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NASA NTRS2012

Air Traffic Management Research at NASA Ames

The Aviation Systems Division at the NASA Ames Research Center conducts leading edge research in air traffic management concepts and technologies. This overview will present concepts and simulation results for research in traffic flow management, safe and efficient airport surface operations, super density terminal area operations, separation assurance and system wide modeling and simulation. A brief review of the ongoing air traffic management technology demonstration (ATD-1) will also be presented. A panel discussion, with Mr. Davis serving as a panelist, on air traffic research will follow the briefing.

Davis, Thomas J.↗

NASA NTRS2011

Trajectory Assessment and Modification Tools for Next Generation Air Traffic Management Operations

This paper reviews three Next Generation Air Transportation System (NextGen) based high fidelity air traffic control human-in-the-loop (HITL) simulations, with a focus on the expected requirement of enhanced automated trajectory assessment and modification tools to support future air traffic flow management (ATFM) planning positions. The simulations were conducted at the National Aeronautics and Space Administration (NASA) Ames Research Centers Airspace Operations Laboratory (AOL) in 2009 and 2010. The test airspace for all three simulations assumed the mid-term NextGenEn-Route high altitude environment utilizing high altitude sectors from the Kansas City and Memphis Air Route Traffic Control Centers. Trajectory assessment, modification and coordination decision support tools were developed at the AOL in order to perform future ATFM tasks. Overall tool usage results and user acceptability ratings were collected across three areas of NextGen operatoins to evaluate the tools. In addition to the usefulness and usability feedback, feasibility issues, benefits, and future requirements were also addressed. Overall, the tool sets were rated very useful and usable, and many elements of the tools received high scores and were used frequently and successfully. Tool utilization results in all three HITLs showed both user and system benefits including better airspace throughput, reduced controller workload, and highly effective communication protocols in both full Data Comm and mixed-equipage environments.

Brasil, Connie↗

NASA NTRS1996

Advanced Air Traffic Management Research (Human Factors and Automation): NASA Research Initiatives in Human-Centered Automation Design in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. The core processes of control and the distribution of decision making in that control are undergoing extensive analysis. From our perspective, the human operators and the procedures by which they interact are the fundamental determinants of the safe, efficient, and flexible operation of the system. In that perspective, we have begun to explore what our experience has taught will be the most challenging aspects of designing and integrating human-centered automation in the advanced system. We have performed a full mission simulation looking at the role shift to self-separation on board the aircraft with the rules of the air guiding behavior and the provision of a cockpit display of traffic information and an on-board traffic alert system that seamlessly integrates into the TCAS operations. We have performed and initial investigation of the operational impact of "Dynamic Density" metrics on controller relinquishing and reestablishing full separation authority. (We follow the assumption that responsibility at all times resides with the controller.) This presentation will describe those efforts as well as describe the process by which we will guide the development of error tolerant systems that are sensitive to shifts in operator work load levels and dynamic shifts in the operating point of air traffic management.

Corker, Kevin M.↗

NASA NTRS2015

Air Traffic Management Technology Demostration: 1 Research and Procedural Testing of Routes

NASA's Air Traffic Management Technology Demonstration-1 (ATD-1) will operationally demonstrate the feasibility of efficient arrival operations combining ground-based and airborne NASA technologies. The ATD-1 integrated system consists of the Traffic Management Advisor with Terminal Metering which generates precise time-based schedules to the runway and merge points; Controller Managed Spacing decision support tools which provide controllers with speed advisories and other information needed to meet the schedule; and Flight deck-based Interval Management avionics and procedures which allow flight crews to adjust their speed to achieve precise relative spacing. Initial studies identified air-ground challenges related to the integration of these three scheduling and spacing technologies, and NASA's airborne spacing algorithm was modified to address some of these challenges. The Research and Procedural Testing of Routes human-in-the-loop experiment was then conducted to assess the performance of the new spacing algorithm. The results of this experiment indicate that the algorithm performed as designed, and the pilot participants found the airborne spacing concept, air-ground procedures, and crew interface to be acceptable. However, the researchers concluded that the data revealed issues with the frequency of speed changes and speed reversals.

Wilson, Sara R.↗

NASA NTRS2019

Building a Knowledge Graph for the Air Traffic Management Community

Historically, most of the focus in the knowledge graph community has been on the support for web, social network, or product search applications. This paper describes some of our experience in developing a large-scale applied knowledge graph for a more technical audience with more specialized information access and analysis needs - the air traffic management community. We describe ATMGRAPH (NASA's Air Traffic Management (ATM) Knowledge Graph), a knowledge graph created by integrating various sources of structured aviation data, provided in large part by US federal agencies. We review some of the practical challenges we faced in creating this knowledge graph.

