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NASA NTRSDate not supplied

Initial Integration of a Conflict Probabilities Service for Upper Class E Traffic Management

This paper outlines the development and integration of a conflict probability calculation-based service designed for Upper Class E Airspace operations. A key aspect of this effort is the integration of the conflict probability calculation algorithm into a simulated situational awareness client application. This application serves as a tool for flight operators to submit operations for Upper Class E Airspace within a simulated environment. The focus is on validating the effectiveness of the service through simulated intentional conflicting scenarios. The paper delves into the practicalities of integrating the conflict probability service into the user interface of the simulated situational awareness client application. This integration aims to enhance the decision-making capabilities of ETM operators within the simulated environment. The experiments and observations conducted in this simulated facility provide insights into the operational effectiveness of the proposed approach. In conclusion, this paper emphasizes the development, integration, and simulation-based validation of a conflict probability calculation service for Upper Class E Airspace. The findings underscore the potential impact of our approach on decision-making within a simulated setting, contributing to the understanding of its practical applications in operational scenarios.

Upper Class E Traffic Management↗
NASA NTRS2009

UAS Related Activities at NASA's Dryden Flight Research Center

NASA's Dryden Flight Research Center is completing its refurbishment and initial flights of one the pre-production Global Hawk aircraft it received from the U.S. Air Force. NASA Dryden has an agreement with the Global Hawk s manufacturer, Northrop Grumman, to partner in the refurbishment and flight operations of the vehicles. The National Oceanic and Atmospheric Administration (NOAA) has also partnered on the project and is assisting NASA with project management and pilot responsibilities for the aircraft. NASA and NOAA will be using the Global Hawks to conduct earth science research. The earth science community is increasing utilizing UAS of all sizes and capabilities to collect important data on a variety of issues including important global climate change issues. To pursue the data collection needs of the science community there is a growing demand for international collaboration with respect to operating UAS in global airspace. Operations of NASA s Ikhana aircraft continued this past year. The Ikhana is a modified Predator B UAS. A UAS dedicated to research at NASA Dryden is the X-48B blended wing body research aircraft. Flight tests with the 500- pound, remotely piloted test vehicle are now in a block 4 phase involving parameter identification and maneuvers to research the limits of the engine in stall situations. NASA s participation in the blended wing body research effort is focused on fundamental, advanced flight dynamics and structural design concepts within the Subsonic Fixed Wing project, part of the Fundamental Aeronautics program managed through NASA s Aeronautics Research Mission Directorate. Potential benefits of the aircraft include increased volume for carrying capacity, efficient aerodynamics for reduced fuel burn and possibly significant reductions in noise due to propulsion integration options. NASA Dryden continues to support the UAS industry by facilitating access to three specially designated test areas on Edwards Air Force Base for the development of small UAS.

Bauer, Jeffrey E.↗
NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or create more accurate transcripts of air traffic management conversations. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement (LOA) which is used as the evaluation case in this paper. These applications can benefit from the use of state-of-the-art Natural Language Processing (NLP) techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of transferring pre-trained large language models to the aviation domain by adapting transformer based models using aviation datasets. This paper utilized two datasets to adapt a ‘Robustly Optimized Bidirectional Encoder Representations from Transformers Approach’ (RoBERTa) model and two down-stream classification tasks to assess its performance. These datasets are all built upon Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. The first two datasets are used for the adaptation of RoBERTa to the aviation domain and were of different sizes to assess the number of documents needed to adapt to the aviation domain. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the unsupervised adaptation. The second dataset is a separate set of LOA documents with two sets of classification labels to be used for evaluation; one at the document level and one at the line level. These down-stream evaluations allowed the measurement of improvement by adapting RoBERTa. The accuracy increased by 4-6% on both tasks and the F1 score on the class of interest increased by 4-8% from the adaptation.

