Results for “Air Traffic Information Management” — Page 2

NASA NTRS2018

Laboratory Evaluation of Dynamic Routing of Air Traffic in an En Route Arrival Metering Environment

Arrival air traffic operations in the presence of convective weather are subject to uncertainty in aircraft routing and subsequently in flight trajectory predictability. Current management of arrival operations in weather-impacted airspace results in significant flight delay and suspension of arrival metering operations. The Dynamic Routing for Arrivals in Weather (DRAW) concept provides flight route amendment advisories to Traffic Management Coordinators to mitigate the impacts of convective weather on arrival operations. DRAW provides both weather conflict and schedule information for proposed route amendments, allowing air traffic managers to simultaneously evaluate weather avoidance routing and potential schedule and delay impacts. Subject matter experts consisting of retired Traffic Management Coordinators and retired Sector Controllers with arrival metering experience participated in a simulation study of Fort Worth Air Route Traffic Control Center arrival operations. Data were collected for Traffic Management Coordinator and Sector Controller participants over three weeks of simulation activities in October, 2017. Traffic Management Coordinators reported acceptable workload levels, a positive impact on their ability to manage arrival traffic while using DRAW, and initiated weather mitigation reroutes earlier while using DRAW. Sector Controllers also reported acceptable workload levels while using DRAW.

Air Traffic Management↗

NASA NTRS1993

The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system

The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

Hermes, Laurie G.↗

NASA NTRS2004

Overview of NASA Glenn Aero/Mobile Communication Demonstrations

The Glenn Research Center at Lewis Field (GRC) has been involved with several other NASA field centers on various networking and RF communications demonstrations and experiments since 1998. These collaborative experiments investigated communications technologies new to aviation, such as wideband Ku satcom, L-band narrowband satcom, and IP (Internet Protocol), using commercial off-the-shelf (COTS) components These technologies can be used to distribute weather and hazard data, air traffic management and airline fleet management information, and passenger cabin Internet service.

Brooks, David↗

NASA NTRS2004

Overview of NASA Glenn Aero/Mobile Communications Demonstrations

The Glenn Research Center at Lewis Field (GRC) has been involved with several other NASA field centers on various networking and RF communications demonstrations and experiments since 1998. These collaborative experiments investigated communications technologies new to aviation, such as wideband Ku satcom, L-band narrowband satcom, and IP (Internet Protocol), using commercial off-the-shelf (COTS) components These technologies can be used to distribute weather and hazard data, air traffic management and airline fleet management information, and passenger cabin Internet service.

Brooks, David↗

NASA NTRS2015

NASA Ames and Future of Space Exploration, Science, and Aeronautics

Pushing the frontiers of aeronautics and space exploration presents multiple challenges. NASA Ames Research Center is at the forefront of tackling these issues, conducting cutting edge research in the fields of air traffic management, entry systems, advanced information technology, intelligent human and robotic systems, astrobiology, aeronautics, space, earth and life sciences and small satellites. Knowledge gained from this research helps ensure the success of NASA's missions, leading us closer to a world that was only imagined as science fiction just decades ago.

Center results↗

NASA NTRS1980

Analysis of eighty-four commercial aviation incidents - Implications for a resource management approach to crew training

A resource management approach to aircrew performance is defined and utilized in structuring an analysis of 84 exemplary incidents from the NASA Aviation Safety Reporting System. The distribution of enabling and associated (evolutionary) and recovery factors between and within five analytic categories suggests that resource management training be concentrated on: (1) interpersonal communications, with air traffic control information of major concern; (2) task management, mainly setting priorities and appropriately allocating tasks under varying workload levels; and (3) planning, coordination, and decisionmaking concerned with preventing and recovering from potentially unsafe situations in certain aircraft maneuvers.