Air Traffic Information Management↗

NASA NTRS2019

Fe(exp3) - A Monte Carlo Simulation Capability for Evaluation of New Air Traffic Management Concepts

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) introduce high-density operations in low-altitude airspace and will change the paradigm of the traditional air traffic system. The Flexible engine for Fast-time evaluation of Flight environments (Fe3) provides the capability of statistically analyzing high-density, high-fidelity, and low-altitude traffic system without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. With this simulation capability, stakeholders can study the impacts of critical factors, define requirements, policies, and protocols needed to support a safe yet efficient traffic system, assess operational risks, and optimize flight schedules. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and applications in high density air traffic operations are also presented.

Paralellization↗

NASA NTRS2004

Application of AirCell Cellular AMPS Network and Iridium Satellite System Dual Mode Service to Air Traffic Management

The AirCell/Iridium dual mode service is evaluated for potential applications to Air Traffic Management (ATM) communication needs. The AirCell system which is largely based on the Advanced Mobile Phone System (AMPS) technology, and the Iridium FDMA/TDMA system largely based on the Global System for Mobile Communications(GSM) technology, can both provide communication relief for existing or future aeronautical communication links. Both have a potential to serve as experimental platforms for future technologies via a cost effective approach. The two systems are well established in the entire CONUS and globally hence making it feasible to utilize in all regions, for all altitudes, and all classes of aircraft. Both systems have been certified for air usage. The paper summarizes the specifications of the AirCell/Iridium system, as well as the ATM current and future links, and application specifications. the paper highlights the scenarios, applications, and conditions under which the AirCell/Iridium technology can be suited for ATM Communication.

Shamma, Mohammed A.↗

NASA NTRS2020

NASA Air Traffic Management – eXploration (ATM-X) Insight Assessment

The focus of this final Air Traffic Management – eXploration (ATM-X) Insight Assessment (IA) report is to summarize key findings, lessons learned, gaps, and shortfalls from 2018 to 2019 National Aeronautics and Space Administration (NASA) ATM-X research and to share the outcomes from National Airspace System (NAS) stakeholder discussions with the broader community. This report was generated from a comprehensive review of 25 NASA ATM-X research papers and augmented by interviews with 23 NASA researchers as well as three virtual seminars discussing the project findings and priorities with 47 NAS stakeholders. While these papers cover a wide range of relevant topics, they only represent a small portion of the vast amount of ongoing research in this rapidly evolving area by industry, academia, and other agencies. The research summary described here could be further refined and expanded by reviewing additional studies.

air transportation↗

NASA NTRSDate not supplied

Air Traffic Management Response to Vertiport Closure

Increasing quantities of urban air mobility operations requires consideration of various contingencies associated with novel operational tempos and airspace management practices. This paper explores a contingency scenario in which a single vertiport closes unexpectedly during high tempo operations. Dynamic re-planning is explored as a function performed both by operators using common operating procedures and through emergency assistance from air traffic control. Implications for airspace capacity, infrastructure requirements, and vehicle energy reserves are discussed.

UAM↗

NASA NTRSDate not supplied

Air Traffic Management Response to Vertiport Closure

UAM↗

NASA NTRS2012

Air Traffic Management Research at NASA

The U.S. air transportation system is the most productive in the world, moving far more people and goods than any other. It is also the safest system in the world, thanks in part to its venerable air traffic control system. But as demand for air travel continues to grow, the air traffic control systems aging infrastructure and labor-intensive procedures are impinging on its ability to keep pace with demand. And that impinges on the growth of our economy. Part of NASA's current mission in aeronautics research is to invent new technologies and procedures for ATC that will enable our national airspace system to accommodate the increasing demand for air transportation well into the next generation while still maintaining its excellent record for safety. It is a challenging mission, as efforts to modernize have, for decades, been hamstrung by the inability to assure safety to the satisfaction of system operators, system regulators, and/or the traveling public. In this talk, we'll provide a brief history of air traffic control, focusing on the tension between efficiency and safety assurance, and we'll highlight some new NASA technologies coming down the pike.

Farley, Todd↗

NASA NTRSDate not supplied

Transitioning TEMPO Data for Air Quality Management Applications at the NASA SPoRT Center

The TEMPO mission has been observing air pollutants every hour during the daytime across its Field of Regard (FoR) covering greater North America since First Light on August 2, 2023. The highly anticipated public release of TEMPO data occurred on May 20, 2024, consisting of level 2 and level 3 trace gas data products of nitrogen dioxide, formaldehyde, and ozone. The NASA SPoRT Center is developing value-added products and tools to support the TEMPO mission and Early Adopters program with special attention on stakeholder from air agencies. One component of our work is focused on evaluating the TEMPO products over stakeholder target areas using Pandora and surface monitor observations to characterize the uncertainties and develop best practices for processing and analyzing TEMPO data. Methods for oversampling TEMPO data to 1 km resolution are being applied over the target areas to resolve fine-scale emission sources and pollutant gradients. Machine learning techniques using TEMPO, surface monitor, and model data to estimate surface-level nitrogen dioxide concentrations are being developed over the target areas. A SPoRT viewer for TEMPO has been launched for providing visualizations of the TEMPO products and an ArcGIS dashboard is being designed for enabling air agency stakeholders to efficiently analyze TEMPO data. Training materials including user guides are being developed to ensure the effective and sustained use of TEMPO data at our stakeholder agencies. One major goal of our TEMPO initiatives at SPoRT is to better enable the inclusion of TEMPO data in air quality management applications such as exceptional event demonstrations through our close engagement with stakeholders. This talk will provide an update on our SPoRT activities and showcase use cases of TEMPO data for monitoring different emission sources including wildland fire smoke.