Air Traffic Management↗
NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or create more accurate transcripts of air traffic management conversations. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement (LOA) which is used as the evaluation case in this paper. These applications can benefit from the use of state-of-the-art Natural Language Processing (NLP) techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of transferring pre-trained large language models to the aviation domain by adapting transformer based models using aviation datasets. This paper utilized two datasets to adapt a ‘Robustly Optimized Bidirectional Encoder Representations from Transformers Approach’ (RoBERTa) model and two down-stream classification tasks to assess its performance. These datasets are all built upon Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. The first two datasets are used for the adaptation of RoBERTa to the aviation domain and were of different sizes to assess the number of documents needed to adapt to the aviation domain. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the unsupervised adaptation. The second dataset is a separate set of LOA documents with two sets of classification labels to be used for evaluation; one at the document level and one at the line level. These down-stream evaluations allowed the measurement of improvement by adapting RoBERTa. The accuracy increased by 4-6% on both tasks and the F1 score on the class of interest increased by 4-8% from the adaptation.

Air Traffic Management↗
NASA NTRS2024

Distributed Sensor Fusion of Ground and Air Nodes Using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds

High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. This work collected data using a distributed radar and camera sensor framework during the NASA Advanced Air Mobility High Density Vertiplex project SUAS flight operation. Node locations include on an onboard SUAS, affixed to the Landing and Impact Research Facility with approximate 200ft elevation, on a tripod on first-floor roof with an approximate elevation of 20 ft, and on a tripod on a concrete pad that is approximately 4 ft above sea level. Each node includes camera, radar, and GPS.

Beyond Visual Line of Sight↗
NASA NTRS2022

UAM Research – X4: Introduction to Community Based Rules (CBRs)

Recent advances in technology have enabled industry development of new and innovative vehicle types, offering lower operating costs and highly automated functionality that facilitates the introduction of new types of operations. These include low-altitude airspace operations with small Unmanned Aircraft Systems (UASs), short distance urban and intercity operations, and high- altitude Upper Class E operations. These and other new operations are expected to result in a much higher operational tempo than is currently experienced across the National Airspace System (NAS). The projected increase in operations, as well as the introduction of new aircraft form factors and supporting technologies—including increasing autonomy—will present challenges to the existing Air Traffic Management (ATM) system, which is currently unable to cost-effectively scale and deliver needed services. In response to these challenges and opportunities, a highly automated, cooperative environment incorporating a federated network has been envisioned and described through multiple operational concepts, depicting the future operating environment as part of the NAS. Foundational to the success of this future operating environment is the establishment of common business rules and understandings across relevant stakeholders, referred to as Community Based Rules (CBRs). Development, adoption, and implementation of CBRs will require collaboration across multiple stakeholders, including operators, support services (industry), and the Federal Aviation Administration (FAA), to identify and resolve a broad range of questions and challenges. Examples of these questions include “what rules are needed?”, “how are they expressed?”, and “how will they be managed?” This document identifies and describes an initial set of questions and considerations to be examined as efforts begin to create the innovative, automated, cooperative operating environment of the future. The goal is to establish a common frame of reference to support discussions and decisions regarding the future implementation of CBRs as part of the NAS.

Community Based Rules↗
NASA NTRSDate not supplied

Decentralized and Asynchronous Planning for Cooperative Practices in High Altitude Digitally Enabled Operations

Cooperative practices will likely be foundational to future digitally enabled airspace operations characterized by decentralized and asynchronous decision-making. This paper explores the implementation of cooperative practices in high-altitude airspace. The digitally enabled operations framework, under exploratory investigation by NASA as a potential new operating mode, which is enabled and dependent on digital technologies and information sharing, may create new operational possibilities for a wide range of vehicle types and missions. An essential element of the operating mode framework under investigation, cooperative practices, could empower operators to manage critical functions such as deconfliction, equitable airspace usage, and demand-capacity balancing. The use of cooperative practices would involve asynchronous flight information sharing and decentralized conflict management by operators, representing a major change from traditional air traffic services that use synchronous surveillance information to support centralized decision-making by air traffic controllers. This paper details three key components for implementing cooperative practices for decentralized, digitally enabled operations: (a) intent modeling and sharing, (b) conflict detection, and (c) cooperative deconfliction.

