With the potential to bypass congested urban road networks and take advantage of the openness of the sky, advanced air mobility (AAM) promises to provide a faster alternative mode for people and goods. However, AAM will also require a new paradigm for the movement of aircraft around an airspace network and may operate at densities of aircraft previously unseen in airspace and beyond the capabilities of existing air traffic management. Given the separation requirements between aircraft congestion may form on AAM airspace networks. Under such conditions managing air traffic flow effectively and mitigating congestion to improve the user and operator experience becomes very important. In this dissertation traffic flow concepts developed from other modes are extended and adjusted to apply to aviation, specifically within the AAM context. This represents an important contribution because previous work on air traffic has generally focused on other topics than the macroscopic modeling and understanding of traffic flow behavior. Macroscopic air traffic flow models linking key traffic variables are established. A microscopic traffic simulator for AAM traffic is created and simulated results used to validate the macroscopic models. Sensitivity analyses to key operating parameters are performed to establish insights relating to traffic flow performance in the airspace. The effects of airspace restrictions are then studied at the local and network levels. A series of traffic flow experiments are performed in restricted airspace structures and networks. After measuring traffic flow variables and other system performance metrics in the experiments traffic flow insights are then established. The results highlight the importance of aircraft density and the conflict rate between aircraft when determining the traffic flow behavior and congestion. It is shown that higher densities of aircraft create more conflicts (predicted loss of separation events) between aircraft, which then negatively affect the average traveling speeds of aircraft and the throughput of the airspace. The macroscopic air traffic flow models are shown to have a predictive capability for air traffic flow conditions when compared with the simulated results. The models are also able to adjust to varying operating parameters such as separating minima between aircraft, maximum aircraft speeds, and heading restrictions in the airspace. The impacts of each of these parameters on air traffic flow behavior is discussed. Airspace structures are shown to have an impact on the development of air traffic flow at the local level. The insights generated from the airspace structure experiments demonstrate three competing effects when considering the impact of structures. Airspace restrictions or structures may artificially raise the density of aircraft, may restrict the detour routing flexibility of aircraft, or may organize the airspace. These effects are not mutually exclusive but all affect at a macroscopic level how traffic flow behaves. At the network level four general airspace network architectures are constructed and seven network performance metrics compared. The network performances reveal that there is no single best network architecture, rather each architecture represents trade-offs between priorities. The trade-offs between networks and the situations in which each network architecture performs the best are discussed. The primary contribution of this research is the application of traffic flow concepts to the air traffic flow problem for the AAM context. Previous work in traffic flow offers a number of strategies and concepts that may be useful for air traffic flow. Meanwhile air traffic flow represents an interesting multi-dimensional extension to the traditional traffic flow models. Macroscopic air traffic flow models that extend and go beyond previous research in the area and created to describe the behavior of air traffic flow. The models provide a greater understanding of how air traffic flow may behave and congest. The macroscopic models are also sensitive to key AAM operating parameters, which gives them greater flexibility in application across contexts and creates interesting insights about traffic flow behavior. Ultimately the models may be used as part of a system to predict and monitor air traffic flow conditions and point towards management strategies. As one example, the air traffic flow models provide a reliable means for estimating both aircraft travel times and airspace capacities, each of which are of critical importance to both operators and users of the AAM system. The dissertation also explores the interaction between airspace structures and air traffic flow. The traffic flow and congestion of airspace structures is illustrated through experiments. Comparisons among experiments illuminate a framework for thinking about the impacts of airspace restrictions and structures that will be useful when designing restricted airspace networks in urban areas. Impacts of network architecture on the operator and user experience are investigated experimentally. The benefits and drawbacks of various network architecture concepts are discussed and suggestions made that could help to improve the design of AAM networks from safety, efficiency, and external impacts perspectives.

Creator

• Cummings, Christopher

DOI

• https://doi.org/10.21985/n2-yswa-7m55

Subject

• Transportation

Language

• en

Alternate Identifier

• etdadmin_upload_929074
• http://dissertations.umi.com/northwestern:16261

Keyword

• Traffic Flow
• Air Traffic Flow
• Air Mobility
• Air Traffic Management

Date created

• 2022-01-01

Resource type

• Dissertation

Rights statement

• In Copyright