Urban air mobility (UAM) is an emerging mode that promises to provide relief to congested urban streets. UAM relies on airspace, however, which is an exhaustible resource considering minimum aircraft separation requirements. In light of these requirements and UAM vehicle attributes, a simulation is developed to explore UAM traffic flows and congestion development. A decentralized conflict resolution scheme is employed in the form of a non-linear program (NLP) to offer improved flexibility in detours relative to past aircraft simulations. An expansion of Edie’s definitions of density and flow rate are used in conjunction with average speed to explore the relationships between traffic flow characteristics. The results find that UAM traffic flows emulate those of other modes, by following the familiar traffic patterns of build-up and breakdown captured in the macroscopic fundamental diagram. These findings also suggest the presence of a capacity of airspace that should be carefully managed by operators to achieve optimal system performance. The relationships established in this study highlight issues that UAM operators and aviation planners may face and could be used to improve the vehicle traffic modeling of other UAM models.
To ease urban congestion, advanced air mobility (AAM) proposes the use of small aerial vehicles at low altitudes for uses such as package delivery and passenger services. In a developed state, an AAM service is predicted to involve thousands of trips daily, creating much higher densities of aircraft than currently exist in any airspace. Airspace structures have been proposed to help manage the high-density aircraft traffic. One such airspace structure is tube airspace, in which vehicles fly along predefined paths at specified altitudes. Tube airspaces have the advantage of aligning vehicle trajectories to reduce conflicts, however, traffic flow through restricted tube airspaces is not yet well understood. This paper defines how to measure traffic flow in a restricted network of airspace. These definitions are applied to measure traffic flow in several simulated scenarios of tube airspace constructs. By analyzing and comparing the macroscopic traffic flow patterns of tube airspace, several insights about the benefits and drawbacks of tube airspace are found. The results of this paper could improve decisions about creating and managing tube airspaces, and therefore would be of interest to AAM network planners and operators. They are also of interest to aviation researchers who could use these scenarios and findings to study further AAM services in airspace.
Large-scale planned special events (PSEs) can pose unique transportation and logistics challenges. Data collection and simulation are important tools to address these challenges, although they are often difficult because of event size and complexity. This paper discusses methods to address the challenge of multimodal simulation at large PSEs through the context of AirVenture, a large week-long airshow organized by the Experimental Aircraft Association in Oshkosh, Wisconsin. Sampling and data collection techniques are discussed for a variety of modal processes like private vehicles, pedestrians, and shuttles, and for different situations like vehicle arrivals and departures, pedestrian queues, and shuttle systems. A flexible simulation framework for integrating these three modes and numerous activities is developed as a network of heterogeneous queues and queue-dependent choices. The simulation tested a variety of proposed policy changes around the site, including rerouting shuttle lines, and adjusting the system of vehicle arrivals to the site. Results of this study demonstrate the effectiveness and flexibility of the data collection and simulation methodologies. The techniques developed in this work can be used to improve planning and transportation systems at many other forms of PSE.
Urban air mobility (UAM) systems include a network of (un)structured airspaces. The geometry and operations on these networks affect system performance across several goals including safety, efficiency, and externalities. The primary goal of this work is to find and illustrate the safety, efficiency, and externality trade-offs between different styles of network architecture. To do so, this paper uses a microscopic traffic simulator for UAM aircraft to experiment with different network architectures. Key performance measures reflecting the varied system goals are considered. Comparisons of network performance at varying demand levels illustrate the different behavior of traffic and congestion for each network architecture. The results indicate that there is no one-size-fits-all solution for network designs, rather there are trade-offs between designs. Fewer network restrictions and organization allow for routing efficiencies at the cost of a higher conflict rate and greater congestion at high demand levels. Greater network restrictions and organization can reduce the conflict rate and effectively manage high levels of demand but may suffer from locally concentrated conflicts and trajectories in addition to routing inefficiency. The insights will interest airspace researchers, regulators, and UAM operators as they consider appropriate future designs of airspace to accommodate UAM operations.
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