Murphy, M. R.↗

NASA NTRS2017

Management by Trajectory Trade Study of Roles and Responsibilities Between Participants and Automation Report

This report describes a trade study of roles and responsibilities associated with the Management by Trajectory (MBT) concept. The MBT concept describes roles, responsibilities, and information and automation requirements for providing air traffic controllers and managers the ability to quickly generate, evaluate and implement changes to an aircraft's trajectory. In addition, the MBT concept describes mechanisms for imposing constraints on flight operator preferred trajectories only to the extent necessary to maintain safe and efficient traffic flows, and the concept provides a method for the exchange of trajectory information between ground automation systems and the aircraft that allows for trajectory synchronization and trajectory negotiation. The participant roles considered in this trade study include: airline dispatcher, flight crew, radar controller, traffic manager, and Air Traffic Control System Command Center (ATCSCC) traffic management specialists. The proposed allocation of roles and responsibilities was based on analysis of several use cases that were developed for this purpose as well as for walking through concept elements. The resulting allocation of roles and responsibilities reflects both increased automation capability to support many aviation functions, as well as increased flexibility to assign responsibilities to different participants - in many cases afforded by the increased automation capabilities. Note that the selection of participants to consider for allocation of each function is necessarily rooted in the current environment, in that MBT is envisioned as an evolution of the National Airspace System (NAS), and not a revolution. A key feature of the MBT allocations is a vision for the traffic management specialist to take on a greater role. This is facilitated by the vision that separation management functions, in addition to traffic management functions, will be carried out as trajectory management functions. This creates an opportunity for flexibility, allowing the traffic management specialist to carry out tasks that today can only be carried out by the controller currently in contact with the aircraft. This additional tasking for the traffic management specialist comes with requirements for workload management. An increased role for the Data-side (D-side) controller relative to the Radar-side (R-side) controller is a potential approach to mitigating workload for the traffic management specialist, as the D-side controller would have similar ability to perform separation management functions in what today might be considered the "trajectory management" timeframe. This analysis did not distinguish between the D-side and R-side controllers since in many cases the R-side controller works unassisted.

Fernandes, Alicia D.↗

NASA NTRS2017

Airport Information Sharing Concept Architecture

The National Airspace System (NAS) Air Traffic management, control and operation depends on a timely and efficient distribution of real time information generated by stakeholders and published from a variety of sources. The Federal Aviation Administration System Wide Information Management (SWIM) is a service oriented architecture design to provide stakeholders with timely NAS information. However, there are other sources of useful information generated by stakeholders that can be included in the management of NAS operations. Airport facilities are host to most stakeholders operating in the NAS (airspace user, airport authority, ground handling, controller tower) and thus large information is generated and consumed at these facilities. The NASA Glenn Research center has been investigating an information exchange architecture framework that would enable the timely, efficient and secure gathering and distribution information generated at airport facilities. This presentation describes the framework architecture concept for the efficient information exchange of airport information.

Airports↗

NASA NTRS2017

Autonomous System Technologies for Resilient Airspace Operations

Increasing autonomous systems within the aircraft cockpit begins with an effort to understand what autonomy is and developing the technology that encompasses it. Autonomy allows an agent, human or machine, to act independently within a circumscribed set of goals; delegating responsibility to the agent(s) to achieve overall system objective(s). Increasingly Autonomous Systems (IAS) are the highly sophisticated progression of current automated systems toward full autonomy. Working in concert with humans, these types of technologies are expected to improve the safety, reliability, costs, and operational efficiency of aviation. IAS implementation is imminent, which makes the development and the proper performance of such technologies, with respect to cockpit operation efficiency, the management of air traffic and data communication information, vital. A prototype IAS agent that attempts to optimize the identification and distribution of "relevant" air traffic data to be utilized by human crews during complex airspace operations has been developed.

