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At least 595 records · Page 33

Quantifying Effects of Departure and Flight Time Uncertainty on Urban Air Mobility Operations

Demand capacity balancing is a key mechanism for maintaining safe and efficient Urban Air Mobility (UAM) operations. However, uncertainties such as departure delays and flight time variation may reduce the effectiveness of algorithms used for balancing and detrimentally impact the safety and efficiency of UAM operations. In this paper, the effects of these uncertainties on UAM operations are quantified by modeling a distribution of departure and flight time errors. A route network in the Dallas/Fort Worth metropolitan area was used to simulate traffic demand with and without uncertainty. Simulations were conducted with three main models of uncertainty – first uncertainty in departure time delay resulting in late takeoffs, second with uncertainty in flight times in addition to departure delays, and finally, uncertainty in departure times that cause either late or early takeoffs. Each of these simulations were performed using varied standard deviations to fully understand the effects of uncertainties. Results from these simulations were compared to a baseline simulation using the same parameters, but without any uncertainty. The results suggest that both safety and efficiency are significantly impacted by uncertainty even with relatively low uncertainty introduced. These results work towards quantifying the effects of uncertainty in flight scheduling for UAM. They will also aid in the further development of the demand capacity balancing algorithms for UAM operations and associated air traffic management.

Urban Air Mobility↗

Design of a Six-Tiltrotor Concept Vehicle for Urban Air Mobility

NASA has developed a series of aircraft concepts known as reference vehicles for urban air mobility operations to facilitate research and development, enabling system-level comparisons between design candidates. In this study, new six-tiltrotor reference vehicles with full-electric and turboelectric propulsion systems were developed using the NASA Design and Analysis of Rotorcraft (NDARC) tool. The sizing results and performance metrics of these new vehicles are presented, along with comparisons to existing reference vehicles. The turboelectric six-tiltrotor is shown to be the fastest among the turboelectric reference vehicles. Although the full-electric six-tiltrotor is not as fast as the turboelectric version, it still offers considerable speed along with increased safety compared to the tiltrotor reference vehicle.

Six-Tiltrotor↗

Refined Analysis of CO2 Emissions in Urban Air Mobility Networks

In this study, we examine the environmental impact of Urban Air Mobility (UAM) operations as measured via carbon dioxide (CO2) emissions by leveraging a computational model from previous studies that has been refined and expanded. Several scenarios are examined in which total transportation emissions for a representative day in a metro area are distributed differently among vehicle types and transportation modes. Specifically, we investigate the use of electric air vehicles in a UAM network; the increasing presence of electric ground vehicles for ground transportation; the impacts from implementing ridesharing in the UAM mode; and the effects of varying the electricity grid emissions. Results for a case study in the Chicago, IL metro area indicate that incorporating electric ground vehicles and UAM ridesharing can both lead to reduced CO2 emissions. These preliminary results indicate that carbon emissions from a UAM system leveraging ridesharing and all-electric aircraft may not be a practical operational limit on UAM, though further improvements to the modeling are warranted.

advanced air mobility↗

Wake Disturbance-Based Separation Evaluation for Urban Air Mobility Aircraft

This paper builds upon previous research to evaluate Urban Air Mobility (UAM) flight dynamics in the presence of wake disturbances. A model for fixed-wing-generated wake effects is applied to a Revolutionary Vertical Lift Technology (RVLT) Lift+Cruise UAM trail aircraft operating in the fixed-wing Cruise configuration. The wake effects are evaluated at various longitudinal and latitudinal separation configurations to determine the most hazardous wake encounter situation. Trim calculations and closed-loop simulations show a trailing aircraft flying directly into a wake vortex as the most hazardous scenario. Furthermore, trailing behind a larger aircraft at similar speeds greatly increases the safe separation distance. These considerations indicate a need for dynamic pairwise separation criteria to enable dense Advanced Air Mobility (AAM) operations while maintaining safety.

