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All sourcesNASA NTRSDOE OSTI
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 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 NTRS2006

Relationship between Weather, Traffic and Delay Based on Empirical Methods

The steady rise in demand for air transportation over the years has put much emphasis on the need for sophisticated air traffic flow management (TFM) within the National Airspace System (NAS). The NAS refers to hardware, software and people, including runways, radars, networks, FAA, airlines, etc., involved in air traffic management (ATM) in the US. One of the metrics that has been used to assess the performance of NAS is the actual delays provided through FAA's Air Traffic Operations Network (OPSNET). The OPSNET delay data includes those reportable delays, i.e. delays of 15 minutes or more experienced by Instrument Flight Rule (IFR) flights, submitted by the FAA facilities. These OPSNET delays are caused by the application of TFM initiatives in response to, for instance, weather conditions, increased traffic volume, equipment outages, airline operations, and runway conditions. TFM initiatives such as, ground stops, ground delay programs, rerouting, airborne holding, and miles-in-trail restrictions, are actions which are needed to control the air traffic demand to mitigate the demand-capacity imbalance due to the reduction in capacity. Consequently, TFM initiatives result in NAS delays. Of all the causes, weather has been identified as the most important causal factor for NAS delays. Therefore, in order to accurately assess the NAS performance, it has become necessary to create a baseline for NAS performance and establish a model which characterizes the relation between weather and NAS delays.

Sridhar, Banavar↗
NASA NTRS2020

Investigating Effects of Controlled Flights through Fast-Time Simulation

Departure flights at major U.S. airports are often subject to Traffic Management Initiatives to mitigate congestion and delay due to demand-capacity imbalances. These controlled flights can lead to inefficiency and delay on the airport surface. The integrated arrival, departure, and surface traffic management capabilities developed by NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. This paper evaluates the impacts of controlled flights on airport performance and assesses the ATD-2 benefits of pushback hold advisories for both controlled and non-controlled flights using fast-time simulation for Charlotte Douglas International Airport.

controlled flight↗
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 NTRS2018

Designing Graceful Degradation into Complex Systems: The Interaction Between Causes of Degradation and the Association with Degradation Prevention and Recovery

System resilience is critical to safety in air traffic control. An important element of maintaining resilience is the ability of systems to degrade gracefully. Of the available graceful degradation research, a majority of studies have focused primarily on technological causes of degradation only, limiting an ecologically valid understanding of the causes of degradation in air traffic control, and the preventative and mitigative strategies that enable graceful degradation. The current study aimed to address this research gap by investigating causes of degradation in air traffic control (ATC) across the broad categories of technology, the environment, and the human operator, and the potential interactions between these causes. 12 retired controllers (ATCOs - Air Traffic Control Officers) participated in semi-structured interviews focused on previous experience of causes of degradation and mitigation strategies. Findings provide an understanding of causation of degradation in air traffic control, and the prevention and mitigation strategies that moderate the relationship between cause and system effect. Findings confirmed that causes appear to interact to create compound, multiple effects on overall system performance. Findings also revealed prevention and mitigation strategies utilized to moderate the effect of the cause on the system. In order to gain an ecologically valid understanding of the causes of degradation, and effective prevention or mitigation strategies, causes from multiple categories, and the interactions between them, must be identified. Findings have implications for designers of future air traffic control systems to ensure the ability of the system to gracefully degrade, as well as risk assessment and system validation processes.

Graceful Degradation↗
NASA NTRS2011

Traffic Flow Management Wrap-Up

Traffic Flow Management involves the scheduling and routing of air traffic subject to airport and airspace capacity constraints, and the efficient use of available airspace. Significant challenges in this area include: (1) weather integration and forecasting, (2) accounting for user preferences in the Traffic Flow Management decision making process, and (3) understanding and mitigating the environmental impacts of air traffic on the environment. To address these challenges, researchers in the Traffic Flow Management area are developing modeling, simulation and optimization techniques to route and schedule air traffic flights and flows while accommodating user preferences, accounting for system uncertainties and considering the environmental impacts of aviation. This presentation will highlight some of the major challenges facing researchers in this domain, while also showcasing recent innovations designed to address these challenges.

