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NASA NTRS1979

Transportation and General Traffic Management, Change 2

This Handbook sets forth those transportation and general traffic management responsibilities, guidelines, and procedures governing the use of commercial and Government transportation for NASA. Transportation is an integral function of the logistic process, involving all activities incident to the movement of persons and things. The fundamental and continuous objectives of transportation are to control and diminish the time-distance of lines of communication by the most suitable means. The function of transportation is accomplished through, and encompasses all, the planning, direction, supervision, and execution of the technical, operational, and administrative tasks required to procure or furnish efficient and economical conveyance of cargo and personnel by all modes of commercial and Government transportation. This Handbook is applicable to NASA Headquarters and Field Installations.

Source record↗

NASA NTRS2000

Antennas Designed for Advanced Communications for Air Traffic Management (AC/ATM) Project

The goal of the Advanced Communications for Air Traffic Management (AC/ATM) Project at the NASA Glenn Research Center at Lewis Field is to enable a communications infrastructure that provides the capacity, efficiency, and flexibility necessary to realize a mature free-flight environment. The technical thrust of the AC/ATM Project is targeted at the design, development, integration, test, and demonstration of enabling technologies for global broadband aeronautical communications. Since Ku-band facilities and equipment are readily available, one of the near-term demonstrations involves a link through a Kuband communications satellite. Two conformally mounted antennas will support the initial AC/ATM communications links. Both of these are steered electronically through monolithic microwave integrated circuit (MMIC) amplifiers and phase shifters. This link will be asymmetrical with the downlink to the aircraft (mobile vehicle) at a throughput rate of greater than 1.5 megabits per second (Mbps), whereas the throughput rate of the uplink from the aircraft will be greater than 100 kilobits per second (kbps). The data on the downlink can be narrow-band, wide-band, or a combination of both, depending on the requirements of the experiment. The AC/ATM project is purchasing a phased-array Ku-band transmitting antenna for the uplink from the test vehicle. Many Ku-band receiving antennas have been built, and one will be borrowed for a short time to perform the initial experiments at the NASA Glenn Research Center at Lewis Field. The Ku-band transmitting antenna is a 254-element MMIC phased-array antenna being built by Boeing Phantom Works. Each element can radiate 100 mW. The antenna is approximately 43-cm high by 24-cm wide by 3.3-cm thick. It can be steered beyond 60 from broadside. The beamwidth varies from 6 at broadside to 12 degrees at 60 degrees, which is typical of phased-array antennas. When the antenna is steered to 60 degrees, the beamwidth will illuminate approximately five satellites on the orbital arc. Spread spectrum techniques will be employed to keep the power impinging on the adjacent satellites below their noise floor so that no interference results. This antenna is power limited. If the antenna elements (currently 254) are increased by a factor of 4 (1024) or 16 (4096), the gain will increase and the beamwidth will decrease in proportion. For the latter two antenna sizes, the power must be "backed off" to prevent interference with the neighboring satellites. The receiving antenna, which is approximately 90-cm high, 60-cm wide, and 3.5-cm thick, is composed of 1500 phased-array elements. The system phased-array controller can control both a 1500-element receiving antenna and a 500-element transmitting antenna. For ground testing, this controller will allow manual beam pointing and polarization alignment. For normal operation, the system can be connected to the receiving antenna and the navigation system for real-time autonomous track operation. This will be accomplished by first pointing both antennas at the satellite using information from the aircraft data bus. Then, the system phased-array controller will electronically adjust the antenna pointing of the receiving antenna to find the peak signal. After the peak signal has been found, the beam of the transmitting antenna will be pointed to the same steering angles as the receiving antenna. For initial ground testing without an aircraft, the ARINC 429 data bus (ARINC Inc., Annapolis, Maryland) will be simulated by a gyro system purchased for the follow-on to the Monolithic Microwave Integrated Circuit (MMIC) Arrays for Satellite Communication on the Move (MASCOM) Project. MASCOM utilized the Advanced Communications Technology Satellite (ACTS) with a pair of Ka-band experimental phased-array antennas.

Zakrajsek, Robert J.↗

NASA NTRSDate not supplied

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗

NASA NTRSDate not supplied

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

Natural Language Processing↗

NASA NTRS2016

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

data management↗

NASA NTRSDate not supplied

Upper E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a coopertive, service-based approach that provides services and capabilities in areas (e.g., Upper E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes an overview of discussions and industry news covering the time since the previous group meeting, a presentation on initial work titled 'Sensitivity Study of Minimum Reserved Airspace in ETM Operations,' and a high level discussion titled 'Separation Management Service Framework for ETM.'

