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NASA NTRS2022

NASA Concept Vehicles and the Engineering of Advanced Air Mobility Aircraft

NASA is conducting investigations in Advanced Air Mobility (AAM) aircraft and operations. AAM missions are characterised by ranges below 300 nm, including rural and urban operations, passenger carrying as well as cargo delivery. Urban Air Mobility (UAM) is a subset of AAM and is the segment that is projected to have the most economic benefit and be the most difficult to develop. The NASA Revolutionary Vertical Lift Technology project is developing UAM VTOL aircraft designs that can be used to focus and guide research activities in support of aircraft development for emerging aviation markets. These NASA concept vehicles encompass relevant UAM features and technologies, including propulsion architectures, highly efficient yet quiet rotors, and aircraft aerodynamic performance and interactions. The configurations adopted are generic, intentionally different in appearance and design detail from prominent industry arrangements. Already these UAM concept aircraft have been used in numerous engineering investigations, including work on meeting safety requirements, achieving good handling qualities, and reducing noise below helicopter certification levels. Focusing on the concept vehicles, observations are made regarding the engineering of Advanced Air Mobility aircraft.

eVTOL↗
NASA NTRSDate not supplied

Eye Glance Behaviors of Ground Control Station Operators in a Simulated Urban Air Mobility Environment

Research into concepts such as advanced air mobility (AAM) and urban air mobility (UAM) offers an opportunity for successfully and safely adding new classes of vehicles into the National Airspace System. However, a need exists for research into the human factors associated with these concepts. In this paper, we evaluate the gaze behaviors of three remote ground control station operators (GCSOs) conducting simulated UAM operations. The participants monitored and controlled an unmanned aircraft system (UAS) from pre-flight to landing using ground control station (GCS) software across nine scenarios within a remote UAS operations center at NASA Langley Research Center (LaRC). As this work was exploratory, descriptive statistics were calculated to provide some initial insight into GCSO gaze patterns associated with the GCS display. Scenarios that required the operator to directly interact with an airspace scheduling system off-screen resulted in fewer on-screen glances than scenarios that did not include direct interactions with the off-screen system. After investigating several areas of interest (AOIs) within the GCS display, participants primarily viewed three AOIs: the map, vehicle status, and operations checklist. The results yielded several GCS design and operational improvement recommendations to include: (a) adding altitude information to the vehicle icon, (b) adding additional traffic information, and (c) including additional GCS training, to reduce the need to scan an operations checklist, which would allow allocation of visual attention towards other AOIs.

Urban Air Mobility↗
NASA NTRSDate not supplied

Theoretical and Simulated Capacity of Urban Air Mobility Airspace Characteristics

As interest in urban air mobility grows, as are the optimistic predictions for potentially hundreds of simultaneous operations within a given metropolitan airspace. This high density of traffic poses a challenge for safe, efficient, and timely operations, particularly when realistic airspace restrictions, fleet sizes, and fluctuating demand are considered. Routes for urban air mobility aircraft, similar to automotive roadways more than other types of airways, are one proposed solution for traffic management. This paper identifies several potential components of urban air mobility routes and compares their numerically predicted maximum capacity with what is achieved in a realistic simulation that includes airspace restrictions, parking limitations, fleet sizes, and uneven demand.

Urban Air Mobility↗
NASA NTRSDate not supplied

Theoretical and Simulated Capacity of Urban Air Mobility Airspace Characteristics

As interest in urban air mobility grows, as are the optimistic predictions for potentially hundreds of simultaneous operations within a given metropolitan airspace. This high density of traffic poses a challenge for safe, efficient, and timely operations, particularly when realistic airspace restrictions, fleet sizes, and fluctuating demand are considered. Routes for urban air mobility aircraft, similar to automotive roadways more than other types of airways, are one proposed solution for traffic management. This paper identifies several potential components of urban air mobility routes and compares their numerically predicted maximum capacity with what is achieved in a realistic simulation that includes airspace restrictions, parking limitations, fleet sizes, and uneven demand.