Urban Air Mobility↗

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This presentation introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗

Refined Analysis of CO2 Emissions in Urban Air Mobility Networks

In this study, we examine the environmental impact of Urban Air Mobility (UAM) operations as measured via carbon dioxide (CO2) emissions by leveraging a computational model from previous studies that has been refined and expanded. Several scenarios are examined in which total transportation emissions for a representative day in a metro area are distributed differently among vehicle types and transportation modes. Specifically, we investigate the use of electric air vehicles in a UAM network; the increasing presence of electric ground vehicles for ground transportation; the impacts from implementing ridesharing in the UAM mode; and the effects of varying the electricity grid emissions. Results for a case study in the Chicago, IL metro area indicate that incorporating electric ground vehicles and UAM ridesharing can both lead to reduced CO2 emissions. These preliminary results indicate that carbon emissions from a UAM system leveraging ridesharing and all-electric aircraft may not be a practical operational limit on UAM, though further improvements to the modeling are warranted.

advanced air mobility↗

Analysis of Traffic Flow in Structured Urban Airspace Networks with MFD-based Feedback Control

This research delves into applying the Macroscopic Fundamental Diagram (MFD) concept to structured airspace networks for comprehensive aggregate modeling and introduces a feedback-based departure function aimed at optimizing traffic flow. Previous studies have rarely examined structured airspace networks featuring non-stationary vehicles through the MFD perspective. We devised a scenario grounded in practical applications, featuring a multi-lane network with explicit lane-changing behavior. The MFD effectively captured the open-loop response, displaying a low-scatter, unimodal curve on the flow versus occupancy plot. Drawing inspiration from the ground transportation ramp-metering strategies, a proportional-integral-based controller was developed. Extensive simulation outcomes suggest that feedback control, informed by MFD, holds significant potential for managing traffic flow in Urban Air Mobility (UAM) environments; a reduction of 80% in the peak number of vehicles in a holding pattern was observed for a slight reduction in throughput in this study.

MFD↗

A Decade of Salt Marsh Elevation Change in New York City’s Coastal Urban Parks

Coastal salt marshes of the eastern United States are particularly vulnerable to accelerated sea level rise, and urban marshes are at greater risk of erosion, inundation, and conversion to mudflat if left unmanaged. To guide New York City (NYC) salt marsh restoration strategies, NYC Parks collected up to 10 years of salt marsh elevation change data through 2020 at six salt marsh sites using the Surface Elevation Table-Marker Horizon (SET-MH) method, conducted a salt marsh trends analysis to determine shoreline change from 1974 to 2012, and conducted a salt marsh conditions assessment. We found that the citywide average surface elevation trend of 3.31 mm yr −1 was not significantly different from the 30-year (1990–2020) Relative Sea Level Rise of 4.23 mm yr −1 at The Battery, NY, tide station, probably due to high variability across and within sites. We also found that accretion rates differed across sites and watersheds, and sites situated lower in the tidal zone had higher accretion rates. Notably, Jamaica Bay’s Idlewild salt marsh, long suspected of being sediment-starved and ranking lowest in our conditions assessment, had the highest accretion rate at 9.5 mm yr −1 . Our salt marsh trends analysis also showed marsh loss at the shoreline edge, bare ground cover, and other indicators of marsh degradation. In mitigating marsh loss, the design grades for our recent wetland restoration projects enlarge the upper elevation ranges of the low- and high-marsh zones and incorporate wider and more gradual slopes in upland transition zones to enable inland marsh migration.

