Search NASA⌕ Search

SEARCH · Search NASA

Results for “airspace technology demonstration”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Terminal Area Icing Remote Sensing System

NASA and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology is now being extended to provide volumetric coverage surrounding an airport. With volumetric airport terminal area coverage, the resulting icing hazard information will be usable by aircrews, traffic control, and airline dispatch to make strategic and tactical decisions regarding routing when conditions are conducive to airframe icing. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize cloud radar, microwave radiometry, and NEXRAD radar. This terminal area icing remote sensing system will use the data streams from these instruments to provide icing hazard classification along the defined approach paths into an airport. Strategies for comparison to in-situ instruments on aircraft and weather balloons for a planned NASA field test are discussed, as are possible future applications into the NextGen airspace system.

aircraft icing↗
NASA NTRS2018

Autonomous Inspection of Electrical Transmission Structures with Airborne UV Sensors and Automated Air Traffic Management

This report details test and measurement flights to demonstrate autonomous UAV (Unmanned Aerial Vehicle) inspection of high-voltage electrical transmission structures. A UAV built with commercial, off-the-shelf hardware and software, supplemented with custom sensors and logging software, measured ultraviolet (UV) emissions from a test generator placed on a low-altitude substation and a medium-altitude switching tower. Since corona discharge precedes catastrophic electrical faults on high-voltage structures, detection and geolocation of ultraviolet emissions is needed to develop a UAV-based self-diagnosing power grid. Signal readings from an onboard ultraviolet sensor were validated during flight with a commercial corona camera. Geolocation was accomplished with onboard GPS; the UAV position was logged to a local ground station and transmitted in real time to a NASA server for tracking in the national airspace. The method has practicality and relevance but not adequacy; either improved UAV position determination technology or increased sensor range is needed to enable broad deployment of this method.

Moore, Andrew J.↗
NASA NTRS2018

Giving the Public a Perspective into Unmanned Aircraft Systems' Operations

NASA is currently engaged in research to safely enable large-scale commercial applications of small Unmanned Aerial Systems (UAS) in low altitude airspace. This research effort, referred to as UAS Traffic Management (UTM), encompasses the concepts and technologies needed to accommodate the projected demand of UAS operating in the national airspace. One aspect related to the successful implementation of UTM in the future is public acceptance. Transparency will heavily influence this acceptance, and a public portal will provide much of that transparency through ease of access to information about the operations - mainly who, why, and where such operations are taking place. Related concerns to the public are individual privacy, security, and accountability of the operators. Providing the aforementioned information about operations can mitigate these concerns, but a balance will have to be achieved between the need for transparency from the public and the privacy of the operators. The proper balance and the needs of the various UTM stakeholders with regard to information access will be explored through the development and testing of a public portal as part of NASA's Technical Capability 3 (TCL 3) demonstration. Additionally, various approaches to the display of information and user interfaces will be surveyed through the development of a public portal by multiple UTM industry partners across different test sites.

UAS↗
NASA NTRSDate not supplied

A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM)

The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.

In-Time Aviation Safety Management System↗
NASA NTRS2014

Control and Non-Payload Communications Generation 1 Prototype Radio Flight Test Report

