Eye Glance Behaviors of Ground Control Station Operators in a Simulated Urban Air Mobility Environment
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Urban Air Mobility↗
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Design of a Tiltwing Concept Vehicle for Urban Air Mobility
NASA is establishing a fleet of conceptual air vehicle designs to support research and development for Urban Air Mobility (UAM). This fleet of vehicles will enable examination of the sensitivity of UAM vehicle designs to technology assumptions, identify key research and development needs for UAM aircraft, and provide the UAM community with reference vehicles that are publicly available and based upon known assumptions. To date, four six-passenger reference vehicles have been established: a quadrotor, a side-by-side, a lift-plus-cruise, and a quiet single main rotor helicopter; this paper adds a tiltwing vehicle to the fleet. This paper details the design process that was followed in order to establish the tiltwing vehicle in the fleet, including early conceptual design decisions, sizing and configuration trades, structural analyses, proprotor design and aeroacoustic predictions, and aerodynamic analyses. The resulting tiltwing vehicle uses a turboelectric propulsion system to power six proprotors positioned on a tilting main wing and two tilting proprotors positioned on the horizontal tail. This paper also compares the resulting tiltwing vehicle with the other six-passenger reference vehicles, including an updated lift-plus-cruise vehicle, and then proposes future studies. The fleet of UAM reference vehicles will continue to evolve; subsequent versions of the reference vehicles will be based upon the results of future trade studies and technology developments.
Urban Air Mobility↗
Air Traffic Management Response to Vertiport Closure
Increasing quantities of urban air mobility operations requires consideration of various contingencies associated with novel operational tempos and airspace management practices. This paper explores a contingency scenario in which a single vertiport closes unexpectedly during high tempo operations. Dynamic re-planning is explored as a function performed both by operators using common operating procedures and through emergency assistance from air traffic control. Implications for airspace capacity, infrastructure requirements, and vehicle energy reserves are discussed.
UAM↗
Air Traffic Management Response to Vertiport Closure
Increasing quantities of urban air mobility operations requires consideration of various contingencies associated with novel operational tempos and airspace management practices. This paper explores a contingency scenario in which a single vertiport closes unexpectedly during high tempo operations. Dynamic re-planning is explored as a function performed both by operators using common operating procedures and through emergency assistance from air traffic control. Implications for airspace capacity, infrastructure requirements, and vehicle energy reserves are discussed.
UAM↗
Transportation Network Topologies
A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21PstP thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the 'Southwest Effect'). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.
Holmes, Bruce J.↗
Transportation Network Topologies
A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21st thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the Southwest Effect). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.
Holmes, Bruce J.↗
Design of a Multi-Tiltrotor Concept Vehicle for Urban Air Mobility: “Version 0” Design, Design Review: Nov 3, 2021
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Advanced Air Mobility↗
DANTi: A Tool for Assistive Detect and Avoid Research
This paper presents DANTi, a research tool developed at NASA Langley Research Center to support the validation of Assistive Detect and Avoid (ADAA) requirements for General Aviation (GA). ADAA is a future on-board aircraft technology intended to augment a pilot’s see-and-avoid capability by helping them identify and resolve traffic conflicts earlier and more efficiently. DANTi includes a realistic Electronic Flight Bag (EFB) display and a fast-time simulation environment that can be fully customized to meet different research requirements. DANTi is currently used within NASA efforts such as the Air Mobility Pathfinders project on future air transportation systems and a joint NASA/FAA Laboratory Integrated Test Environment (NFLITE) on next-generation airspace operations in urban environments. These efforts investigate ADAA requirements in advanced urban air mobility settings where new aircraft types, new services, and new traffic patterns will be integrated in an overall crowded airspace.
Detect and Avoid↗
What’s Next in Regional (Air) Mobility? Finding the next possible big ideas in selected problems
This presentation summarizes studies ongoing under the "What's Next in Regional (Air) Mobility" umbrella within the Intercenter Systems Analysis Team. It includes a look at the Regional Air Mobility (RAM) market potential, simulation of a RAM passenger network to gather statistics, and scrutinizes airport energy needs to support RAM operations. It also references a companion presentation provided by the DOT Volpe Center presented by Jacob Wishart related to RAM market and demand estimates.
Advanced Air Mobility↗
Sim to Flight: Evaluating Flight Path Management Automation in High Density Urban Environments
Combined simulation and flight testing enable the study of single- and multi-aircraft performance of onboard automation systems for dynamic flight path management (FPM). The National Aeronautics and Space Administration (NASA) is investigating system performance and functional capabilities of such automation for immersion into complex, high density, future operations such as Urban Air Mobility (UAM). This paper provides an overview of a series of interdependent sim-to-flight research activities involving large-scale batch simulations, human-in-the-loop verification, and flight-test validation of a research prototype FPM automation system. Together, they significantly contributed to a functional assessment of FPM automation functionality in a live-virtual-constructive (LVC) operating environment characterized by two live aircraft and hundreds of virtual aircraft interacting in a modeled complex urban airspace. Initial simulation and flight test results, future work, and conclusions are presented.