Air Quality↗

NASA NTRSDate not supplied

A Brief Introduction to AI/ML Applications of Air Traffic Management Data at NASA Ames

This presentation will give a brief overview of several AI/ML This presentation will give a brief overview of several AI/ML projects that NASA Ames interns are exploring in partnership with NASA Aeronautic Research Institute (NARI) and the FAA. NASA is interested in Natural Language Processing (NLP) of various legacy text and speech data within air traffic management e.g., Notices To Airmen (NOTAMs), Letters of Agreement (LoAs), Standard Operating Procedures (SOPs), and Air Traffic Control Center audio briefings. Since our focus is on applying state of the art AI/ML tools to legacy air traffic management data, we first showcase the different data sources of interest followed by a brief introduction to the techniques and language models used. We present some exciting preliminary results on each topic including both unsupervised learning techniques (e.g., clustering) and other modern language models (e.g., BERT) that help extract useful information from these data sources that are interpretable by both man and machine.

Air Traffic Management↗

NASA NTRS1996

Human-Centered Technologies and Procedures for Future Air Traffic Management: A Preliminary Overview of 1996 Studies and Results

In this project, we have been exploring the use of a general methodology to predict the impact of future Air Traffic Management (ATM) concepts and technologies. In applying this methodology, our emphasis has been on the importance of modeling coordination and cooperation among the multiple agents within this system, and on understanding how the interactions among these agents will be influenced as new roles, responsibilities, procedures and technologies are introduced. To accomplish this, we have been collecting data on performance under the current air traffic management system, trying to identify critical problem areas and looking for exemplars suggestive of general approaches for solving such problems. Based on the results of these field studies, we have developed a set of scenarios centered around potential future system designs, and have conducted studies using these scenarios involving a total 40 controllers, dispatchers, pilots and traffic managers. The purpose of this report is to provide NASA with an early summary of the major recommendations that have resulted from our research under the AATT Program thus far. Recommendations 1-3 deal with general approaches that our findings suggest should be incorporated in future AATT Program activities, while Recommendations 4-11 identify some specific topics and technologies that merit research and development activities. Detailed technical reports containing supporting data, as well as the results of our still ongoing analyses, will be provided at a later date. The remainder of this report is organized as follows. Section 1 briefly describes the general design philosophy supported by our empirical studies. Section 2 presents the research methods we have used for identifying requirements for future system designs and for evaluating alternative design solutions. Section 3 discusses preliminary results from an initial set of investigations that we have conducted using these research methods. Section 4 then provides an overall summary. An outline of the rest of this preliminary project summary is provided on the following page.

Smith, Philip↗

NASA NTRS2005

Air Traffic Management Research at NASA Ames Research Center

Since the late 1980's, NASA Ames researchers have been investigating ways to improve the air transportation system through the development of decision support automation. These software advances, such as the Center-TRACON Automation System (eTAS) have been developed with teams of engineers, software developers, human factors experts, and air traffic controllers; some ASA Ames decision support tools are currently operational in Federal Aviation Administration (FAA) facilities and some are in use by the airlines. These tools have provided air traffic controllers and traffic managers the capabilities to help reduce overall delays and holding, and provide significant cost savings to the airlines as well as more manageable workload levels for air traffic service providers. NASA is continuing to collaborate with the FAA, as well as other government agencies, to plan and develop the next generation of decision support tools that will support anticipated changes in the air transportation system, including a projected increase to three times today's air-traffic levels by 2025. The presentation will review some of NASA Ames' recent achievements in air traffic management research, and discuss future tool developments and concepts currently under consideration.

Lee, Katharine↗

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 NTRS1999

Modeling Air Traffic Management Technologies with a Queuing Network Model of the National Airspace System

This report describes an integrated model of air traffic management (ATM) tools under development in two National Aeronautics and Space Administration (NASA) programs -Terminal Area Productivity (TAP) and Advanced Air Transport Technologies (AATT). The model is made by adjusting parameters of LMINET, a queuing network model of the National Airspace System (NAS), which the Logistics Management Institute (LMI) developed for NASA. Operating LMINET with models of various combinations of TAP and AATT will give quantitative information about the effects of the tools on operations of the NAS. The costs of delays under different scenarios are calculated. An extension of Air Carrier Investment Model (ACIM) under ASAC developed by the Institute for NASA maps the technologies' impacts on NASA operations into cross-comparable benefits estimates for technologies and sets of technologies.

Long, Dou↗