Unmanned aircraft (UA) represent a new capability that will provide a variety of services in the Government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized because of the lack of a common understanding of what is required to safely operate Unmanned Aircraft Systems in the National Airspace System (UAS in the NAS). The desire and ability to fly UA is of increasing urgency. The application of UA to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UA to the NAS. Existing Federal Aviation Regulations, procedures, and technologies do not allow routine UA access to the NAS. Access to the NAS is hampered by challenges such as the lack of an onboard pilot to see and avoid other aircraft; the ability of a single pilot or operator to control multiple UA; the reliance on command and control (C2) links; the altitudes, speeds, and duration at which the aircraft fly; and the wide variation in UA size and performance. NASA is working with other Government agencies to provide solutions that reduce technical barriers and make access to the NAS routine. This goal will be accomplished through system-level integration of key concepts, technologies, or procedures and through demonstrations of these integrated capabilities in an operationally relevant environment. This project provides an opportunity to transition the acquired empirical data and knowledge to the Federal Aviation Administration and other stakeholders to help them define the requirements for routine UA access to the NAS.Radio communications channels for UA are currently managed through exceptions and use either Department of Defense frequencies for line-of-sight (LOS) and satellite-based communications links, low-power LOS links in amateur bands, or unlicensed Industrial/Scientific/Medical (ISM) frequencies. None of these frequency bands are designated for safety and regularity of flight. Only recently has radiofrequency (RF) spectrum been allocated by the International Telecommunications Union specifically for commercial UA C2, LOS communication (L-Band: 960 to 1164 MHz, and C-Band: 5030 to 5091 MHz). The safe and efficient integration of UA into the NAS requires the use of protected RF spectrum allocations and a new data communications system that is both secure and scalable to accommodate the potential growth of these new aircraft. Data communications for UA-referred to as control and non-payload communications (CNPC)-will be used to exchange information between a UA and a ground station (GS) to ensure safe, reliable, and effective UA flight operation. The focus of this effort is on validating and allocating new RF spectrum and data link communications to enable civil UA integration into the NAS. Through a cost-sharing cooperative agreement with Rockwell Collins, Inc., the NASA Glenn Research Center is exploring and performing the necessary development steps to realize a prototype UA CNPC system. These activities include investigating signal waveforms and access techniques, developing representative CNPC radio hardware, and executing relevant testing and validation activities. There is no intent to manufacture the CNPC end product, rather the goals are to study, demonstrate, and validate a typical CNPC system that will allow safe and efficient communications within the L-Band and C-Band spectrum allocations. The system is addressing initial "seed" requirements from RTCA, Inc., Special Committee 203 (SC-203) and is on a path to Federal Aviation Administration certification. This report provides results from the flight testing campaign of the Rockwell Collins Generation 1 prototype radio, referred hereafter as the "radio." The radio sets operate within the 960- to 977-MHz frequency band with both air and ground radios using identical hardware. Flight tests involved one aircraft and one GS. Results include discussion of aircraft flight paths and associated radio performance.

Shalkhauser, Kurt A.↗
NASA NTRS1995

Aeronautical Satellite Data Link System (SDLS) for high-density air-traffic areas

The European Space Agency has recently commissioned a study to investigate the feasibility of a low-cost aeronautical Satellite Data Link System (SDLS) to provide for the needs of Air Traffic Services, i.e. safety related communications over continental areas with high air-traffic density. This study is placed in today's context which sees the first generation of Aeronautical Mobile Satellite System (AMSS) being gradually but restrictively put into service in oceanic airspaces with low air-traffic density. This paper first discusses the case of ATS dedicated versus mixed (ATS and commercial) Comms service provision and identifies the specific ATS comms requirements context. Specific emphasis is put on the ICAO (International Civil Aviation Organization) standardization framework for both the ATN (Aeronautical Telecommunication Network) and the SSR (Secondary Surveillance Radar) Mode S specific services. An architectural system and network design for a future SDLS is then proposed, such as to meet the ATS comms requirements within the realm of existing technologies. To minimize development risk and cost, consideration is given to re-use the ESA-developed Land Mobile Communication Technology, known as MSBN (Mobile Satellite Business Network) featuring distinct subnetworks. It is particularly suited to an ATM (Air Traffic Management) decentralized architecture made of independent ATC (Air Traffic Control) Centers. Finally the study follow-on phase is introduced, which is intended to cover system design and development leading to a demonstration program, as a first step towards proposals for international standardization and acceptance.

Alain Delrieu↗
NASA NTRS2009

Progress on the Development of Future Airport Surface Wireless Communications Network

Continuing advances in airport surface management and improvements in airport surface safety are required to enable future growth in air traffic throughout the airspace, as airport arrival and departure delays create a major system bottleneck. These airport management and safety advances will be built upon improved communications, navigation, surveillance, and weather sensing, creating an information environment supporting system automation. The efficient movement of the digital data generated from these systems requires an underlying communications network infrastructure to connect data sources with the intended users with the required quality of service. Current airport surface communications consists primarily of buried copper or fiber cable. Safety related communications with mobile airport surface assets occurs over 25 kHz VHF voice and data channels. The available VHF spectrum, already congested in many areas, will be insufficient to support future data traffic requirements. Therefore, a broadband wireless airport surface communications network is considered a requirement for the future airport component of the air transportation system. Progress has been made on defining the technology and frequency spectrum for the airport surface wireless communications network. The development of a test and demonstration facility and the definition of required testing and standards development are now underway. This paper will review the progress and planned future work.