Upper E↗

NASA NTRS1991

The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

Ansari, Nirwan↗

NASA NTRS2002

Advanced Air Transportation Technologies (AATT) Project: Distributed Air-Ground Traffic Management

This viewgraph presentation provides an overview of active Distributed Air Ground Traffic Management (DAG-TM) work and reported on its overall progress to date. It does not include details on the concept elements (CEs).The DAG-TM research project is defined as a concept development and definition project and no tools will be delivered. Of the 14 CEs, three are being explored actively: CE-5, CE-6, and CE-11. Overviews of CE-5 (Free Maneuvering for User-Preferred Separation Assurance and Local TFM Conformance), CE-6 (En Route and Transition Trajectory Negotiation for User-Preferred Separation and Local TFM Conformance) and CE-11 (Self-Spacing for Merging and In-Trail Separation) are presented.

Mogford, Richard↗

NASA NTRS2019

Analysis of At-Altitude LTE Power Spectra for C2 Communications for UAS Traffic Management

The National Aeronautics and Space Administration’s (NASA) Unmanned Aircraft Systems Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude small Unmanned Aerial Systems (sUAS, also known as drones) operations. This paper presents results of work completed in the paper [1] presented at the 2018 ICNS conference where proposed approaches were explored for evaluating and analyzing sUAS Command and Control (C2) links based on commercial cellular networks. This paper focuses on the UTM Project’s Technology Capability Level 3 (TCL-3) test results which address the communications portion identified within the same paper. A software defined radio (SDR) was flown as a sUAS payload to capture received signal spectrum in Long Term Evolution (LTE) frequency bands of interest. The purpose was to measure the RF environment at UTM altitudes to characterize the interference potential. The SDR payload was flown at various stationary altitudes where the LTE over-the-air complex (I/Q) samples were captured by the SDR and later post-processed. The SDR received inputs through an omnidirectional antenna. The complex samples captured were an aggregate of transmissions received from all line-of-sight (LOS) towers within the geographic area for the specific radio frequency bandwidth the SDR is programmed to capture. Using this approach, the complex samples captured do not distinguish between the various eNodeB's (Long Term Evolution (LTE) transmitting towers). The complex samples were post processed via a Discrete Fourier Transform (DFT) algorithm to view the captured spectrum along with the power levels across the captured LTE bandwidth. This SDR payload process of capturing complex samples was done at two different regions within the US: 1) NASA's Ames Research Center (ARC) in Moffett Field, CA, and 2) Griffiss Airfield in Rome, NY. The data capture at the ARC site was done at two physical locations within the Ames campus where many stationary altitude captures where done as high as 800 ft. above ground level (AGL). The data captured at the Griffiss Airport (also known as the NY Corridor Site) were acquired at one location with three specific stationary altitude levels – {Ground Level (GL), 300 ft., and 400 ft.}. The LTE spectrum power levels were captured for two LTE carriers, AT&T and Verizon, at both sites where their respective spectra and power levels were measured and compared at various altitudes. The overall results show that there is an increase in LTE spectrum power levels at higher altitudes for drones. A detailed analysis of this data and conclusions drawn from the results are presented in this paper.

Kerczewski, Robert J.↗

NASA NTRSDate not supplied

Uncrewed Aerial System Traffic Management Beyond Visual Line of Sight Multi Operator Technology Assessment Simulation

UAS Traffic Management (UTM) is a rapidly evolving space with increasing demand for regulation surrounding more complex operations. Beyond visual line of sight (BVLOS) operations are among these complex operations. The NASA UTM BVLOS sub-project is focusing on enabling more routine BVLOS operations through data collection for support of standards formulation. The Multi Operator Technology Assessment (MOTA) simulation is one of these activities that collects data on BVLOS operations within the same geographical area while sharing operational intents through a USS. Data collected includes workload, situation awareness, and usability on nominal and off-nominal operations. Results of this study are intended to provide recommendations for standards as well as provide insight on improvements to the systems under test. NASA intends to incorporate those improvements into their operations to support and updated BVLOS waiver from the FAA’s Near-Term Approval Process (NTAP).

