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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Concept of Operations for Interval Management Arrivals and Approach

This paper presents the concept of operations for interval management operations to be deployed in the US National Airspace System (NAS) by the Federal Aviation Administration (FAA) after 2020. The use of interval management operations is described that begin in en route airspace and continue to a termination point inside the arrival terminal area, in a terminal environment that includes other arrival management tools such as arrival metering, Ground-based Interval Management - Spacing (GIM-S), and Terminal Sequencing and Spacing (TSAS). The roles of Air Traffic Controllers and Flight Crews and the ground automation tools that are used by Air Traffic Controllers to enable the primary operation and variations are described.

Hicok, Daniel S.↗
DOE OSTI2017

Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better at higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO 2 , NO x , VOC, PM 10 ) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2012

NASA Research on an Integrated Concept for Airport Surface Operations Management

Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. There have been attempts to address the resulting inefficiencies with both strategic and tactical tools for metering departure aircraft. This presentation gives an overview of Spot And Runway Departure Advisor with Collaborative Decision Making (SARDA-CDM): an integrated strategic and tactical system for improving surface operations by metering departure aircraft. SARDA-CDM is the augmentation of ground and local controller advisories through sharing of flight movement and related operations information between airport operators, flight operators and air traffic control at the airport. The goal is to enhance the efficiency of airport surface operations by exchanging information between air traffic control and airline operators, while minimizing adverse effects on stakeholders and passengers. The presentation motivates the need for departure metering, and provides a brief background on the previous work on SARDA. Then, the concept of operations for SARDA-CDM is described. Then the preliminary results from testing the concept in a real-time automated simulation environment are described. Results indicate benefits such as reduction in taxiing delay and fuel consumption. Further, the preliminary implementation of SARDA-CDM seems robust for two minutes delay in gate push-back times.

Gupta, Gautam↗
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↗
NASA NTRS2018

Predicting the Operational Acceptance of Airborne Flight Reroute Requests Using Data Mining

For tools that generate more efficient flight routes or reroute advisories, it is important to ensure compatibility of automation and autonomy decisions with human objectives so as to ensure acceptability by the human operators. In this paper, the authors developed a proof of concept predictor of operational acceptability for route changes during a flight. Such a capability could have applications in automation tools that identify more efficient routes around airspace impacted by weather or congestion and that better meet airline preferences. The predictor is based on applying data mining techniques, including logistic regression, a decision tree, a support vector machine, a random forest and Adaptive Boost, to historical flight plan amendment data reported during operations and field experiments. Cross validation was used for model development, while nested cross validation was used to validate the models. The model found to have the best performance in predicting air traffic controller acceptance or rejection of a route change, using the available data from Fort Worth Air Traffic Control Center and its adjacent Centers, was the random forest, with an F-score of 0.77. This result indicates that the operational acceptance of reroute requests does indeed have some level of predictability, and that, with suitable data, models can be trained to predict the operational acceptability of reroute requests. Such models may ultimately be used to inform route selection by decision support tools, contributing to the development of increasingly autonomous systems that are capable of routing aircraft with less human input than is currently the case.

Operational Acceptability↗
NASA NTRS1990

Guidance concepts for time-based flight operations

Airport congestion and the associated delays are severe in today's airspace system and are expected to increase. NASA and the FAA is investigating various methods of alleviating this problem through new technology and operational procedures. One concept for improving airspace productivity is time-based control of aircraft. Research to date has focused primarily on the development of time-based flight management systems and Air Traffic Control operational procedures. Flight operations may, however, require special onboard guidance in order to satisfy the Air Traffic Control imposed time constraints. The results are presented of a simulation study aimed at evaluating several time-based guidance concepts in terms of tracking performance, pilot workload, and subjective preference. The guidance concepts tested varied in complexity from simple digital time-error feedback to an advanced time-referenced-energy guidance scheme.

Vicroy, Dan D.↗
NASA NTRS2023

Monitoring Airspace Complexity and Determining Contributing Factors

The national airspace has evolved over many years to accommodate increased traffic demand while simultaneously maintaining air travel as one of the safest forms of transportation. One of the reasons for this success is the ability of the air traffic control system and the operators to adapt and accommodate to situations that routinely disrupt normal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators’ ability to control. These factors can lead to states where automation is unable to properly handle these issues, and therefore air traffic controllers and pilots have to intervene — ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions, complexity increases. This is because, under these conditions humans are required to make tactical decisions in response to external factors. This results in a departure from the original strategic plan where operations would be more efficiently managed. Human operators manage airspace complexity under rigid regulations but in a constantly changing environment. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. Some prior studies devised airspace complexity metrics in commercial aviation and related these metrics to controller workload. The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic — including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to ours that identifies such contributing factors or precursor patterns.

Precursor↗
NASA NTRS2002

CATS-based Agents That Err

This report describes preliminary research on intelligent agents that make errors. Such agents are crucial to the development of novel agent-based techniques for assessing system safety. The agents extend an agent architecture derived from the Crew Activity Tracking System that has been used as the basis for air traffic controller agents. The report first reviews several error taxonomies. Next, it presents an overview of the air traffic controller agents, then details several mechanisms for causing the agents to err in realistic ways. The report presents a performance assessment of the error-generating agents, and identifies directions for further research. The research was supported by the System-Wide Accident Prevention element of the FAA/NASA Aviation Safety Program.