Kerczewski, Robert J.↗
NASA NTRS2016

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Davila, Carlos G.↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and F1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

LSTM↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and 𝐹1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

ATC↗
DOE OSTI2026

Preparing For Advanced Air Mobility: A System-Level Framework For Infrastructure, Investment, and Deployment

Advanced air mobility (AAM) is moving from demonstration toward early deployment, supported by a growing national strategy that outlines how these systems may evolve across airspace, infrastructure, and operations. As this transition takes shape, a more practical question comes into focus: what does it mean to be ready? This paper introduces a Capability Maturity Model (CMM) as a structured way to think about that challenge. Rather than treating readiness as a fixed condition, it frames it as a progression - one that develops across multiple, interdependent domains over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2018

Unmanned Aircraft Systems (UAS) Traffic Management (UTM) National Campaign II

The Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA aims to enable access to low-altitude airspace for small UAS. This goal is being pursued partly through partnerships that NASA has developed with the UAS stakeholder community, the FAA, other government agencies, and the designated FAA UAS Test Sites. By partnering with the FAA UAS Test Sites, NASA's UTM project has performed a geographically diverse, simultaneous set of UAS operations at locations in six states. The demonstrations used an architecture that was developed by NASA in partnership with the FAA to safely coordinate such operations. These demonstrations—the second or "Technical Capability Level (TCL 2)" National Campaign of UTM testing—was performed from May 15 through June 9, 2017. Multiple UAS operations occurred during the testing at sites located in Alaska, Nevada, Texas, North Dakota, Virginia, and New York with multiple organizations serving as UAS Service Suppliers and/or UAS Operators per the specifications provided by NASA. By engaging various members of the UAS community in development and operational roles, this campaign provided initial validation of different aspects of the UTM concept including: UAS Service Supplier technologies and procedures; geofencing technologies/conformance monitoring; ground-based surveillance/sense and avoid; airborne sense and avoid; communication, navigation, surveillance; and human factors related to UTM data creation and display. Additionally, measures of performance were defined and calculated from the flight data to establish quantitative bases for comparing flight test activities and to provide potential metrics that might be routinely monitored in future operational UTM systems.

Aweiss, Arwa↗
NASA NTRS2019

Propulsion System Optimization for a Turboelectric Tiltwing Urban Air Mobility Aircraft

An emerging potential market within the aviation industry is short, frequent air taxi flights within the urban airspace. These air taxis (also called urban air mobility or UAM vehicles) are envisioned to be vertical take-o and landing designs which are capable of carrying 1 to 15 passengers in an intra-urban environment with less than 50 nautical miles of range. Numerous vehicle conceptual designs have been proposed by various industry and government organizations to fulfill these potential missions. These concepts are enabled by recent advancements in a number of areas including propulsion and power systems. While new technologies are making these vehicles possible, this new UAM design space is large, unexplored, and multidisciplinary in nature. New challenges exist in identifying and creating optimized designs for these unique vehicles with new propulsion technologies. This work presents the development of a suite of propulsion system analysis tools, which when coupled together, can improve the multidisciplinary conceptual design and optimization of UAM vehicle propulsion systems. These analysis tools are then applied to the design optimization of a turboelectric propulsion system for a notional UAM tiltwing concept. The optimization demonstration for this vehicle shows how a tightly-coupled multidisciplinary design can be developed which considers both physical design characteristics and operating schedules. Furthermore, the results explore trade-o s in the thermal management system design and how those trade-o s impact the overall vehicle.