Bryan J Petty↗

NASA NTRSDate not supplied

Uncrewed Aerial System Traffic Management Beyond Visual Line of Sight Multi Operator Technology Assessment Simulation

Bryan J Petty↗

NASA NTRSDate not supplied

Upper E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a cooperative, service-based approach that provides services and capabilities in areas (e.g., Upper E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes a presentation of Communication, Navigation, and Surveillance assessments as they relate to the ETM environment, a review of Industry thoughts on equitable airspace access and associated rules of the road, and an initial presentation of the separation assurance process and related negotiation aspect.

Upper E↗

NASA NTRSDate not supplied

ETM: Upper E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a cooperative, service-based approach that provides services and capabilities in areas (e.g., Upper E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes an overview of discussions and industry news covering the time since the previous group meeting, a discussion of industry's position on operation intent and negotiation strategies in ETM airspace, applications of that position as captured through use cases, and a simulation roadmap for NASA's planned work ahead into CY21.

Upper E↗

NASA NTRSDate not supplied

ETM: Upper E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a cooperative, service-based approach that provides services and capabilities in areas (e.g., Upper E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes an overview of discussions and industry news covering the time since the previous group meeting, a discussion of industry's feedback regarding a specific use case, a presentation on lexicon and the definition of Common Operating Practices, and an update on modeling and simulation work.

Upper E↗

NASA NTRSDate not supplied

Upper E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a cooperative, service-based approach that provides services and capabilities in areas (e.g., Upper E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes an overview of discussions and industry news covering the time since the previous group meeting, a recap of the group's history and road ahead, a discussion of industry's initial position on, 'Industry principles for ETM rules of the road: Conflict identification and resolution,' and a simulation roadmap for planned work ahead.

Upper E↗

NASA NTRSDate not supplied

ETM: Upper Class E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a cooperative, service-based approach that provides services and capabilities in areas (e.g., Upper Class E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper Class E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes an overview of discussions and industry news covering the time since the previous group meeting, a discussion of questions in response to a proposal document from Aerospace Industries Association (AIA), an update on modeling and simulation work, and announcements of upcoming plans for the project.

Upper E↗

NASA NTRS2018

Flight Deck Implications for the Implementation of an Integrated Arrival, Departure, and Surface (IADS) Traffic Management System

NASA's Airspace Technical Demonstration-2 (ATD-2) Integrated Arrival, Departure, and Surface (IADS) traffic management system integrates strategic and tactical scheduling tools for traffic sequencing from the gate to the overhead stream and back again for multi-airport, metroplex environments. The system is expected to increase airport efficiency, predictability, and throughout while improving information sharing among all airport operators. A series of knowledge elicitation sessions were conducted with commercial airline pilots and general aviation pilots to characterize airport operations and procedures. This presentation describes ATD-2 IADS-enabled Information Sharing impacts on the Flight Deck, benefits of that Information Sharing, pilot procedural changes, our pilot engagement/outreach efforts, use of a Mobile App to faciliate information flow in GA operations, and future IADS efforts at other airports/metroplexes.

IADS↗

NASA NTRSDate not supplied

Validation of an Automated System for Arrival Traffic Management

The fuel-efficiencies of arrival flights that were managed by an automated system were compared to the fuel-efficiencies of arrival flights that were managed by air traffic controllers. It was infeasible to have the automated system control arrivals in real operations, so the comparison was accomplished by setting up a fast-time simulation where the automated system could manage arrivals with the same initial conditions and flight plans as those that operated in real operations during a selected comparison period and in the same background traffic. For this study, Newark Liberty International Airport was selected as the arrival airport because its high traffic load and constrained arrival procedures were expected to highlight fuel-efficiency benefits of an automated system. In the simulation, the automated system managed Newark arrivals, and the other flights (arrivals to other airports, departures, and overflights) composed the background traffic. To match the simulation and the real operations background traffic, the other flights flew in simulation the same trajectory that they flew in real operations during the comparison period. Fuel-efficiency was measured by calculating fuel burns of the arrival trajectories. The fuel-efficiencies of arrival trajectories produced in the simulation were compared with the estimated fuel-efficiencies of arrival trajectories recorded from real operations during the comparison period. Results showed that automation managed arrivals burned 346 lbs less fuel per flight on average than controller managed arrivals.

air traffic control↗