Houston, Vincent E.↗

NASA NTRSDate not supplied

Identifying Information Needs and Tools to Support Interactions between Upper Class E Traffic Management (ETM) Operations and the Air Traffic System (ATS)

With the introduction of high-altitude long endurance (HALE) vehicles and balloons designed to operate above 60,000 feet, the frequency and duration of operations in Upper Class E airspace are expected to increase. In response to the need for scalable traffic management for these diverse operations at higher altitudes, the FAA introduced the Upper Class E Traffic Management (ETM) concept. Like the successful demonstration of Uncrewed Aircraft System (UAS) Traffic Management (UTM), the ETM concept is also designed as a community-based, industry-driven cooperative approach to traffic management. As these vehicles and balloons ascend to/descend from ETM Cooperative Areas in Upper Class E, they will transit through Class A controlled airspace where they will interact with various entities of the conventional Air Traffic System (ATS) (e.g., Air Traffic Control (ATC)). This work explores tools that will help support ETM-ATS interactions for users throughout the ATS, as well as ETM Operators. An information needs analysis using ETM-ATS interaction use cases, revealed that the needed functionalities generally grouped themselves into two main themes, the visualization of flights and airspace designations, and digital communication capabilities across various human users. In this paper, we describe two envisioned tools, 1) an Integrated Visualization Tool to display flight information and airspace designations, and 2) an Integrated Digital Communication Tool to facilitate two-way information exchange between users about vehicle position information, the coordination of airspace approvals, and notifications. The tools we describe create an integrated visual representation of vehicles and airspace designations with a set of communication capabilities to consolidate information into a single display interface. These tools may be used to guide the development of prototype tools for demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center to further explore ETM-ATS interactions within the ETM concept.

Upper Class E Traffic Management (ETM)↗

NASA NTRSDate not supplied

Identifying Information Needs and Tools to Support Interactions between Upper Class E Traffic Management (ETM) Operations and the Air Traffic System (ATS)

With the introduction of high-altitude long endurance (HALE) vehicles and balloons designed to operate above 60,000 feet, the frequency and duration of operations in Upper Class E airspace are expected to increase. In response to the need for scalable traffic management for these diverse operations at higher altitudes, the FAA introduced the Upper Class E Traffic Management (ETM) concept. Like the successful demonstration of Uncrewed Aircraft System (UAS) Traffic Management (UTM), the ETM concept is also designed as a community-based, industry-driven cooperative approach to traffic management. As these vehicles and balloons ascend to/descend from ETM Cooperative Areas in Upper Class E, they will transit through Class A controlled airspace where they will interact with various entities of the conventional Air Traffic System (ATS) (e.g., Air Traffic Control (ATC)). This work explores tools that will help support ETM-ATS interactions for users throughout the ATS, as well as ETM Operators. An information needs analysis using ETM-ATS interaction use cases, revealed that the needed functionalities generally grouped themselves into two main themes, the visualization of flights and airspace designations, and digital communication capabilities across various human users. In this paper, we describe two envisioned tools, 1) an Integrated Visualization Tool to display flight information and airspace designations, and 2) an Integrated Digital Communication Tool to facilitate two-way information exchange between users about vehicle position information, the coordination of airspace approvals, and notifications. The tools we describe create an integrated visual representation of vehicles and airspace designations with a set of communication capabilities to consolidate information into a single display interface. These tools may be used to guide the development of prototype tools for demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center to further explore ETM-ATS interactions within the ETM concept.

Upper Class E Traffic Management (ETM)↗

NASA NTRS2010

Generic Airspace Concepts and Research

The purpose of this study was to evaluate methods for reducing the training and memorization required to manage air traffic in mid-term, Next Generation Air Transportation System (NextGen) airspace. We contrasted the performance of controllers using a sector information display and NextGen automation tools while working with familiar and unfamiliar sectors. The airspace included five sectors from Oakland and Salt Lake City Centers configured as a "generic center" called "West High Center." The Controller Information Tool was used to present essential information for managing these sectors. The Multi Aircraft Control System air traffic control simulator provided data link and conflict detection and resolution. There were five experienced air traffic controller participants. Each was familiar with one or two of the five sectors, but not the others. The participants rotated through all five sectors during the ten data collection runs. The results addressing workload, traffic management, and safety, as well as controller and observer comments, supported the generic sector concept. The unfamiliar sectors were comparable to the familiar sectors on all relevant measures.