Salt marsh elevation change↗

Evaluation of Initial and Mid-Term Air Traffic Procedures for Urban Air Mobility

Urban air mobility (UAM) operations are expected to expand in scale over the next several years as novel aircraft types, including electric vertical takeoff and landing aircraft, are certified and begin operations. These new aircraft may increase safety, decrease noise, and lower operating costs compared with helicopters, allowing them to operate in ways existing aircraft do not. It is vital that these expanded operations are compatible with and do not disrupt existing operations or the air traffic management system. To study the ways in which scaled UAM operations can best integrate in the national airspace system, NASA and Joby Aviation partnered to conduct a high-fidelity air traffic controller-in-the-loop study. Building on air traffic procedures used to manage high tempo operations in other parts of the airspace, new procedures, routes, and communications protocols were developed and tested by retired controllers in NASA’s Future Flight Central tower simulation facility. In addition, new cooperative airspace constructs in the form of corridors were developed to understand their potential contributions to even greater scales of operation. The controllers managed traffic scenarios in the Dallas-Fort Worth and Dallas Love Field airports consisting of fleets of up to 100 UAM aircraft operating alongside traditional traffic. Metrics for air traffic controller workload, duration of communications, departure delays, and other measures of allowable aircraft throughput were collected. The analysis indicates that using today’s procedures for initial UAM operations under nominal conditions could enable up to 40 operations per hour to an airport’s central terminal area if that involved crossing a runway and up to 55 operations per hour if reaching the central terminal did not involve crossing a runway. Operations at these tempos did not delay or otherwise interfere with simulated runway traffic and were rated acceptable by the air traffic controllers. The new corridor constructs dramatically lowered controller workload in certain circumstances, suggesting they may be effective in further increasing the allowable scale of operations.

Advanced Air Mobility↗

Exploring Ridesharing in Passenger Urban Air Mobility: A Comparative Analysis

There is growing interest in urban air mobility (UAM) as an alternative for passenger and cargo transport around metropolitan areas in a multimodal transportation system that leverages small, electric aircraft. Ridesharing has been proposed as a means of making UAM passenger trips more affordable and environmentally friendly. We present a UAM ridesharing model integrated into an existing computational framework for analyzing daily work commute trips within a metropolitan area. We leverage this model to estimate the potential demand for ridesharing-enabled UAM trips within six metropolitan areas across the United States: Chicago, IL; Cleveland, OH; Dallas, TX; Denver, CO; New York City, NY; and Orlando, FL. We compare results for each metropolitan area with and without ridesharing. Results indicate that ridesharing enables at least an order of magnitude more UAM-preferring passengers than without ridesharing, though specifics vary across metropolitan areas and network sizes. Enabling ridesharing in UAM also considerably lowers the mean and mode value of time for passengers that select the UAM mode, indicating that ridesharing can help make UAM more economically accessible to a larger set of the population. An important caveat is that the UAM ridesharing model does not account for operational constraints, such as aerodrome capacity and aircraft availability, and relies on a perfect knowledge of passenger movements and mode preferences. This leads to high UAM ridesharing volumes that are unlikely to reflect real-world UAM operations and thus serves as an upper bound estimate.

advanced air mobility↗

Quantifying the Effects of Departure and Flight Time Uncertainty on Urban Air Mobility Operations

Demand capacity balancing is a key mechanism for maintaining safe and efficient Urban Air Mobility (UAM) operations. However, uncertainties such as departure delays and flight time variation may reduce the effectiveness of algorithms used for balancing and detrimentally impact the safety and efficiency of UAM operations. In this paper, the effects of these uncertainties on UAM operations are quantified by modeling a distribution of departure and flight time errors. A route network in the Dallas/Fort Worth metropolitan area was used to simulate traffic demand with and without uncertainty. Simulations were conducted with three main models of uncertainty – first uncertainty in departure time delay resulting in late takeoffs, second with uncertainty in flight times in addition to departure delays, and finally, uncertainty in departure times that cause either late or early takeoffs. Each of these simulations were performed using varied standard deviations to fully understand the effects of uncertainties. Results from these simulations were compared to a baseline simulation using the same parameters, but without any uncertainty. The results suggest that both safety and efficiency are significantly impacted by uncertainty even with relatively low uncertainty introduced. These results work towards quantifying the effects of uncertainty in flight scheduling for UAM. They will also aid in the further development of the demand capacity balancing algorithms for UAM operations and associated air traffic management.

