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Serious Gaming for Test & Evaluation of Clean-Slate (Ab Initio) National Airspace System (NAS) Designs

Incremental approaches to air transportation system development inherit current architectural constraints, which, in turn, place hard bounds on system capacity, efficiency of performance, and complexity. To enable airspace operations of the future, a clean-slate (ab initio) airspace design(s) must be considered. This ab initio National Airspace System (NAS) must be capable of accommodating increased traffic density, a broader diversity of aircraft, and on-demand mobility. System and subsystem designs should scale to accommodate the inevitable demand for airspace services that include large numbers of autonomous Unmanned Aerial Vehicles and a paradigm shift in general aviation (e.g., personal air vehicles) in addition to more traditional aerial vehicles such as commercial jetliners and weather balloons. The complex and adaptive nature of ab initio designs for the future NAS requires new approaches to validation, adding a significant physical experimentation component to analytical and simulation tools. In addition to software modeling and simulation, the ability to exercise system solutions in a flight environment will be an essential aspect of validation. The NASA Langley Research Center (LaRC) Autonomy Incubator seeks to develop a flight simulation infrastructure for ab initio modeling and simulation that assumes no specific NAS architecture and models vehicle-to-vehicle behavior to examine interactions and emergent behaviors among hundreds of intelligent aerial agents exhibiting collaborative, cooperative, coordinative, selfish, and malicious behaviors. The air transportation system of the future will be a complex adaptive system (CAS) characterized by complex and sometimes unpredictable (or unpredicted) behaviors that result from temporal and spatial interactions among large numbers of participants. A CAS not only evolves with a changing environment and adapts to it, it is closely coupled to all systems that constitute the environment. Thus, the ecosystem that contains the system and other systems evolves with the CAS as well. The effects of the emerging adaptation and co-evolution are difficult to capture with only combined mathematical and computational experimentation. Therefore, an ab initio flight simulation environment must accommodate individual vehicles, groups of self-organizing vehicles, and large-scale infrastructure behavior. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ab initio simulation environment is similar to online gaming environments in which player participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual player's active participation.

Allen, B. Danette↗

Flight Demonstration of Unmanned Aircraft System (UAS) Traffic Management (UTM) at Technical Capability Level 4

The NASA Unmanned Aircraft Systems (UAS) Traffic Management (UTM) Project executed the fourth and final UTM Technical Capability Level demonstration between May and August 2019. Two Federal Aviation Administration (FAA)-designated UAS test sites managed the range, partners, and operations to meet the requirements set forth by the UTM Project. All stakeholders supported the execution of the flight testing through close collaboration. Results of the demonstration indicate the viability of the UTM concept to manage large scale operations and contingencies in an urban environment. The demonstration also provided insight into key technological gaps that must be addressed before such operations are routine, safe, and efficient. Standardization efforts related to UTM and the industry participants of those efforts can leverage the results and experiences of this flight activity to accelerate and more firmly ground forthcoming standards. The FAA and other regulators will be able to leverage results to inform future rule-making and identify additional gaps that require further analysis.

Unmanned Aircraft System Traffic Management↗

Control and Non-Payload Communications (CNPC) Prototype Radio - Generation 2 Security Flight Test Report

NASA Glenn Research Center (GRC), in cooperation with Rockwell Collins, is working to develop a prototype Control and Non-Payload Communications (CNPC) radio platform as part of NASA Integrated Systems Research Program's (ISRP) Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) project. A primary focus of the project is to work with the Federal Aviation Administration (FAA) and industry standards bodies to build and demonstrate a safe, secure, and efficient CNPC architecture that can be used by industry to evaluate the feasibility of deploying a system using these technologies in an operational capacity. GRC has been working in conjunction with these groups to assess threats, identify security requirements, and to develop a system of standards-based security controls that can be applied to the GRC prototype CNPC architecture as a demonstration platform. The proposed security controls were integrated into the GRC flight test system aboard our S-3B Viking surrogate aircraft and several network tests were conducted during a flight on November 15th, 2014 to determine whether the controls were working properly within the flight environment. The flight test was also the first to integrate Robust Header Compression (ROHC) as a means of reducing the additional overhead introduced by the security controls and Mobile IPv6. The effort demonstrated the complete end-to-end secure CNPC link in a relevant flight environment.

