requisite first step of assessing the airspace safety of an integrated AAM eco-system from the candidate technologies is crucial but as yet unclear. This dissertation proposes an entropy-based framework for assessing the airspace safety level for low-altitude airspace in an AAM setting. The framework includes a conceptual model for depicting the information flows between air vehicles and an air traffic authority (ATA) and the use of a probability distribution to represent the traffic state. Subsequently, the framework embeds three airspace-level metrics for assessing airspace safety and uncertainty levels. The traffic safety severity metric quantifies the traffic safety level. The traffic entropy quantifies the uncertainty level of the traffic state distribution. Finally, the temperature is the ratio of the traffic safety severity to the traffic entropy. The temperature is similar to the traffic safety severity but gives a higher weight to the instance with a safe traffic state. </div><div><br></div><div>Simulation studies show that the combined use of the three metrics can evaluate relative airspace safety levels even if the unsafe conditions do not occur. The use cases include using the metrics for real-time airspace safety level monitoring and comparing the design of airspace systems and operational strategies. Additionally, this study demonstrates using a heat map to visualize vehicle-level metrics and assess designs of UAM airspace structures. The contribution of this study includes two parts. First, the temperature metric can heuristically assess a probability function. Based on the definition of the cost function, the temperature metric gives a higher weighting to the instance of the probability function with a lower cost value. This study constructs several triggers for predicting if a near-miss event would happen in the airspace. The temperature-based trigger has a better prediction accuracy than the cost-function-based trigger. Secondly, the temperature can visualize the safety level of an airspace structure with the considerations of the environmental and vehicle state measurement uncertainty. The locations with high-temperature values indicate that the regions are more likely to have endangered vehicles. Although this framework does not provide any means of resolving the unsafe conditions, it can be powerful in the comparison of different airspace design concepts and identify the weaknesses of either airspace design or operational strategies. </div>

<p>As Urban Air Mobility (UAM) is developed and brought into fruition via electric vertical takeoff and landing (eVTOL) vehicles, contingencies associated with this new distributed electric propulsion technology in metropolitan areas must be considered. On the state of knowledge on contingencies for eVTOL vehicles, these can be Epistemological Risks or Ontological Risks. Epistemological Risks include known-knowns (probabilistic risks) and known-unknowns (gaps in knowledge). Ontological Risks include, unknown-knowns (hidden knowledge), unknown-unknowns (fog of ignorance). As UAM operations at large scale do not have as much historical accidents data as General Aviation or Commercial Aviation, it is challenging to estimate its accident failure rate per 100,000 flight hours. While battery thermal runaway, battery energy uncertainty, software issues, and common mode power failures are some failure cases listed in this thesis, it is the undiscovered contingency (i.e., unknown-unknown) or unprepared contingency (i.e., unknown-known), along with other external factors, that can lead to an accident. UAM is expected to operate at 1500 feet AGL and at high frequencies over dense metropolitan areas. In an in-flight emergency at these altitudes, any startle response experienced by on-board or remote pilots can lead to longer response times. This study aims to create a framework for contingency planning and risk mitigation using a Reachable Ground Footprint model for eVTOL aircraft under 100% power failure scenarios in-flight. This framework utilizes all existing, public aerodrome infrastructures in metropolitan areas as potential contingency landing sites. Metrics such as Contingency Landing Assurance Percentage and Cruise Altitude Floor requirement are introduced to quantitatively measuring the safety of any UAM trip and provide recommendations on safe cruising altitudes. A demonstration case in the Chicago Metropolitan Area between DuPage Regional Airport and John H. Stroger Hospital Helipad is shown and discussed. Furthermore, aggregate analysis of 434 UAM trips in Chicago Metropolitan Area between Regional Airports, between Regional and Heliports, and between Heliports is performed, along with sensitivity studies involving wind and turn control restrictions. The results discuss variations in Cruise Altitude Floor, Flight Time, and Energy Consumption of these trips using an eVTOL vehicle.</p>