Grabbe, Shon↗
NASA NTRS2018

Designing Graceful Degradation into Complex Systems: The Interaction Between Causes of Degradation and the Association with Degradation Prevention and Recovery

System resilience is critical to safety in air traffic control. An important element of maintaining resilience is the ability of systems to degrade gracefully. Of the available graceful degradation research, a majority of studies have focused primarily on technological causes of degradation only, limiting an ecologically valid understanding of the causes of degradation in air traffic control, and the preventative and mitigative strategies that enable graceful degradation. The current study aimed to address this research gap by investigating causes of degradation in air traffic control across the broad categories of technology, the environment, and the human operator, and the potential interactions between these causes. 12 retired controllers participated in semi-structured interviews focused on previous experience of causes of degradation and mitigation strategies. Findings provide an understanding of causation of degradation in air traffic control, and the prevention and mitigation strategies that moderate the relationship between cause and system effect. Findings confirmed that causes appear to interact to create compound, multiple effects on overall system performance. Findings also revealed prevention and mitigation strategies utilized to moderate the effect of the cause on the system. In order to gain an ecologically valid understanding of the causes of degradation, and effective prevention or mitigation strategies, causes from multiple categories, and the interactions between them, must be identified. Findings have implications for designers of future air traffic control systems to ensure the ability of the system to gracefully degrade, as well as risk assessment and system validation processes.

human performance↗
NASA NTRS2019

An Initial Analysis of Automating Conjunction Assessment and Collision Avoidance Planning in Space Traffic Management

We introduce a framework that automates the process of assessing potential satellite conjunctions in space, and generating collision avoidance maneuvers to support mitigation efforts within a novel space traffic management (STM) architecture. A software implementation of the framework was developed in a MATLAB-STK integrated environment, however, the concept and framework is agnostic to the language or environment. The software pulls from existing catalogs of spaceborne objects and ingests user-defined parameters to produce conjunction data, which could potentially aid collision avoidance planning in the STM architecture. The utility of the software in maneuver planning and exploring a performance-based tradespace of actions is demonstrated using three example cases: one-to-one conjunction, one-versus-four conjunctions, and a near head-on collision. The framework also provides a test-bed for the use of application programming interfaces (APIs) to demonstrate machine-to-machine communication between entities in our proposed STM architecture. Results from this software implementation are expected to aid distributed decision-making among various stakeholders, and inform efficient, autonomous, structured but flexible concept of operations within STM.

Space Systems Engineering↗
NASA NTRS2014

Clustering Days with Similar Airport Weather Conditions

On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between the aircraft demand and the weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traffic data to identify patterns and past decisions that can ultimately inform day-of-operations decision-making. More specifically, this study identified similar weather impacted days at select U.S. airports, and analyzed the traffic management initiatives implemented on these representative days. The identification of the similar days was accomplished by applying a decision tree algorithm to the hourly Localized Aviation Model Output Statistics Program observations and the arrival delays for Newark Liberty International Airport. The branches from the trained decision tree were subsequently pruned to identify four weather conditions that resulted in medium to high delays for the arrivals scheduled to Newark in 2012. Using these weather conditions, four, daily airport-level Weather Impacted Traffic Index values were calculated using the Localized Aviation Model Output Statistics Program observations and the 2012 scheduled arrival counts from the FAAs Aviation System Performance Metric system. The four, daily Weather Impacted Traffic Index values for 2012 were subsequently clustered using an Expectation Maximization clustering algorithm, and nine unique types of weather days at Newark were identified. By far the most prominent type of day at Newark was a day associated with relatively good weather conditions, where there was little convective activity, winds were low, ceilings and visibility were high and there was little precipitation. Moderate levels of convective activity characterized the next most prominent type of day. Days with persistently high winds or low ceiling and visibility levels were relatively rare in 2012. Lastly, the frequency at which Ground Delay Programs, Ground Stops and Miles-in-Trail restrictions were implemented on each of the typical types of days at Newark were analyzed. Based on the results, it does appear as if the usage of Miles-in-Trail, Ground Delay Program and Ground Stop restrictions correlates well with the severity of the weather associated with each unique type of weather impacted day at Newark. Furthermore, the results demonstrate that it is feasible to use historical weather and air traffic archives to provide guidance on the types of traffic management restrictions to implement in response to the weather conditions impacting an airport.