Communication Networks↗

Weather Requirements and Procedures for Step 1: High Altitude Long Endurance (HALE) Unmanned Aircraft System (UAS) Flight Operations in the National Air Space (NAS)

This cover sheet is for version 2 of the weather requirements document along with Appendix A. The purpose of the requirements document was to identify and to list the weather functional requirements needed to achieve the Access 5 vision of "operating High Altitude, Long Endurance (HALE) Unmanned Aircraft Systems (UAS) routinely, safely, and reliably in the National Airspace System (NAS) for Step 1." A discussion of the Federal Aviation Administration (FAA) references and related policies, procedures, and standards is provided as basis for the recommendations supported within this document. Additional procedures and reference documentation related to weather functional requirements is also provided for background. The functional requirements and related information are to be proposed to the FAA and various standards organizations for consideration and approval. The appendix was designed to show that sources of flight weather information are readily available to UAS pilots conducting missions in the NAS. All weather information for this presentation was obtained from the public internet.

Source record↗

Defining the Collision Avoidance Region for DAA Systems

Unmanned aircraft systems (UAS) will be required to equip with a detect-­‐and-­‐avoid (DAA) system in order to satisfy the federal aviation regulations to maintain well clear of other aircraft, some of which may be equipped with a Traffic Collision Avoidance System (TCAS) to mitigate the possibility of mid-­‐air collisions. As such, the minimum operational performance standards (MOPS) for UAS DAA systems are being designed with TCAS interoperability in mind by a group of industry, government, and academic institutions named RTCA Special Committee-228 (SC-228). This document will discuss the development of the spatial-­‐temporal volume known as the collision avoidance region in which the DAA system is not allowed to provide vertical guidance to maintain or regain DAA well clear that could conflict with resolution advisories (RAs) issued by the intruder aircraft's TCAS system. Three collision avoidance region definition candidates were developed based on the existing TCAS RA and DAA alerting definitions. They were evaluated against each other in terms of their interoperability with TCAS RAs and DAA alerts in an unmitigated factorial encounter analysis of 1.3 million simulated pairs.

collision avoidance region↗

AirSTAR Hardware and Software Design for Beyond Visual Range Flight Research

The National Aeronautics and Space Administration (NASA) Airborne Subscale Transport Aircraft Research (AirSTAR) Unmanned Aerial System (UAS) is a facility developed to study the flight dynamics of vehicles in emergency conditions, in support of aviation safety research. The system was upgraded to have its operational range significantly expanded, going beyond the line of sight of a ground-based pilot. A redesign of the airborne flight hardware was undertaken, as well as significant changes to the software base, in order to provide appropriate autonomous behavior in response to a number of potential failures and hazards. Ground hardware and system monitors were also upgraded to include redundant communication links, including ADS-B based position displays and an independent flight termination system. The design included both custom and commercially available avionics, combined to allow flexibility in flight experiment design while still benefiting from tested configurations in reversionary flight modes. A similar hierarchy was employed in the software architecture, to allow research codes to be tested, with a fallback to more thoroughly validated flight controls. As a remotely piloted facility, ground systems were also developed to ensure the flight modes and system state were communicated to ground operations personnel in real-time. Presented in this paper is a general overview of the concept of operations for beyond visual range flight, and a detailed review of the airborne hardware and software design. This discussion is held in the context of the safety and procedural requirements that drove many of the design decisions for the AirSTAR UAS Beyond Visual Range capability.

Laughter, Sean↗

Development of a High-Fidelity Simulation Environment for Shadow-Mode Assessments of Air Traffic Concepts

This paper will describe the purpose, architecture, and implementation of a gate-to-gate, high-fidelity air traffic simulation environment called the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Test Bed.The overarching purpose of the SMART-NAS Test Bed (SNTB) is to conduct high-fidelity, real-time, human-in-the-loop and automation-in-the-loop simulations of current and proposed future air traffic concepts for the Next Generation Air Transportation System of the United States, called NextGen. SNTB is intended to enable simulations that are currently impractical or impossible for three major areas of NextGen research and development: Concepts across multiple operational domains such as the gate-to-gate trajectory-based operations concept; Concepts related to revolutionary operations such as the seamless and widespread integration of large and small Unmanned Aerial System (UAS) vehicles throughout U.S. airspace; Real-time system-wide safety assurance technologies to allow safe, increasingly autonomous aviation operations. SNTB is primarily accessed through a web browser. A set of secure support services are provided to simplify all aspects of real-time, human-in-the-loop and automation-in-the-loop simulations from design (i.e., prior to execution) through analysis (i.e., after execution). These services include simulation architecture and asset configuration; scenario generation; command, control and monitoring; and analysis support.