Urban Air Mobility↗
NASA NTRS2020

In-time System-wide Safety Assurance (ISSA) Concept of Operations and Design Considerations for Urban Air Mobility (UAM)

Emerging operations involving Advanced Air Mobility (AAM), such as Urban Air Mobility (UAM), pose a challenge to safety assurance and to accessibility within the National Airspace System (NAS).In particular, the public has a low tolerance for risk in aviation and the current NAS tends to be labor-intensive with limited ability to scale up for UAM. In response to this landscape, NASA is collaborating with industry to define a Concept of Operations (ConOps) for In-time System-Wide Safety Assurance (ISSA) for scalable UAM involving a service-oriented architecture. This architecture focuses safety investments for technological solutions that can overcome safety related barriers for emerging operations. By working with industry, consensus can be reached on desirable system traits that are based on integration and fusion of data and leverage increasingly autonomous and automated systems. These complex systems can identify anomalies, precursors, and trends that together enable more proactive management of operational risks. AAM and UAM elevate the need for risk management in relation to increasing density and heterogeneity of vehicles and operations. Whereas safety in today’s NAS is built on a history of programs and technologies that react to incidents and accidents, AAM presents an opportunity to leverage that experience and its implications and proactively integrate safety into the earliest designs of vehicles and systems. In a perfect world AAM and UAM would not be inherently dangerous but until then ensuring the highest quality of safety requirements is the bridge to mitigating risks.

In-Time System-Wide Safety Assurance↗
NASA NTRSDate not supplied

Urban Air Mobility Community Noise Test Planning

The term “Advanced Air Mobility” has been adopted by NASA to describe safe, sustainable, affordable, and accessible aviation for transformational local and intraregional missions. By this definition, Advanced Air Mobility includes both “rural” and “urban” applications including cargo and passenger transport missions, and other aerial missions (e.g., infrastructure inspection). There will be a range of aircraft types performing such missions, including small and medium Unmanned Aircraft Systems (UAS), electric Conventional Takeoff and Landing (eCTOL) aircraft, and electric Vertical Takeoff and Landing (eVTOL) aircraft. Urban Air Mobility (UAM) is a challenging use case for transporting cargo and passengers in an urban environment and is a new opportunity for aviation that could revolutionize the transportation system. The National Aeronautics and Space Administration and the Noise Division of the Federal Aviation Administration Office of Environment and Energy have initiated discussions for planning UAM community noise test(s) at the end of this decade. This presentation discusses the test goals, candidate test objectives, and some of activities needed in preparation for the test(s). It also draws distinctions between the type of study envisioned (observational vs. staged), and between it and recent and planned studies on large fixed-wing transports and commercial supersonic transports.

urban air mobility↗
NASA NTRSDate not supplied

Cyber Resiliency and the Implementation of a Host-Based Intrusion Detection System in an Urban Air Mobility Environment

With the growth in Urban Air Mobility systems and the increasing reliance on interconnected technologies, ensuring the security of these complex components has become critical. As cities evolve into smart urban centers, the vulnerability to cyber threats escalates, possibly endangering citizens safety and the efficiency of transportation networks.In response to these challenges, this paper presents a study on the need for cyber resilient techniques within future air traffic environments. It will pay specific attention to the implementation of a Host-Based Intrusion Detection System (HIDS) utilizing Atomic OSSEC software, tailored specifically to a NASA simulation of an UrbanAirMobility environments’ unique demands. Further, this study seeks to outline the rational for NASA’s recommendation for a HIDS in such environments. It explores the design, development, and deployment of the proposed HIDS, focusing on its adaptability to monitor the hybrid nature of the Urban Air Mobility environment. Leveraging machine learning algorithms and anomaly detection techniques, the HIDS is equipped to continuously monitor and analyze the behavior of individual host systems, vehicles, and devices, thereby providing a proactive approach to threat detection. Implementing a HIDS is a pivotal strategy for enhancing cyber resiliency, as it gives an organization granular visibility into internal system activities, enables rapid detection and response to anomalous behavior and cyber threats, and fortifies the organizations overall cybersecurity posture. Finally, this study aims to provide recommendations and include learned takeaways that the Urban Air Mobility industry should consider. In brief, this paper highlights the significance of host-based intrusion detection in UrbanAirMobility environments and underscores the necessity of tailored security solutions to safeguard against emerging cyber threats.