cooperative operating practics↗
NASA NTRS2010

Integration of Advanced Concepts and Vehicles Into the Next Generation Air Transportation System: Introduction, Key Messages, and Vehicle Attributes - Volume 1

Raytheon, in partnership with NASA, is leading the way in ensuring that the future air transportation continues to be a key driver of economic growth and stability and that this system provides an environmentally friendly, safe, and effective means of moving people and goods. A Raytheon-led team of industry and academic experts, under NASA contract NNA08BA47C, looked at the potential issues and impact of introducing four new classes of advanced aircraft into the next generation air transportation system -- known as NextGen. The study will help determine where NASA should further invest in research to support the safe introduction of these new air vehicles. Small uncrewed or unmanned aerial systems (SUAS), super heavy transports (SHT) including hybrid wing body versions (HWB), very light jets (VLJ), and supersonic business jets (SSBJ) are the four classes of aircraft that we studied. Understanding each vehicle's business purpose and strategy is critical to assessing the feasibility of new aircraft operations and their impact on NextGen's architecture. The Raytheon team used scenarios created by aviation experts that depict vehicles in year 2025 operations along with scripts or use cases to understand the issues presented by these new types of vehicles. The information was then mapped into the Joint Planning and Development Office's (JPDO s) Enterprise Architecture to show how the vehicles will fit into NextGen's Concept of Operations. The team also identified significant changes to the JPDO's Integrated Work Plan (IWP) to optimize the NextGen vision for these vehicles. Using a proven enterprise architecture approach and the JPDO s Joint Planning Environment (JPE) web site helped make the leap from architecture to planning efficient, manageable and achievable. Very Light Jets flying into busy hub airports -- Supersonic Business Jets needing to climb and descend rapidly to achieve the necessary altitude Super-heavy cargo planes requiring the shortest common flight path -- are just a few of the potential new operations in the future National Airspace System. To assess the impact of these new scenarios on overall national airspace operations, the Raytheon team used the capabilities of a suite of tools such as NASA's Airspace Concepts Evaluation System (ACES), the Flight Optimization System (FLOPS), FAA's Aviation Environmental Design Tool (AEDT), Intelligent Automations Kinematic Trajectory Generator (KTG) and the Aviation Safety Risk Model (ASRM). Detailed metroplex modeling, surface delay models for super heavy transports, prioritized routing and corridors for supersonics business jets, and VLJ demand models are some of the models developed by the Raytheon team to study the effect of operating these new vehicles in the future NAS. Using this suite of models, several trade studies were conducted to evaluate these effects in terms of delays, equity in access, safety, and the environment. Looking at the impact of each vehicle, a number of critical issues were identified. The Raytheon team concluded that strict compliance to NextGen's 4-dimensional trajectory (4DT) management will be required to accommodate these vehicles unique operations and increased number of flights in the future air space system. The next section provides a discussion of this and the other key findings from our study.

Zellweger, Andres↗
NASA NTRS2021

Cooperative Upper Class E Airspace: Concept of Operations and Simulation Development for Operational Feasibility Assessment

Upper Class E Traffic Management (ETM) is a novel community-based traffic management concept incorporating the FAA, NASA, and industry’s collaborative efforts to support safe, efficient, and scalable future operations in the airspace near and above 60,000 ft. The concept complements Air Traffic Control (ATC) infrastructure and Air Traffic Management (ATM) services by facilitating cooperative operations with ETM provided services. This paper presents an initial Cooperative Separation Management (CSM) concept for High Altitude Long Endurance (HALE) vehicles’ conflict detection and resolution during their extended operations. A prototype simulation platform has been developed to visualize and assess the concept during demonstrations to stakeholders. Further development plans for simulations and the CSM concept are discussed.