human-in-the-loop↗

Considerations in Assuring Safety of Increasingly Autonomous Systems

Recent technological advances have accelerated the development and application of increasingly autonomous (IA) systems in civil and military aviation. IA systems can provide automation of complex mission tasks-ranging across reduced crew operations, air-traffic management, and unmanned, autonomous aircraft-with most applications calling for collaboration and teaming among humans and IA agents. IA systems are expected to provide benefits in terms of safety, reliability, efficiency, affordability, and previously unattainable mission capability. There is also a potential for improving safety by removal of human errors. There are, however, several challenges in the safety assurance of these systems due to the highly adaptive and non-deterministic behavior of these systems, and vulnerabilities due to potential divergence of airplane state awareness between the IA system and humans. These systems must deal with external sensors and actuators, and they must respond in time commensurate with the activities of the system in its environment. One of the main challenges is that safety assurance, currently relying upon authority transfer from an autonomous function to a human to mitigate safety concerns, will need to address their mitigation by automation in a collaborative dynamic context. These challenges have a fundamental, multidimensional impact on the safety assurance methods, system architecture, and V&V capabilities to be employed. The goal of this report is to identify relevant issues to be addressed in these areas, the potential gaps in the current safety assurance techniques, and critical questions that would need to be answered to assure safety of IA systems. We focus on a scenario of reduced crew operation when an IA system is employed which reduces, changes or eliminates a human's role in transition from two-pilot operations.

Alves, Erin E.↗

NASA's UAS [Unmanned Aircraft Systems] Related Activities

NASA continues to operate all sizes of UAS in all classes of airspace both domestically and internationally. Missions range from highly complex operations in coordination with piloted aircraft, ground, and space systems in support of science objectives to single aircraft operations in support of aeronautics research. One such example is a scaled commercial transport aircraft being used to study recovery techniques due to large upsets. NASA's efforts to support routine UAS operations continued on several fronts last year. At the national level in the United States (U.S.), NASA continued its support of the UAS Executive Committee (ExCom) comprised of the Federal Aviation Administration (FAA), Department of Defense (DoD), Department of Homeland Security (DHS), and NASA. The committee was formed in recognition of the need of UAS operated by these agencies to access to the National Airspace System (NAS) to support operational, training, development and research requirements. Recommendations were received on how to operate both manned and unmanned aircraft in class D airspace and plans are being developed to validate and implement those recommendations. In addition the UAS ExCom has begun developing recommendations for how to achieve routine operations in remote areas as well as for small UAS operations in class G airspace. As well as supporting the UAS ExCom, NASA is a participant in the recently formed Aviation Rule Making Committee for UAS. This committee, established by the FAA, is intended to propose regulatory guidance which would enable routine civil UAS operations. As that effort matures NASA stands ready to supply the necessary technical expertise to help that committee achieve its objectives. By supporting both the UAS ExCom and UAS ARC, NASA is positioned to provide its technical expertise across the full spectrum of UAS airspace access related topic areas. The UAS NAS Access Project got underway this past year under the leadership of NASA s Aeronautics Research Mission Directorate. This project is focused on advancing the state of the art and providing research and analysis results in the areas of Separation Assurance, Communications (non-governmental spectrum allocation for UAS), Certification, and Human System Integration (ground control station design/pilot interfaces). The project is working in close coordination with the FAA and industry standards organizations (e.g. RTCA SC 203). More details on this project are provided in a separate article in this year's yearbook