UAM↗
NASA NTRSDate not supplied

Individual Response Trends to Urban Air Mobility Noise in A Laboratory Study

Advanced Air Mobility, of which Urban Air Mobility (UAM) is a subset, presents new opportunities for more dynamic aviation transportation systems. It is essential to understand the human response to the noise of these vehicles for sustainable operations. This research aims to investigate the relationship between the noise level and number of events on individual human annoyance to UAM vehicle noise. A “noise and number” laboratory psychoacoustic study was conducted in the Exterior Effects Room at NASA Langley Research Center in January 2023. A total of 38 participants listened to 4-minute audio clips of UAM vehicle flyover noise and provided their annoyance response on an 11-point numerical scale. A test hypothesis was that annoyance to multiple flyovers can be found by adding the annoyance responses to individual flyovers. Results for the overall test subject pool suggest that annoyance grows faster than hypothesized as the number of aircraft events increases. This trend of faster annoyance growth only seems to hold when the individual flyovers are heard as distinct events. Parsing the data down to individuals provides further insight into the mechanisms contributing to the increased annoyance with number of events.

noise and number↗
NASA NTRSDate not supplied

Optimizing Urban Air Mobility Research Through Bi-Directional Integration Processes for Effective Verification and Validation

Urban Air Mobility (UAM), a subset of Advanced Air Mobility (AAM), aims to revolutionize metropolitan transportation. This paper explores an engineering process framework within National Aeronautics and Space Administration (NASA)’s Air Mobility Pathfinders (AMP) project, which is focused on the safe scaling and seamless integration of UAM operations within the National Airspace System (NAS). Progressing through three phases — Initial, Midterm, and Mature — the Federal Aviation Administration (FAA)’s UAM Concept of Operations (ConOps) describes a proposed path for the evolution of UAM operations, presenting multifaceted challenges in technology, regulation, and stakeholder engagement. With this ConOps as a basis, the AMP project is executing research, development, test, and evaluation activities aimed at delivering validated reference architectures for the Midterm phase. This paper illuminates the pivotal role of the systems engineering process in managing these technical efforts. Robust verification and validation methods, along with systematic bi-directional integration process, enhance the ability to conduct research into the design and evolution of safe, efficient, and reliable UAM systems. In this paper a systematic framework will be presented and shown to facilitate interactions between UAM stakeholders and to effectively manage the complex architecture of UAM operations in the NAS.

National Airspace System↗
NASA NTRS2025

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↗
NASA NTRSDate not supplied

An Overview of Advanced Air Mobility Research at NASA

Advanced Air Mobility (AAM) will enable new types of aircraft to operate more cleanly, efficiently, and quietly, complemented by higher levels of autonomy and automation, and supported by air traffic management systems and infrastructure. The operations that these aircraft and systems are intended to conduct are designed to support missions that cover a varied set of use cases. The National Aeronautics and Space Administration (NASA) has been helping to lead the way in its AAM research through a broad portfolio of efforts that leverages multiple internal activities and external collaborations with industry and government. As the AAM concept has continued to advance, it has also become clear that there are very likely great benefits in its application to disaster response and the challenges posed by such complex events. In this application, NASA is leveraging its foundational work performed in partnership with the Japan Aerospace Exploration Agency (JAXA) on integrated unmanned and manned aircraft operations in disaster response situations. The joint NASA and JAXA work, along with the ongoing AAM efforts, have contributed to the formulation of a new project that will expand the scope of technology integration with an initial focus on wildland firefighting.