upper Class E airspace↗
NASA NTRSDate not supplied

Cooperative Upper Class E Airspace: Concept of Operations and Simulation Development for Operational Feasibility Assessment

Upper Class E Traffic Management (ETM) is a novel community-based traffic management concept incorporating the FAA, NASA, and industry’s collaborative efforts to support safe, efficient, and scalable future operations in the airspace near and above 60,000 ft. The concept complements Air Traffic Control (ATC) infrastructure and Air Traffic Management (ATM) services by facilitating cooperative operations with ETM provided services. This paper presents an initial Cooperative Separation Management (CSM) concept for High Altitude Long Endurance (HALE) vehicles’ conflict detection and resolution during their extended operations. A prototype simulation platform has been developed to visualize and assess the concept during demonstrations to stakeholders. Further development plans for simulations and the CSM concept are discussed.

upper Class E airspace↗
NASA NTRS2016

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

ATD-3↗
NASA NTRS2018

Airspace Technology Demonstration 3 (ATD-3): Dynamic Routes for Arrivals in Weather (DRAW) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration – 3 (ATD-3) is part of NASA’s Airspace Operations and Safety Program (AOSP) – specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multi-year research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the third of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA’s Dynamic Routes for Arrivals in Weather (DRAW) –Arrival Metering Operations. This research enables continued use of arrival metering operations while efficiently rerouting traffic in weather

DRAW↗
NASA NTRS2019

Airspace Technology Demonstration 3 (ATD-3): Dynamic Routes for Arrivals in Weather (DRAW) Technology Transfer Document Summary Version 2.0

Airspace Technology Demonstration – 3 (ATD-3) is part of NASA’s Airspace Operations and Safety Program (AOSP) – specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multi-year research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the third Research Transition Product (RTP) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan, which is Dynamic Routes for Arrivals in Weather (DRAW). This technology transfer consists of artifacts for DRAW Arrival Metering (AM) Operations delivered in June 2018, DRAW AM updates, and DRAW Extended Metering (XM) Operations. Blue highlighting indicates the new or modified deliverables. Some of the artifacts in this technology transfer have distribution restrictions that need to be followed. Distribution information is noted in each section. DRAW is a trajectory-based system that combines the legacy Dynamic Weather Routes (DWR) weather avoidance technology with an arrival-specific rerouting algorithm and arrival scheduler to improve traffic flows on weather-impacted arrival routes into major airports. First, DRAW identifies flights that could be rerouted to more efficient Standard Terminal Arrival Routes (STARs) that may have previously been impacted by weather. Second, when weather is impacting the arrival routing, DRAW proposes simple arrival route corrections that enable aircraft to stay on their flight plan while avoiding weather. The DRAW system proposes reroutes early enough to allow Time Based Flow Management (TBFM) to make the necessary schedule adjustments. As a result, metering operations can be sustained longer and more consistently in the presence of weather because the arrival schedule accounts for the dynamic routing intent of arrival flights to deviate around weather. The first DRAW tech transfer in June 2018 focused on arrival metering operations with the DRAW algorithm implemented in the NASA Center TRACON Automation System (CTAS) automation software. This tech transfer delivery includes updates for DRAW implemented in FAA’s TBFM 4.7 automation software and preliminary research into DRAW for XM operations.