Bauer, Jeffrey↗

UAS CNPC Satellite Link Performance - Sharing Spectrum with Terrestrial Systems

In order to provide for the safe integration of unmanned aircraft systems into the National Airspace System, the control and non-payload communications (CNPC) link connecting the ground-based pilot with the unmanned aircraft must be highly reliable. A specific requirement is that it must operate using aviation safety radiofrequency spectrum. The 2012 World Radiocommunication Conference (WRC-12) provided a potentially suitable allocation for radio line-of-sight (LOS), terrestrial based CNPC link at 5030-5091 MHz. For a beyond radio line-of-sight (BLOS), satellite-based CNPC link, aviation safety spectrum allocations are currently inadequate. Therefore, the 2015 WRC will consider the use of Fixed Satellite Service (FSS) bands to provide BLOS CNPC under Agenda Item 1.5. This agenda item requires studies to be conducted to allow for the consideration of how unmanned aircraft can employ FSS for BLOS CNPC while maintaining existing systems. Since there are terrestrial Fixed Service systems also using the same frequency bands under consideration in Agenda Item 1.5 one of the studies required considered spectrum sharing between earth stations on-board unmanned aircraft and Fixed Service station receivers. Studies carried out by NASA have concluded that such sharing is possible under parameters previously established by the International Telecommunications Union. As the preparation for WRC-15 has progressed, additional study parameters Agenda Item 1.5 have been proposed, and some studies using these parameters have been added. This paper examines the study results for the original parameters as well as results considering some of the more recently proposed parameters to provide insight into the complicated process of resolving WRC-15 Agenda Item 1.5 and achieving a solution for BLOS CNPC for unmanned aircraft.

Pilotless aircraft↗

Identification and Reduction of Interactional Noise of a Quadcopter in Hover and Forward Flight Conditions

Advanced Air Mobility is a vision for a safe, accessible, and sustainable aviation system to transport people and cargo between places not served by traditional aviation. With this emerging transportation industry, there is motivation to characterize the noise of vehicles to determine their potential impacts on the community. An experimental testing campaign was conducted on a representative model of a small unmanned aircraft system in the NASA Langley Low Speed Aeroacoustic Wind Tunnel as a continuation of a previous testing campaign. The goals of the current test are to identify sources of interactional noise as well as to test custom-designed rotors and noise reduction devices. The tested noise reduction methods involve increasing the vertical distances between the rotors and the vehicle airframe as well as between the forward and aft rotor disk planes. These methods are intended to reduce rotor-airframe interaction noise in hover and fore-aft rotor wake ingestion noise in forward flight. A phased microphone array is also utilized to identify the locations of prominent noise generation for the different vehicle configurations in forward flight. Elevation of the rotors from the vehicle airframe yielded nearly 8 dBA overall noise reduction in forward flight, while yielding up to 4 dB reduction in overall tonal levels for one of the rotors in hover.

Nikolas S Zawodny↗

Common Operating Picture: UAV Security Study

This initial communication security study is a top-level assessment of basic security issues related to the operation of Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). Security considerations will include information relating to the use of International Civil Aviation Organization (ICAO) Aeronautical Telecommunications Network (ATN) protocols and applications identifying their maturity, as well as the use of IPV4 and a version of mobile IPV6. The purpose of this assessment is to provide an initial analysis of the security implications of introducing UAVs into the NAS.

Source record↗

UAS Modeling of the Communication Links Study Results

The Federal Aviation Administration (FAA) is the authority that grants access into, and operations within, the National Airspace System (NAS) for all aircraft, including Unmanned Aircraft Systems (UAS). The safe operation of UAS in the NAS must be assured if the full potential of UAS is to be realized and supported by the public and Congress. This report analyzed the communication systems that are needed for the safe operations of UAS in the NAS. Safe operations can be defined as the availability of the required links to carry the information to control the UAS and the return links to allow controllers to know where the UAS is at any given moment as well as how it is performing. This report is the end result of work performed jointly between the FAA and National Aeronautics and Space Administration (NASA)/Kennedy Space Center (NASA KSC). The work was done in support of the Radio Technical Commission for Aeronautics (RTCA) Special Committee 203 (SC-203) Control and Communications Working Group. The RTCA is a federal advisory committee to the FAA. Though the work was not under the direction of the working group, a large part of the specific values used in the simulations came from the working group. Specifically, all of the radio links were modeled based on the formulation completed by the working group. This report analyzed three scenarios from RTCA SC-203 that represent how a UAS would operate in the NAS. Each scenario was created using the Satellite Tool Kit (STK) modeling and simulation tool. The flight paths of the UAS were generated and the UAS dynamics were likewise modeled. Then each communication asset such as transmitters, receivers, and antennas were modeled and placed on the appropriate UAS, satellite, or Control Station (CS). After that, the radio links were analyzed for signal strength and antenna blockage, and the overall link performance was analyzed in detail. The goal was to obtain 99.9% availability on all of the radio communication links. In order to ensure the 99.9% availability, certain values for the telemetry transmitter will have to be increased slightly from I watt up to about 4 watts which is reasonable. The results of this analysis show that it is possible to send commands, during the airborne segment, to the Unmanned Aircraft (UA) and have the UA send back the system health and status with high availability of at least 99.9% of the time. This 99.9% availability included the condition of heavy rain at 90 mm/hr as well as interference from adjacent satellites. The link budget values used in this report were based on the work from the working group.