Hendricks, Eric S.↗
NASA NTRS2018

Unmanned Aircraft Systems (UAS) Traffic Management (UTM) National Campaign II

The Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA aims to enable access to low-altitude airspace for small UAS. This goal is being pursued partly through partnerships that NASA has developed with the UAS stakeholder community, the FAA, other government agencies, and the designated FAA UAS Test Sites. By partnering with the FAA UAS Test Sites, NASA's UTM project has performed a geographically diverse, simultaneous set of UAS operations at locations in six states. The demonstrations used an architecture that was developed by NASA in partnership with the FAA to safely coordinate such operations. These demonstrations-the second or 'Technical Capability Level (TCL 2)' National Campaign of UTM testing-was performed from May 15 through June 9, 2017. Multiple UAS operations occurred during the testing at sites located in Alaska, Nevada, Texas, North Dakota, Virginia, and New York with multiple organizations serving as UAS Service Suppliers and/or UAS Operators per the specifications provided by NASA. By engaging various members of the UAS community in development and operational roles, this campaign provided initial validation of different aspects of the UTM concept including: UAS Service Supplier technologies and procedures; geofencing technologies/conformance monitoring; ground-based surveillance/sense and avoid; airborne sense and avoid; communication, navigation, surveillance; and human factors related to UTM data creation and display. Additionally, measures of performance were defined and calculated from the flight data to establish quantitative bases for comparing flight test activities and to provide potential metrics that might be routinely monitored in future operational UTM systems.

Aweiss, Arwa S.↗
NASA NTRSDate not supplied

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This paper introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗
NASA NTRSDate not supplied

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This presentation introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗
NASA NTRS2019

Flight Demonstration of Unmanned Aircraft System (UAS) Traffic Management (UTM) at Technical Capability Level 3

The goal of the Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA is to enable access to low-altitude airspace for small UAS. This goal is being achieved partly through partnerships that NASA has developed with the FAA, other government agencies, the UAS stakeholder community, and the designated FAA UAS Test Sites. This paper reports the technical and operational capabilities demonstrated during the UTM flight demonstration, March 6 through May 30, 2018. The demonstration featured geographically diverse operations, involving FAA UAS Test Sites in Alaska, Nevada, New York, North Dakota, Texas and Virginia. The demonstration leveraged the contributions of 30 partner organizations serving as UAS service suppliers, UAS operators, and/or providers of sensors, surveillance, connectivity, and management roles. Utilizing the UTM architecture developed at NASA, the demonstration explored 11 use cases for small UAS operations to highlight UTM capabilities at what NASA calls “Technical Capability Level (TCL) 3.” TCL 3 is characterized by multiple small UAS safely operating in moderately populated areas and beyond the visual line of sight of their operators. The TCL 3 flights demonstrated the basic feasibility of such operations in the UTM environment, including USS exchanges; communication, navigation and surveillance functions; sense and avoid capabilities; and technologies and procedures to enable them.

Aweiss, Arwa↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Recent Advancements in spoken language processing technologies have enabled the development of reliable automation tools to assist air traffic control (ATC) operations. These advancements present a unique opportunity to strategically implement digital taxi instructions for aircraft movement on the ground. Digital taxi instructions issue taxiing procedures to pilots as textual or graphical instructions. There are several benefits of digital instructions, including a reduction in radio congestion, elimination of communication errors, and improved aircraft monitoring capabilities. Natural language understanding (NLU) models can extract digital taxi instructions from verbal instructions issued by air traffic controllers. This capability enables the implementation of a digital taxi communication framework with minimal changes to the existing air traffic controller operational environment. We explore a novel application for NLU: automatically generating digital taxi instructions from air traffic controller speech. We describe the development of an annotation scheme to represent (aircraft) ground traffic communications in the US National Airspace System (NAS).Our annotation scheme uses intent classification and slot filling to extract taxi instructions, enabling NLU models to leverage syntactic information. Several neural network models were trained to categorize the controller’s intent and label information relevant to his or her intent.Our research demonstrates that it is feasible to use NLU to automatically generate digitaltaxi instructions, suggesting that it is a powerful tool for the implementation of digital taxi communications.

Hillel Steinmetz↗