Callantine, Todd J.↗
NASA NTRS1999

The Effects of Shared Information on Pilot-Controller Situation Awareness And Re-Route Negotiation

The effect of shared information is assessed in terms of pilot-controller negotiating behavior and shared situation awareness. Pilot goals and situation awareness requirements are developed and compared against those of air traffic controllers to identify areas of common and competing interest. An exploratory, part-task simulator experiment is described which evaluates the extent to which shared information may lead pilots and controllers to cooperate or compete when negotiating route amendments. Results are presented which indicate that shared information enhances situation awareness and can engender more collaborative interaction between pilots and air traffic controllers. Furthermore, the value of providing controllers with a good-quality weather overlay on their plan view displays is demonstrated. Observed improvements in situation awareness and separation assurance are discussed.

Farley, Todd C.↗
NASA NTRS2002

Air Ground Integration Study

A simulation was conducted to examine the effect of shared air/ground authority when each is equipped with enhanced traffic- and conflict-alerting systems. The potential benefits of an advanced air traffic management (ATM) concept referred to as "free flight" include improved safety through enhanced conflict detection and resolution capabilities, increased flight-operations management, and better decision-making tools for air traffic controllers and flight crews. One element of the free-flight concept suggests shifting aircraft separation responsibility from air traffic controllers to flight crews, thereby creating an environment with "shared-separation" authority. During FY00. NASA, the Federal Aviation Administration (FAA), and the Volpe National Transportation Systems Center completed the first integrated, high-fidelity, real-time, human-in-the-loop simulation.

Lozito, Sandy↗
NASA NTRS1972

Broadcast control of air traffic

The development of a system of broadcast control for improved flight safety and air traffic control is discussed. The system provides a balance of equality between improved cockpit guidance and control capability and ground control in order to provide the pilot with a greater degree of participation. The manner in which the system is operated and the equipment required for safe operation are examined.

Litchford, G. B.↗
NASA NTRS1995

Wake-Vortex Separation Distances when Flight-Path Corridors are Constrained

Since the vortex wakes of large transport aircraft can pose a hazard to smaller following aircraft during landing and takeoff operations, certain separation guidelines are followed while aircraft are in the approach and departure corridors at airports. These guidelines reduce the capacity of airports because the separation distances are larger than other airport factors require. This paper studies the effect that a decrease in the size of the cross-section of the flight corridors for air traffic control would have on the wake-vortex separation guidelines; e.g., when the Global Positioning System (GPS) is implemented for air traffic control. It is first shown why smaller flight corridors permit reduced spacings at airports. Several arrangements of smaller flight corridors are then presented to illustrate how differing atmospheric and airport conditions can be accommodated. These considerations indicate that a reduction is then permissible in the wake-vortex spacings while still retaining the same or an improved degree of safety.

Rossow, Vernon J.↗
NASA NTRS1989

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗
NASA NTRS1989

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗
NASA NTRS2004

Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds

A computationally efficient algorithm for minimizing the flight time of an aircraft in a variable wind field has been invented. The algorithm, referred to as Neighboring Optimal Wind Routing (NOWR), is based upon neighboring-optimal-control (NOC) concepts and achieves minimum-time paths by adjusting aircraft heading according to wind conditions at an arbitrary number of wind measurement points along the flight route. The NOWR algorithm may either be used in a fast-time mode to compute minimum- time routes prior to flight, or may be used in a feedback mode to adjust aircraft heading in real-time. By traveling minimum-time routes instead of direct great-circle (direct) routes, flights across the United States can save an average of about 7 minutes, and as much as one hour of flight time during periods of strong jet-stream winds. The neighboring optimal routes computed via the NOWR technique have been shown to be within 1.5 percent of the absolute minimum-time routes for flights across the continental United States. On a typical 450-MHz Sun Ultra workstation, the NOWR algorithm produces complete minimum-time routes in less than 40 milliseconds. This corresponds to a rate of 25 optimal routes per second. The closest comparable optimization technique runs approximately 10 times slower. Airlines currently use various trial-and-error search techniques to determine which of a set of commonly traveled routes will minimize flight time. These algorithms are too computationally expensive for use in real-time systems, or in systems where many optimal routes need to be computed in a short amount of time. Instead of operating in real-time, airlines will typically plan a trajectory several hours in advance using wind forecasts. If winds change significantly from forecasts, the resulting flights will no longer be minimum-time. The need for a computationally efficient wind-optimal routing algorithm is even greater in the case of new air-traffic-control automation concepts. For air-traffic-control automation, thousands of wind-optimal routes may need to be computed and checked for conflicts in just a few minutes. These factors motivated the need for a more efficient wind-optimal routing algorithm.

Jardin, Matthew R.↗
NASA NTRS2017

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.↗
NASA NTRS1965

Introduction to SST-ATC Study Program

The purpose of this brief introduction is to define the objectives of the program and to describe the manner in which it is being pursued. The study is directed toward problems anticipated with the introduction of the supersonic transport into the air-traffic-control system. The primary objectives are: (1) The determination of the effects of the SST (supersonic transport) on requirements of the ATC (air traffic control) system. (2) The determination of the effects of the ATC system on requirements for the SST design and for its equipment. Basically, the program is a simulation effort involving equipment both at Langley and at the NAFEC facility. A block diagram illustrating the manner in which the equipment of the two agencies has been integrated to carry out the program. The Langley equipment includes a cockpit, or flight compartment that is generally representative of transport equipment, and an analog computer for solving the six-degree-of-freedom motion equations for an aircraft having the characteristics of the SST design under study.

Toll, Thomas A.↗