Birr, Richard B.↗

A Overview of New Technologies Driving Innovation in the Airborne Science Community

Following a more than a century of scientific aircraft and ballooning there is a sense that a renaissance of sorts is at hand in the aviation industry. The advent of incredibly miniaturized autopilots, inertial navigation systems, GPS antennae, and payloads has sparked a revolution in manned and unmanned aircraft. Improved SATCOM and onboard computing has enabled realtime data processing and improved transfer of data on and off the aircraft, making flight planning and data collection more efficient and effective. Electric propulsion systems are scaling up to larger and larger vehicles as evidenced by the NASA GL-10, which is leading to a new X-plane and is leading to renewed interest in personal air vehicles. There is also significant private and government investments in the development of High Altitude, Long Endurance (HALE) aircraft. This presentation will explore how such developments are likely to improve our ability to observe earth systems processes from aircraft by providing an overview of current NASA Airborne Science capabilities, followed by a brief discussion of new technologies being applied to Airborne Science missions, and then conclude with an overview of new capabilities on the horizon that are likely to be of interest to the Earth Science community.

airborne science↗

An Overview of New Technologies Driving Innovation in the Airborne Science Community

Following a more than a century of scientific aircraft and ballooning there is a sense that a renaissance of sorts is at hand in the aviation industry. The advent of incredibly miniaturized autopilots, inertial navigation systems, GPS antennae, and payloads has sparked a revolution in manned and unmanned aircraft. Improved SATCOM and onboard computing has enabled realtime data processing and improved transfer of data on and off the aircraft, making flight planning and data collection more efficient and effective. Electric propulsion systems are scaling up to larger and larger vehicles as evidenced by the NASA GL-10, which is leading to a new X-plane and is leading to renewed interest in personal air vehicles. There is also significant private and government investments in the development of High Altitude, Long Endurance (HALE) aircraft. This presentation will explore how such developments are likely to improve our ability to observe earth systems processes from aircraft by providing an overview of current NASA Airborne Science capabilities, followed by a brief discussion of new technologies being applied to Airborne Science missions, and then conclude with an overview of new capabilities on the horizon that are likely to be of interest to the Earth Science community.

airborne science↗

Characteristics of a Well Clear Definition and Alerting Criteria for Encounters Between UAS and Manned Aircraft in Class E Airspace

Unmanned aircraft systems (UAS) will be required to equip with a detect-and-avoid (DAA) system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. For a DAA system to satisfy the requirement to stay well clear of other airborne traffic, a quantitative definition of well clear needs to be defined and evaluated. This study investigates the implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the National Airspace System (NAS). The first analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The second analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results presented in this study inform the safety case, requirements development, and the operational environment for DAA minimum operational performance standards.

Safety↗

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, aviation incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts entities relevant to safety analysts. The custom NER model is built by fine-tuning an existing Bidirectional Encoder Representations from Transformers (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from failure-relevant text. This model performs passably, with a weighted average f1 score of 0.33 across entity types, indicating more labeled training data is needed. Extracted entities are used to form a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported using the SAFECOM system. Similar mishaps are manually clustered and reported as single rows within an FMEA. Foreach cluster, we compute frequency, severity, and overall riskin accordance with FAA standards. This methodology can beapplied as part of a broader safety management system totrack trends in mishaps (e.g., likelihood, severity) and discoverknowledge (e.g., causes, effects) that can be utilized to improvesafety outcomes and system performance.

Machine Learning↗