advanced air mobility↗
NASA NTRSDate not supplied

Advancing Air Mobility: Few-Shot Learning in Airspace Research and Development

The advancement of Air Mobility, particularly in the context of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM), represents a transformative shift in aviation's role in modern society. A comprehensive understanding of requirement consistency is paramount for fostering interoperability, standardization, and cost-effectiveness within airspace systems. This paper introduces a novel approach utilizing a pretrained Sentence Transformers model and few-shot learning to address this crucial aspect task of flagging potentially inconsistent requirements. Few-shot learning supports the development of this future through ensuring the accuracy and consistency of identified requirements with little human oversight. This approach offers a promising solution to the challenges of requirement consistency identification in airspace systems. By harnessing the power of advanced NLP techniques with fine-tuned models, stakeholders can enhance efficiency, accuracy, and scalability; ultimately fostering improved interoperability, standardization, and cost-effectiveness in airspace management.

Natural Language Processing↗
NASA NTRSDate not supplied

A Psychoacoustic Test on the Effect of Masking on Annoyance to Urban Air Mobility Vehicle Noise

Urban Air Mobility (UAM) vehicles have a large range of designs and configurations that lead to new noise characteristics and potentially different perceptual responses when compared to traditional aircraft. In addition, UAM vehicles are expected to operate around and within densely populated regions where the presence of ambient background noise is often present. Strategically, this can be leveraged to inform vehicle design and operations to partially or completely mask UAM noise, allowing for mitigation of negative responses and an increased number of allowed operations. A psychoacoustic test was conducted to investigate how masking effects can influence the annoyance response to a low frequency harmonic tone complex (80-320 Hz). To do this, five test subjects compared their annoyance response to the low frequency tonal noise with a higher frequency broadband noise (10dB down bandwidth between 300-2000 Hz), with and without a masking noise present. Detection thresholds were also measured for both sounds to help fit a model to the data. Although the effect of masking on annoyance is complex, results indicate that for some individuals, masking leads to a lower annoyance than the sound level alone would predict.

Matthew Boucher↗
NASA NTRSDate not supplied

Urban Air Mobility National Campaign Test Series

The Urban Air Mobility (UAM) National Campaign test series is designed to promote public confidence in UAM safety, facilitate community-wide learning while capturing the public’s imagination, and give prospective vehicle manufacturers and operators, and prospective airspace service providers, insights into the evolving regulatory and operational environment. The National Campaign is also intended to support requirements and system development for Urban Air Mobility through integrated demonstrations of candidate vehicles and airspace in operational scenarios critical to scalable commercialization. The NASA National Campaign series will facilitate bringing together vehicle and airspace service providers to demonstrate industry’s concept and technology maturity levels with respect to vehicle performance, safety assurance, and airspace interoperability solutions for civil use.

Urban Air Mobility↗
NASA NTRSDate not supplied

A Data Analysis Approach for Simulations of Urban Air Mobility Operations

For the Urban Air Mobility (UAM) industry, NASA has defined a series of UAM Maturity Levels (UML) corresponding to increasingly more complex and operationally dense UAM operations. In support of the gradual progression towards higher UML levels, NASA is currently conducting a set of UAM air traffic simulations—collectively referred to as X4. This paper describes a set of system effectiveness measures, and their associated metrics, for data analysis of X4 simulations. The descriptions, rationales, and calculation procedures for two metrics to be used in data analysis of simulation results, the number of predicted demand-capacity imbalances and the pre-departure delays, are described. Results from data analysis of one set of simulation runs are presented to demonstrate how these metrics support the assessment of performance of the system architecture for X4 simulations and the verification of experiment requirements.

Urban Air Mobility↗
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