Advanced Air Mobility↗
Generic Urban Air Mobility Simulation
This research presents a simulation framework for autonomous research for a UAM vehicle using the NASA Revolutionary Vertical Lift Technology Lift+Cruise concept vehicle. Our research results were produced using the open-source, six degree of freedom, rigid-body, nonlinear generic urban air mobility (GUAM) simulation. The intent of this paper is to demonstrate the GUAM simulation and a series of Challenge Problems that our researchers have posed to the broader autonomous vehicle research community. Our team has developed the GUAM simulation for the express purpose of providing a high-fidelity transition vehicle dynamics model to foster collaboration and algorithm performance comparison across research teams. In this paper, we demonstrate some of the autonomous flight research challenges and some of our current approaches to tackling basic autonomous flight tasks (e.g., trajectory following, stationary and moving obstacle avoidance). Additionally, we propose some flight metrics to assess autonomous algorithm performance while accomplishing these basic autonomous tasks.
autonomous flight↗
An Overview of the Proprotor Performance Test in the 14- by 22-Foot Subsonic Tunnel
This work experimentally investigates the aerodynamic behavior of proprotors across a wide range of angles of attack. These flight conditions are intended to be representative of Urban Air Mobility (UAM) vehicle platforms that utilize articulating propulsors to transition from a vertical takeoff and landing (VTOL) phase typical of a conventional rotorcraft, to an axial mode of forward flight typical of a fixed-wing aircraft. These data are used to identify the potential limits of lower fidelity aerodynamic modeling tools, as well as to inform future acoustic phases of testing. Tests were conducted on two proprotor designs in the NASA Langley 14- by 22-Foot Subsonic Tunnel using an articulating propeller test stand. Hover results identified unique flow physics on one of the proprotors, including severe outboard flow separation and perpendicular blade vortex interactions on the outboard portions of the blades. Transition and forward flight conditions yielded very informative trends in terms of both on- and off-axis forces and moments against which low-fidelity prediction models were compared.
aerodynamics↗
Deep Learning-Based Negotiation Strategy Selection for Cooperative Conflict Resolution in Urban Air Mobility
This paper presents a collaborative conflict resolution technique using deep neural network-based intelligent search of the solution space. This approach offers a rapid convergence to a mutually acceptable solution for real-time conflict resolution, suitable for urban air mobility operations. Furthermore, the presented technique allows operational flexibility to the urban air mobility agents where these agents can collaboratively devise the solution via integrative negotiation, based on their local utility functions, as long as such a solution does not violate the global safety thresholds. The presented machine-to-machine negotiation method is built on our prior work on holistic assessment of the airspace and potential conflict detection implemented at-the-edge, onboard the unmanned aircraft systems. This paper extends the prior work to augment decision-making at-the-edge, thereby, promising a true distributed control architecture for urban air mobility. In this approach, each agent (a) builds a potential in-flight conflict map, (b) identifies the conflicting agents, (c) dynamically prepares a list of alternatives based on its current utility functions, (d) negotiates with the conflicting agents to pick one of these alternatives, and (e) implements the negotiated alternative to mutually resolve the conflict. Note that such an approach does not require a contingency plan to be made pre-flight, as the conflict resolution strategies are decided and negotiated in real time based on the present state of the agent. The contingency plan, if available, can serve as an input to the real-time conflict resolution strategy formulation, and also can be used as a fallback plan in case the negotiation fails and the impacted agents need to switch to a rule-based/supervisory resolution mode from the discussed distributed resolution mode. The presented collaborative negotiation-based conflict resolution technique incorporates a time-dependent reward function to catalyze collaborative resolution by incentivizing the agents with local and global rewards beneficial to their business operations.
Advanced Air Mobility↗
Acoustics Technical Working Group and UAM Noise Working Group Proceedings
The NASA Acoustics Technical Working Group Meeting originally started as a program planning meeting in 1992 and has grown through the years. The purpose of these biannual meetings is to foster communication and collaboration among NASA researchers and their university, industry, and government colleagues on activities and work of current and future mutual interest. The NASA-led Urban Air Mobility (UAM) Noise Working Group (UNWG) Meeting began in 2018 as a one-day meeting immediately following the Acoustics Technical Working Group Meeting. The UNWG utilizes four subgroups that conduct regular meetings throughout the year to focus on challenges facing UAM vehicles for community noise and acceptance. The four subgroups coordinate research for development of noise prediction tools/noise reduction technologies, ground and flight test methods, human response and metrics, and regulations and policy (led by the FAA). This work is a compilation of the presentations given at ATWG/UNWG Fall 2022 held in person and via Teams at NASA Glenn Research Center. All NASA content was previously submitted through STRIVES for public presentation. This is merely a compilation. Non-NASA content has permission to distribute. Slide 208 video is included in the Available Downloads as Medial.MOV.
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↗
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↗
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↗
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↗