traffic flow management↗
NASA NTRS2014

Clustering Days with Similar Airport Weather Conditions

On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between the aircraft demand and the weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traffic data to identify patterns and past decisions that can ultimately inform day-of-operations decision-making. More specifically, this study identified similar weather impacted days at select U.S. airports, and analyzed the traffic management initiatives implemented on these representative days. The identification of the similar days was accomplished by applying a decision tree algorithm to the hourly Localized Aviation Model Output Statistics Program observations and the arrival delays for Newark Liberty International Airport. The branches from the trained decision tree were subsequently pruned to identify four weather conditions that resulted in medium to high delays for the arrivals scheduled to Newark in 2012. Using these weather conditions, four, daily airport-level Weather Impacted Traffic Index values were calculated using the Localized Aviation Model Output Statistics Program observations and the 2012 scheduled arrival counts from the FAAs Aviation System Performance Metric system. The four, daily Weather Impacted Traffic Index values for 2012 were subsequently clustered using an Expectation Maximization clustering algorithm, and nine unique types of weather days at Newark were identified. By far the most prominent type of day at Newark was a day associated with relatively good weather conditions, where there was little convective activity, winds were low, ceilings and visibility were high and there was little precipitation. Moderate levels of convective activity characterized the next most prominent type of day. Days with persistently high winds or low ceiling and visibility levels were relatively rare in 2012. Lastly, the frequency at which Ground Delay Programs, Ground Stops and Miles-in-Trail restrictions were implemented on each of the typical types of days at Newark were analyzed. Based on the results, it does appear as if the usage of Miles-in-Trail, Ground Delay Program and Ground Stop restrictions correlates well with the severity of the weather associated with each unique type of weather impacted day at Newark. Furthermore, the results demonstrate that it is feasible to use historical weather and air traffic archives to provide guidance on the types of traffic management restrictions to implement in response to the weather conditions impacting an airport.

weather↗
NASA NTRS2010

Predicting Airspace Capacity Impacts Using the Consolidated Storm Prediction for Aviation

Convective weather is currently the largest contributor to air traffic delays in the United States. In order to make effective traffic flow management decisions to mitigate these delays, weather forecasts must be made as early and as accurately as possible. A forecast product that could be used to mitigate convective weather impacts is the Consolidated Storm Prediction for Aviation. This product provides forecasts of cloud water content and convective top heights at 0- to 8-hour look-ahead times. The objective of this study was to examine a method of predicting the impact of convective weather on air traffic sector capacities using these forecasts. Polygons representing forecast convective weather were overlaid at multiple flight levels on a sector map to calculate the fraction of each sector covered by weather. The fractional volume coverage was used as the primary metric to determine convection s impact on sectors. Results reveal that the forecasts can be used to predict the probability and magnitude of weather impacts on sector capacity up to eight hours in advance.

Russell, Carl↗
NASA NTRS2013

Modeling Weather Impact on Airport Arrival Miles-in-Trail Restrictions

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-intrail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011. Then, machine-learning methods for predicting (1) situations in which MIT restrictions for ATL arrivals are implemented under low demand scenarios, and (2) days in which a large number of MIT restrictions are required to properly manage and control ATL arrivals are presented. More specifically, these predictions were accomplished by using an ensemble of decision trees with Bootstrap aggregation (BDT) and supervised machine learning was used to train the BDT binary classification models. The models were subsequently validated using data cross validation methods. When predicting the occurrence of arrival MIT restrictions under low demand situations, the model was able to achieve over all accuracy rates ranging from 84% to 90%, with false alarm ratios ranging from 10% to 15%. In the second set of studies designed to predict days on which a high number of MIT restrictions were required, overall accuracy rates of 80% were achieved with false alarm ratios of 20%. Overall, the predictions proposed by the model give better MIT usage information than what has been currently provided under current day operations. Traffic flow managers can use these predictions to identify potential MIT restrictions to eliminate (e.g., those occurring during low arrival demand periods), and to determine the days in which a significant number of restrictions may be required

Operation↗
NASA NTRSDate not supplied

Developing a Cybersecurity Architecture for Extensible Traffic Management (xTM)

This paper explores the development of a cybersecurity architecture tailored for Extensible Traffic Management (xTM) to address emerging challenges in managing diverse aerial vehicles within the National Airspace System (NAS). Driven by technological advances and the rise of uncrewed aerial systems (UAS), urban air mobility (UAM), and high-altitude traffic (ETM), the NAS is undergoing a paradigm shift. Traditional air traffic management, reliant on traditional Federal Aviation Administration (FAA) control, will give way to decentralized coordination among autonomous and semi-autonomous systems. The proposed xTM Security Architecture, designed as a high-level framework, focuses on ensuring the confidentiality, integrity, and availability of data and operations in this evolving ecosystem. Utilizing threat modeling, the research identifies potential risks across key flight phases, operations and use cases to offer security control recommendations. Key objectives include analyzing interactions between novel airspace entrants and existing NAS traffic, cataloging vulnerabilities, and developing mitigative strategies to ensure safety, operational stability, and secure data exchanges. This research lays the groundwork for regulatory and industry adaptation, providing critical insights into managing cybersecurity risks in this complex, multi-domain environment.