Urban Air Mobility↗

Separation Assurance in Urban Air Mobility Systems Using Shared Scheduling Protocols

Ensuring safe separation between aircraft is a critical challenge in air traffic management, particularly in urban air mobility (UAM) environments where high traffic density and low altitudes require precise control. In these environments, conflicts often arise at the intersections of flight corridors, posing significant risks. We propose a tactical separation approach leveraging shared scheduling protocols, originally designed for Ethernet networks and operating systems, to coordinate access to these intersections. Using a decentralized Markov decision process framework, the proposed approach enables aircraft to autonomously adjust their speed and timing as they navigate these critical areas, maintaining safe separation without a central controller. We evaluate the effectiveness of this approach in simulated UAM scenarios, demonstrating its ability to reduce separation violations to zero while acknowledging trade-offs in flight times as traffic density increases. Additionally, we explore the impact of non-compliant aircraft, showing that while shared scheduling protocols can no longer guarantee safe separation, they still provide significant improvements over systems without scheduling protocols.

Separation Assurance↗

Provider of Services for Urban Air Mobility (PSU) Prototype Simulation (X5) Final Report

Urban Air Mobility (UAM) is a new air transportation service concept to carry passengers or cargo in metropolitan areas, leveraged by innovative aircraft and air traffic automation technologies. NASA has conducted a series of simulations, called the X-series simulation, to evaluate the UAM concept of operations and support the development of airspace procedures and services for UAM operations. The simulation called “X5” was conducted in 2023 to test a Provider of Services for UAM (PSU) prototype developed by NASA for UAM flight planning, strategic conflict management support, and data exchange between UAM operators. In this simulation, two strategic conflict management capabilities, Demand-Capacity Balancing and Sequencing and Scheduling, were further investigated. This document describes the UAM system architecture modeled, the X5 simulation environment to be executed (e.g., traffic scenario and UAM airspace construct), and the strategic conflict management processes developed and evaluated in this study. Then, the simulation results are provided using several system performance metrics, such as the number of operations planned and activated, demand-capacity imbalances detected and resolved, and pre-departure delays. Based on these metrics, the test findings and lessons learned from this simulation are discussed. NASA developed a PSU prototype as part of a reference implementation of UAM system architecture and evolved strategic conflict management capabilities for UAM operations from the previous collaborative simulations with industry partners. Below is the summary of the achievements: - Aligned NASA’s UAM reference architecture with the FAA’s UAM ConOps notional architecture - Extended UAM airspace management capabilities to include 1) Demand-Capacity Balancing (DCB) to ensure operators coordinate planned usage of shared vertiports, and 2) Sequencing and Scheduling (S&S) at UAM corridor entry and exit points to help facilitate an orderly flow of traffic - Defined the PSU information exchange APIs and requirements towards informing industry standards - Developed and tested a NASA PSU prototype as reference implementation to validate the requirements and APIs - Developed a prototype service connecting NASA’s PSU and the FAA system for testing future PSU-ATM interface requirements - Tested NASA-developed assumptions for UAM operations such as airspace design, procedures, vehicle performance, and strategic conflict management methods to inform future Cooperative Operating Practices (COPs) development with industry - Evaluated system performance metrics such as number of simultaneous operations and ground delays that can help define system-level requirements. The simulation results showed that the UAM traffic demand could be managed to minimize the needs of tactical separation provision with ground delays assigned by DCB and S&S. These accomplishments and the lessons learned from the PSU Prototype X5 simulation activities will be valuable inputs for the Air Mobility Pathfinders (AMP) project, which is NASA’s new project to create and evaluate a reference architecture for safe, secure, and scalable UAM operations.

Simulation↗