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NASA NTRS2017

The NASA Air Traffic Management Ontology: Technical Documentation

This document is intended to serve as comprehensive documentation for the NASA Air Traffic Management (ATM) Ontology. The ATM Ontology is a conceptual model that defines key classes of entities and relationships pertaining to the US National Airspace System (NAS) and the management of air traffic through that system. A wide variety of classes are represented in the ATM Ontology, including classes corresponding to flights, aircraft, manufacturers, airports, airlines, air routes, NAS facilities, air traffic control advisories, weather phenomena, and many others. The Ontology can be useful in the context of a variety of information management tasks relevant to NAS, including information exchange, data query and search, information organization, information integration, and terminology standardization.

information management↗
NASA NTRSDate not supplied

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗
NASA NTRS2021

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗
NASA NTRS2023

Procedure Automation Rating Matrix

The National Aeronautics and Space Administration (NASA) Advanced Air Mobility (AAM) National Campaign (NC) is researching the means by which future Urban Air Mobility (UAM) aircraft will operate safely in an integrated and scalable airspace architecture. Consistent with this objective, the NASA NC Airspace Procedures team designed a matrix to evaluate UAM instrument flight procedure design, flyability and interoperability of candidate departure, enroute, and approach architectures in live flight or simulation. The Procedure Automation Rating Matrix (PARM) is a multi-dimensional rating scale designed to provide direct feedback from test pilots and operators to airspace procedure designers developing airspace constructs for the integration and scalability of AAM operations in the National Airspace System (NAS). The PARM is assessed using a hierarchical decision tree that guides the operator through a ten-point alpha-numeric rating scale initiated either with or without the use of automation.

National Campaign↗
NASA NTRSDate not supplied

Remote Pilot Handoffs in Large UAS Multi-Vehicle Operations: Best Practices and Supportive Technologies

In response to pilot shortages and increasing air cargo demands, NASA's Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project conducted the fourth in a series of tabletop studies investigating scalable solutions for integrating large Uncrewed Aircraft Systems (UAS) into the National Airspace System (NAS). This study solicited subject matter expertise to identify solutions to potential challenges for a further term vision, guiding participants through scenario-based discussions where the remote pilot (RP)-to-vehicle ratio has been scaled from 1:1 to m:N. Of those challenges, remote pilot handoffs were found throughout all phases of flight, both in nominal and non-nominal scenarios. The current paper details participant-suggested procedural and technological solutions for overcoming the handoff challenge, including determining the accepting RP, which aircraft to release, the location and timing of the transition, and options for supporting personnel, tools, and automation that could facilitate safe and efficient handoffs.

unmanned aircraft systems (UAS)↗
NASA NTRSDate not supplied

Remote Pilot Handoffs in Large UAS Multi-Vehicle Operations: Best Practices and Supportive Technologies

In response to pilot shortages and increasing air cargo demands, NASA's Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project conducted the fourth in a series of tabletop studies investigating scalable solutions for integrating large Uncrewed Aircraft Systems (UAS) into the National Airspace System (NAS). This study solicited subject matter expertise to identify solutions to potential challenges for a further term vision, guiding participants through scenario-based discussions where the remote pilot (RP)-to-vehicle ratio has been scaled from 1:1 to m:N. Of those challenges, remote pilot handoffs were found throughout all phases of flight, both in nominal and non-nominal scenarios. The current paper details participant-suggested procedural and technological solutions for overcoming the handoff challenge, including determining the accepting RP, which aircraft to release, the location and timing of the transition, and options for supporting personnel, tools, and automation that could facilitate safe and efficient handoffs.

uncrewed aircraft systems↗
NASA NTRS2008

A Common Communications, Navigation and Surveillance Infrastructure for Accommodating Space Vehicles in the Next Generation Air Transportation System

Suborbital space flight and space tourism are new potential markets that could significantly impact the National Airspace System (NAS). Numerous private companies are developing space flight capabilities to capture a piece of an emerging commercial space transportation market. These entrepreneurs share a common vision that sees commercial space flight as a profitable venture. Additionally, U.S. space exploration policy and national defense will impose significant additional demands on the NAS. Air traffic service providers must allow all users fair access to limited airspace, while ensuring that the highest levels of safety, security, and efficiency are maintained. The FAA's Next Generation Air Transportation System (NextGen) will need to accommodate spacecraft transitioning to and from space through the NAS. To accomplish this, space and air traffic operations will need to be seamlessly integrated under some common communications, navigation and surveillance (CNS) infrastructure. As part of NextGen, the FAA has been developing the Automatic Dependent Surveillance Broadcast (ADS-B) which utilizes the Global Positioning System (GPS) to track and separate aircraft. Another key component of NextGen, System-Wide Information Management/ Network Enabled Operations (SWIM/NEO), is an open architecture network that will provide NAS data to various customers, system tools and applications. NASA and DoD are currently developing a space-based range (SBR) concept that also utilizes GPS, communications satellites and other CNS assets. The future SBR will have very similar utility for space operations as ADS-B and SWIM has for air traffic. Perhaps the FAA, NASA, and DoD should consider developing a common space-based CNS infrastructure to support both aviation and space transportation operations. This paper suggests specific areas of research for developing a CNS infrastructure that can accommodate spacecraft and other new types of vehicles as an integrated part of NextGen.