Isaacson, Douglas R.↗
NASA NTRS2018

Airspace Technology Demonstration 3 (ATD-3) Multi-Flight Common Route (MFCR) Technology Transfer Document Summary Version 2.0

Airspace Technology Demonstration - 3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multi-year research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en-route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the second of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. The original transfer, completed in December 2017, consisted of NASA's Multi-Flight Common Route (MFCR) research for efficient route corrections for en-route weather avoidance. This transfer updates the Concept of Operations document to a publicly-available NASA Technical Memorandum. The MFCR concept builds on the experience of the legacy Dynamic Weather Routes (DWR) and focuses on a better balance of potential savings with ATC acceptability, common route corrections options for multiple flights on similar routings, and better use of existing and/or modern automation for communication and coordination of route change options. All of these capabilities are expected to improve system performance significantly in terms of actual delay-reducing clearances issued to flights compared to that of the DWR tool and operating concept.

Tech transfer↗
NASA NTRSDate not supplied

A Concept of Operations for Power Beaming of Electric Air Vehicles

A concept of operations is presented for power beaming of microwaves to extend battery charge of an electric air vehicle. Critical aspects of airspace operations and power beam charging are addressed. Three classes of electric Vertical Take-Off and Landing vehicle models are considered for recharging. The effects of transmitter frequency, antenna size, and beam width are analyzed. Based on past experiments in the industry, a 2.5 kW power beam is selected. A no-drag rectifying antenna under the belly of the vehicle is selected along with the conversion efficiency, power density, and its size. The combined efficiency of the transmit/receive system as well as the beam containment values are addressed. These parameters are chosen to assess viability and feasibility of the energy augmentation method to establish safety for humans on-board from exposure to the transmitted energy. NASA will test the concept of operations in a laboratory experiment with parameters selected and presented here.

eVTOL vehicles↗
NASA NTRSDate not supplied

A Concept of Operations for Power Beaming of Electric Air Vehicles

A concept of operations is presented for power beaming of microwaves to extend battery charge of an electric air vehicle. Critical aspects of airspace operations and power beam charging are addressed. Three classes of electric Vertical Take-Off and Landing vehicle models are considered for recharging. The effects of transmitter frequency, antenna size, and beam width are analyzed. Based on past experiments in the industry, a 2.5 kW power beam is selected. A no-drag rectifying antenna under the belly of the vehicle is selected along with the conversion efficiency, power density, and its size. The combined efficiency of the transmit/receive system as well as the beam containment values are addressed. These parameters are chosen to assess viability and feasibility of the energy augmentation method to establish safety for humans on-board from exposure to the transmitted energy. NASA will test the concept of operations in a laboratory experiment with parameters selected and presented in this paper.

eVTOL vehicles↗
NASA NTRS2014

A Novel Application of TMA to Converging Runway Operations in a Simulated NextGen Environment

In 2013, the Airspace Operations Laboratory at NASA Ames Research Center conducted a human-in-the-loop simulation that examined the feasibility of applying a number of Next Generation Air Transportation System (NextGen) solutions to complex arrival operations in and around the New York metroplex. The delivery of arrivals to Newark Liberty International Airport (EWR) was the focus of this simulation, which involved extending the Terminal Sequencing and Spacing (TSS) scheduling capability to precisely schedule arrivals to intersecting runways 22 Left and 11. An important enabler for the concept was the availability of a dependent runway scheduler that was able to coordinate arrival times between aircraft landing on intersecting runways. At the time of the study, there was no functionality within the TSS scheduler to automatically create the dependent runway schedules. Instead, a Traffic Management Coordinator (TMC) manually created a de-conflicted schedule, which allowed for the concept to be tested as well as provided valuable insight into the tool requirements for a dependent runway scheduler. Throughout the course of preparations for the simulation, the individual serving as the TMC developed a number of strategies and procedures for manually adjusting the Scheduled Time of Arrival (STA) of the EWR arrivals in order to ensure that adequate spacing was provided between runway 22L and 11 arrival pairs. This paper describes the strategies and procedures that were developed and details how they were successfully applied during the simulation. Results will also be presented that shed additional light on exactly how the schedules were manipulated and their impact on delivery performance and safety. Ideas for additional TSS enhancements and next steps, based on participant feedback, will also be presented.

Homola, Jeffrey↗