UAM↗
NASA NTRS1990

ACTS Multibeam Communications Package - Technology for the 1990S

To maintain its competitive position in the 1990s, satellite communications must evolve to provide new services and to reduce the costs of supplying existing services. NASA's Advanced Communications Technology Satellite (ACTS) program is directed toward developing the technology base that will support this evolution. The ACTS communications payload is optimized for digital communications using a time-division multiple access format. Scanning spot-beam antennas provide high-performance on-demand service to the earth communication stations. On-board processing and switching allow full connectivity in a single-hop network architecture. ACTS employs Ka-band (30/20 GHz) links for communications traffic and includes techniques for mitigating rain fades. Scheduled to be launched by a Space Shuttle in 1992, ACTS will provide in-orbit technology verification and support experimental communications networks for up to four years.

Graebner, John C.↗
NASA NTRS1992

ACTS Multibeam Communications Package - Description and Performance Characterization

To maintain its competitive position in the 1990s, satellite communications must evolve to provide new services and to reduce the costs of supplying existing services. NASA's Advanced Communications Technology Satellite (ACTS) program is directed toward developing the technology base that will support this evolution. The ACTS communications payload is optimized for digital communications using a time-division multiple-access format. Scanning spot-beam antennas provide high-performance, on-demand service to communications earth stations. On-board processing and switching allow full connectivity in a single-hop network architecture. ACTS employs Ka-Band (30/20 GHz) links for communications traffic and includes techniques for mitigating rain fades. The prelaunch test program has verified that all critical payload performance requirements have been realized, including G/T, EIRP, beam coverage, AM/AM, AM/PM, and BER vs. E(b)/N(o). Scheduled to be launched by a Space Shuttle in 1993, ACTS will provide in-orbit technology verification and support experimental communications networks for up to four years.

Cashman, William F.↗
NASA NTRS2016

An Integrated Gate Turnaround Management Concept Leveraging Big Data Analytics for NAS Performance Improvements

"Gate Turnaround" plays a key role in the National Air Space (NAS) gate-to-gate performance by receiving aircraft when they reach their destination airport, and delivering aircraft into the NAS upon departing from the gate and subsequent takeoff. The time spent at the gate in meeting the planned departure time is influenced by many factors and often with considerable uncertainties. Uncertainties such as weather, early or late arrivals, disembarking and boarding passengers, unloading/reloading cargo, aircraft logistics/maintenance services and ground handling, traffic in ramp and movement areas for taxi-in and taxi-out, and departure queue management for takeoff are likely encountered on the daily basis. The Integrated Gate Turnaround Management (IGTM) concept is leveraging relevant historical data to support optimization of the gate operations, which include arrival, at the gate, departure based on constraints (e.g., available gates at the arrival, ground crew and equipment for the gate turnaround, and over capacity demand upon departure), and collaborative decision-making. The IGTM concept provides effective information services and decision tools to the stakeholders, such as airline dispatchers, gate agents, airport operators, ramp controllers, and air traffic control (ATC) traffic managers and ground controllers to mitigate uncertainties arising from both nominal and off-nominal airport gate operations. IGTM will provide NAS stakeholders customized decision making tools through a User Interface (UI) by leveraging historical data (Big Data), net-enabled Air Traffic Management (ATM) live data, and analytics according to dependencies among NAS parameters for the stakeholders to manage and optimize the NAS performance in the gate turnaround domain. The application will give stakeholders predictable results based on the past and current NAS performance according to selected decision trees through the UI. The predictable results are generated based on analysis of the unique airport attributes (e.g., runway, taxiway, terminal, and gate configurations and tenants), and combined statistics from past data and live data based on a specific set of ATM concept-of-operations (ConOps) and operational parameters via systems analysis using an analytic network learning model. The IGTM tool will then bound the uncertainties that arise from nominal and off-nominal operational conditions with direct assessment of the gate turnaround status and the impact of a certain operational decision on the NAS performance, and provide a set of recommended actions to optimize the NAS performance by allowing stakeholders to take mitigation actions to reduce uncertainty and time deviation of planned operational events. An IGTM prototype was developed at NASA Ames Simulation Laboratories (SimLabs) to demonstrate the benefits and applicability of the concept. A data network, using the System Wide Information Management (SWIM)-like messaging application using the ActiveMQ message service, was connected to the simulated data warehouse, scheduled flight plans, a fast-time airport simulator, and a graphic UI. A fast-time simulation was integrated with the data warehouse or Big Data/Analytics (BAI), scheduled flight plans from Aeronautical Operational Control AOC, IGTM Controller, and a UI via a SWIM-like data messaging network using the ActiveMQ message service, illustrated in Figure 1, to demonstrate selected use-cases showing the benefits of the IGTM concept on the NAS performance.

Efficent ATM systems↗