VanSuetendael, RIchard↗
NASA NTRS2014

UAS-Systems Integration, Validation, and Diagnostics Simulation Capability

As part of the Phase 1 efforts of NASA's UAS-in-the-NAS Project a task was initiated to explore the merits of developing a system simulation capability for UAS to address airworthiness certification requirements. The core of the capability would be a software representation of an unmanned vehicle, including all of the relevant avionics and flight control system components. The specific system elements could be replaced with hardware representations to provide Hardware-in-the-Loop (HWITL) test and evaluation capability. The UAS Systems Integration and Validation Laboratory (UAS-SIVL) was created to provide a UAS-systems integration, validation, and diagnostics hardware-in-the-loop simulation capability. This paper discusses how SIVL provides a robust and flexible simulation framework that permits the study of failure modes, effects, propagation paths, criticality, and mitigation strategies to help develop safety, reliability, and design data that can assist with the development of certification standards, means of compliance, and design best practices for civil UAS.

Buttrill, Catherine W.↗
NASA NTRS2021

Bell Unmanned Aircraft Systems Integration and Operationalization (SIO) Demonstration: Final Report, Summary of Research

National Aeronautics and Space Administration (NASA) initiated the Unmanned Aircraft Systems Integration and Operationalization (SIO) demonstration as a partnership between NASA and Industry with the goal of accelerating routine unmanned aircraft systems (UAS) operations in the national airspace (NAS). In order to accomplish this goal, NASA partnered separately with Bell and two other industry teams each pioneering the development, integration, and testing of their UAS, with the intent to make progress towards type certification. The program culminated in flight demonstrations representing future commercial operations by each partner.

Flight Demonstration↗
NASA NTRSDate not supplied

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗
NASA NTRSDate not supplied

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.

L. Prinzel↗
NASA NTRSDate not supplied

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.

Aviation Safety↗
NASA NTRS1992

NAS technical summaries: Numerical aerodynamic simulation program, March 1991 - February 1992

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefiting other supercomputer centers in Government and industry. This report contains selected scientific results from the 1991-92 NAS Operational Year, March 4, 1991 to March 3, 1992, which is the fifth year of operation. During this year, the scientific community was given access to a Cray-2 and a Cray Y-MP. The Cray-2, the first generation supercomputer, has four processors, 256 megawords of central memory, and a total sustained speed of 250 million floating point operations per second. The Cray Y-MP, the second generation supercomputer, has eight processors and a total sustained speed of one billion floating point operations per second. Additional memory was installed this year, doubling capacity from 128 to 256 megawords of solid-state storage-device memory. Because of its higher performance, the Cray Y-MP delivered approximately 77 percent of the total number of supercomputer hours used during this year.

Source record↗
NASA NTRS2013

NASA GRC UAS Project: Communications Modeling and Simulation Status

The integration of Unmanned Aircraft Systems (UAS) in the National Airspace represents new operational concepts required in civil aviation. These new concepts are evolving as the nation moves toward the Next Generation Air Transportation System (NextGen) under the leadership of the Joint Planning and Development Office (JPDO), and through ongoing work by the Federal Aviation Administration (FAA). The desire and ability to fly UAS in the National Air Space (NAS) in the near term has increased dramatically, and this multi-agency effort to develop and implement a national plan to successfully address the challenges of UAS access to the NAS in a safe and timely manner is well underway. As part of the effort to integrate UAS in the National Airspace, NASA Glenn Research Center is currently involved with providing research into Communications systems and Communication system operations in order to assist with developing requirements for this implementation. In order to provide data and information regarding communication systems performance that will be necessary, NASA GRC is tasked with developing and executing plans for simulations of candidate future UAS command and control communications, in line with architectures and communications technologies being developed and/or proposed by NASA and relevant aviation organizations (in particular, RTCA SC-203). The simulations and related analyses will provide insight into the ability of proposed communications technologies and system architectures to enable safe operation of UAS, meeting UAS in the NAS project goals (including performance requirements, scalability, and interoperability), and ultimately leading to a determination of the ability of NextGen communication systems to accommodate UAS. This presentation, compiled by the NASA GRC team, will provide a view of the overall planned simulation effort and objectives, a description of the simulation concept and status of the design and development that has occurred to date.