Mogford, Richard H.↗

NASA NTRS1994

Initial Field Evaluation of Pilot Procedures for Flying CTAS Descent Clearances

The Center TRACON Automation System (CTAS) is a new support system that is designed to assist air traffic controllers in the management of arrival traffic. CTAS will provide controllers with more information about current air traffic, enabling them to provide clearances for efficient, conflict-free descents that help achieve an orderly stream of aircraft at the final approach fix. CTAS is a computer-based system that functions as a "ground-based FMS" that can predict flight trajectories and arrival times for all incoming aircraft. CTAS uses an aircraft's cruise airspeed; current air traffic, winds and temperature; performance characteristics of the aircraft type; and individual airline preferences to create a flight profile from cruise altitude to the final approach fix. Controllers can use this flight profile to provide a descent clearance that will allow an aircraft to fly an efficient descent and merge more smoothly with other arriving aircraft. A field test of the CTAS Descent Advisor software was conducted at the Denver Center for aircraft arriving at the Stapleton International Airport from September 12-29. CTAS Descent clearances were given to a NASA flight test aircraft and to 77 airline flights that arrived during low traffic periods. For the airline portion of the field test, cockpit procedures and pilot briefing packages for both FMS equipped and unequipped aircraft were developed in cooperation with an airline. The procedures developed for the FMS equipped aircraft were to fly a VNAV descent at a controller specified speed to cross a metering fix at a specified altitude and speed. For nonFMS aircraft, the clearance also specified a CTAS calculated top-of-descent point. Some CTAS related flight deck issues included how much time was available to the pilots' for compliance, the amount of information that needed to be interpreted in the clearance and possible repercussions of misunderstandings. Data collected during the study ranged from subjective data (including the airline pilots' opinions and comments about the new descent clearances and procedures) to objective data (including observations of aircraft performance from the flight deck). This paper will present data and the resulting changes in the design of the procedures and clearance phraseology.

Palmer, Everett↗

NASA NTRSDate not supplied

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗

NASA NTRS2022

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗

NASA NTRS2010

A Final Approach Trajectory Model for Current Operations

Predicting accurate trajectories with limited intent information is a challenge faced by air traffic management decision support tools in operation today. One such tool is the FAA's Terminal Proximity Alert system which is intended to assist controllers in maintaining safe separation of arrival aircraft during final approach. In an effort to improve the performance of such tools, two final approach trajectory models are proposed; one based on polynomial interpolation, the other on the Fourier transform. These models were tested against actual traffic data and used to study effects of the key final approach trajectory modeling parameters of wind, aircraft type, and weight class, on trajectory prediction accuracy. Using only the limited intent data available to today's ATM system, both the polynomial interpolation and Fourier transform models showed improved trajectory prediction accuracy over a baseline dead reckoning model. Analysis of actual arrival traffic showed that this improved trajectory prediction accuracy leads to improved inter-arrival separation prediction accuracy for longer look ahead times. The difference in mean inter-arrival separation prediction error between the Fourier transform and dead reckoning models was 0.2 nmi for a look ahead time of 120 sec, a 33 percent improvement, with a corresponding 32 percent improvement in standard deviation.

Gong, Chester↗

NASA NTRS2011

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Idris, Husni↗

NASA NTRS2020

Ramp Traffic Console (RTC) and Ramp Manager Traffic Console (RMTC) User Manual

This document serves as a user manual for the ATD-2 Ramp Traffic Console (RTC) (version 5.11) utilized by the Ramp Control Tower. It describes the elements of the RTC interface and provides step-by-step instructions for using the tool. RTC provides live flight information, including, flight state and location, departure/arrival schedules, gate conflicts, Traffic Management Initiative (TMI) restrictions, and gate advisories to support Surface Time-Based Metering (STBM). RTC facilitates information sharing with the Air Traffic Control (ATC) Tower. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) for Ramp Manager functions, such as managing the priority flight list and setting the ramp status. The RTC/RMTC ramp tools are components of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Deborah Lee Bakowski↗