Kubat, Greg↗
NASA NTRS2014

NASA GRC UAS Project - Communications Modeling and Simulation Development Status

The integration of Unmanned Aircraft Systems (UAS) in the National Airspace represents new operational concepts required in civil aviation. These new concepts are evolving as the nation moves toward the Next Generation Air Transportation System (NextGen) under the leadership of the Joint Planning and Development Office (JPDO), and through ongoing work by the Federal Aviation Administration (FAA). The desire and ability to fly UAS in the National Air Space (NAS) in the near term has increased dramatically, and this multi-agency effort to develop and implement a national plan to successfully address the challenges of UAS access to the NAS in a safe and timely manner is well underway. As part of the effort to integrate UAS in the National Airspace, NASA Glenn Research Center is currently involved with providing research into Communications systems and Communication system operations in order to assist with developing requirements for this implementation. In order to provide data and information regarding communication systems performance that will be necessary, NASA GRC is tasked with developing and executing plans for simulations of candidate future UAS command and control communications, in line with architectures and communications technologies being developed and or proposed by NASA and relevant aviation organizations (in particular, RTCA SC-203). The simulations and related analyses will provide insight into the ability of proposed communications technologies and system architectures to enable safe operation of UAS, meeting UAS in the NAS project goals (including performance requirements, scalability, and interoperability), and ultimately leading to a determination of the ability of NextGen communication systems to accommodate UAS. This presentation, compiled by the NASA GRC Modeling and Simulation team, will provide an update to this ongoing effort at NASA GRC as follow-up to the overview of the planned simulation effort presented at ICNS in 2013. The objective of presentation will be to describe the progress made in developing both a NAS-Wide simulation architecture application and the detailed radiocomm system models for this research, and will present interim data and information compiled in the process of developing these simulation capabilities to date.

Modeling and Simulation↗
NASA NTRS2021

GA-ASI Final Report and Program Wrap-up for NASA System Integration and Operationalization (SIO)

The NASA SIO demonstration flight of April 3, 2020 represents a successful culmination of 18 months of coordinated effort between GA-ASI, NASA, the FAA, Collins Aerospace, and Honeywell Aerospace to operate a Medium Altitude, Long Endurance (MALE) Unmanned Aircraft System (UAS) safely in the National Airspace System (NAS) using industry leading prototype technologies. The GA-ASI team consisted of technical experts, program managers, engineers, mechanics, flight technicians, flight crews, and numerous other subject matter experts. This final report describes the most significant and potentially impactful aspects of the planning, integration, test, and flight aspects of this effort. GA-ASI successfully integrated the key technologies needed for UAS to fly in the NAS onto our prototype SkyGuardian UAS, which was designed to meet the most stringent airworthiness standards applicable to an aircraft of its size category. A proven Detect and Avoid (DAA) system, developed by GA-ASI and utilizing Honeywell Aerospace technology was integrated onto SkyGuardian for the first time, along with datalink radios from Collins Aerospace that meet the new civil standard for Control and Non-Payload Communication (CNPC) links. GA-ASI also obtained approvals from the FAA and FCC to operate the reconfigured UAS. The SIO demonstration flight represented a commercial aerial surveying operation conducted at medium altitude (>10,000ft above mean sea level). The aircraft’s onboard sensors were used to capture photographic, infrared and radar imagery of public and commercial infrastructure and land, and to subsequently produce the types of data products that would provide business value to potential customers. These survey services would supplement or replace services currently provided by manned airplanes and helicopters, small drones or satellites. A “virtual” mission was also planned, to show what additional survey data could have been captured during the flight if additional sensors had been installed on the aircraft’s external hardpoints. This revision of the final report focuses on information of value to the wider UAS community, and avoids propriety data to facilitate broad dissemination. It also includes a description of GA-ASI’s engagement with the FAA following the SIO flight, which led to the award of an updated Special Airworthiness Certificate in the Experimental Category (SAC-EC) and a Certificate of Waiver or Authorization (COA) allowing operation of the SkyGuardian UAS using its DAA system to satisfy right-of-way rules, instead of a chase plane. The associated operational limitations are described to illustrate the further steps that would be needed to remove those limitations for unhindered commercial operations.

Flight demonstration↗
NASA NTRS2000

FACET: Future ATM Concepts Evaluation Tool

FACET (Future ATM Concepts Evaluation Tool) is an Air Traffic Management research tool being developed at the NASA Ames Research Center. This paper describes the design, architecture and functionalities of FACET. The purpose of FACET is to provide E simulation environment for exploration, development and evaluation of advanced ATM concepts. Examples of these concepts include new ATM paradigms such as Distributed Air-Ground Traffic Management, airspace redesign and new Decision Support Tools (DSTs) for controllers working within the operational procedures of the existing air traffic control system. FACET is currently capable of modeling system-wide en route airspace operations over the contiguous United States. Airspace models (e.g., Center/sector boundaries, airways, locations of navigation aids and airports) are available from databases. A core capability of FACET is the modeling of aircraft trajectories. Using round-earth kinematic equations, aircraft can be flown along flight plan routes or great circle routes as they climb, cruise and descend according to their individual aircraft-type performance models. Performance parameters (e.g., climb/descent rates and speeds, cruise speeds) are obtained from data table lookups. Heading, airspeed and altitude-rate dynamics are also modeled. Additional functionalities will be added as necessary for specific applications. FACET software is written in Java and C programming languages. It is platform-independent, and can be run on a variety of computers. FACET has been designed with a modular software architecture to enable rapid integration of research prototype implementations of new ATM concepts. There are several advanced ATM concepts that are currently being implemented in FACET airborne separation assurance, dynamic density predictions, airspace redesign (re-sectorization), benefits of a controller DST for direct-routing, and the integration of commercial space transportation system operations into the U.S. National Airspace System (NAS).

Bilmoria, Karl D.↗