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At least 199 records · Page 11

Overview: Spot and Runway Departure Advisor (SARDA)

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for DallasFt. Worth International Airport. The presentation also explains the latest status of NASA's current surface research through a collaboration with an airline partner. The presentation concludes with a discussion on other on-going as well as future surface research.

decision support tool↗

Spot and Departure Runway Advisor (SARDA)

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for Dallas-Ft. Worth International Airport. The presentation also discusses the latest status of NASA's current surface research through a collaboration with an airline partner, where a tool is developed for airline ramp operators to assist departure pushback operations.

Departure Schedule↗

Inadequacies of conventional traffic forecasting in determining the demand for new aircraft

Decisions concerning the selection of new aircraft must take into account the expected volume and character of air traffic in particular future markets. An investigation is, therefore, conducted regarding the currently available approaches for obtaining estimates of air traffic growth. Essentially, air traffic forecasting consists in studying past air traffic growth patterns, attempting to determine what may cause them to change, relating them where possible to such determinants or to other series whose changes they follow in some predictable fashion. Attention is given to the short-shelf life of conventional air traffic forecasts, the observation that most forecasts reflect recent experience, factors which may partially offset the inadequacies of air traffic forecasting technology, the limitations of conventional forecasting, and research useful in identifying a range of future scenarios.

Gorham, J. E.↗

Concept of Operations for Management by Trajectory

This document describes Management by Trajectory (MBT), a concept for future air traffic management (ATM) in which every flight operates in accordance with a four-dimensional trajectory (4DT) that is negotiated between the airspace user and the Federal Aviation Administration (FAA) to respect the airspace user's goals while complying with National Airspace System (NAS) constraints. In the present-day NAS, the ATM system attempts to predict the trajectory for each flight based on the approved flight plan and scheduled or controlled departure time. However, once the aircraft starts to move, controllers tactically manage the aircraft to implement traffic management restrictions, separate otherwise conflicting aircraft, and address arising NAS constraints. Tactical controller actions are not directly communicated to the automation systems or other stakeholders. Furthermore, the initial trajectory prediction does not anticipate these disruptions or how they will impact the flight. Consequently, and compounded by gaps in required data and models, trajectory predictions are less accurate than possible, which affects Traffic Flow Management (TFM) performance. A cornerstone of the MBT concept is that all air vehicles have, at all times, an assigned 4DT from their current state to their destination. These assigned trajectories consist of trajectory constraints and descriptions. Pilots and air traffic controllers, with the aid of automation, operate the aircraft to comply with the assigned trajectory, unless first negotiating a revision. Equipped aircraft have substantial responsibility for complying with the assigned trajectory without controller intervention. To maximize the operational flexibility available to the airspace user, the assigned trajectory only imposes trajectory constraints as required to achieve the ATM goals of NAS constraint compliance and aircraft separation. Trajectory descriptions are added to the assigned trajectory to ensure sufficient predictability. To further improve trajectory prediction accuracy, airspace users supplement the assigned trajectory by broadcasting intent information and updating it as necessary. Air vehicle intent is a more detailed description of the airspace user's plan for how the flight will fly the assigned trajectory. Air vehicle intent can change freely, without negotiation, as long as it remains in compliance with the assigned trajectory. Aircraft assigned trajectories, air vehicle intent, and predicted trajectories are shared, creating a common view among stakeholders. A NAS Constraint Service gathers and publishes information about all known NAS constraints, enabling airspace users to be informed participants in trajectory negotiation. Trajectory constraints in the assigned trajectory are mapped to NAS constraints to facilitate identifying which aircraft are affected when NAS constraints change. To support efficient trajectory negotiation, all aircraft provide current information about air vehicle capabilities. Assigned trajectories are constructed to satisfy all known NAS constraints, improving trajectory stability and predictability. Uncertainty and disruptions are handled by modifying the assigned trajectory as far in advance as possible. By proactively negotiating changes to the assigned trajectory, rather than relying on controller-selected tactical actions such as vectors to resolve traffic conflicts or implement miles-in-trail restrictions, MBT keeps aircraft on closed trajectories that are fully known to all stakeholders. Since reactive air traffic control actions cannot be predicted in advance, the downstream trajectory cannot be accurately predicted until they happen. Reliable trajectory predictions allow the system to identify needed modifications to trajectories further in advance, where they can be negotiated and communicated as amendments (i.e., additional or altered trajectory constraints) to the assigned trajectory. Decision Support Tools (DSTs) aid controllers in rapidly defining and communicating closed trajectories to the aircraft and support all stakeholders in trajectory negotiation. Anticipated MBT benefit mechanisms include more accurate trajectory predictions, improved ATM performance and robustness to off-nominal conditions, increased flexibility and operational efficiency, reduced impediments to emerging classes of airspace users accessing NAS resources, reduced environmental impacts, and enhanced safety.

ConOps↗

Performance of an Automated System for Control of Traffic in Terminal Airspace

This paper examines the performance of a system that performs automated conflict resolution and arrival scheduling for aircraft in the terminal airspace around major airports. Such a system has the potential to perform separation assurance and arrival sequencing tasks that are currently handled manually by human controllers. The performance of the system is tested against several simulated traffic scenarios that are characterized by the rate at which air traffic is metered into the terminal airspace. For each traffic scenario, the levels of performance that are examined include: number of conflicts predicted to occur, types of resolution maneuver used to resolve predicted conflicts, and the amount of delay for all flights. The simulation results indicate that the percentage of arrivals that required a maneuver that changes the flight's horizontal route ranged between 11% and 15% in all traffic scenarios. That finding has certain implications if this automated system were to be implemented simply as a decision support tool. It is also found that arrival delay due to purely wake vortex separation requirements on final approach constituted only between 29% and 35% of total arrival delay, while the remaining major portion of it is mainly due to delay back propagation effects.

air traffic control↗

Initial Analysis of and Predictive Model Development for Weather Reroute Advisory Use

In response to severe weather conditions, traffic management coordinators (TMCs) reroute air traffic around regions of airspace affected by the severe weather. Presently, acceptable reroutes are specified by issuing reroute advisories. Advisories, based on reroutes published in the National Severe Weather Playbook, consist of several routes describing routing options. These reroutes are selected by TMCs based on their understanding of weather conditions and their previous experience dealing with similar weather conditions. Providing recommendations and analysis of available reroute options could assist the TMCs in making rerouting decisions. While reroute advisories have historically been based on Playbook plays, plays are frequently modified or combined to generate an advisory. Thus, it is natural to present rerouting suggestions to TMCs as modified Playbook plays. The challenge here is to compare advisory subroutes and play subroutes in a meaningful way in order to map advisories back to the Playbook plays upon which they may have been based. In this work, several subroute comparison metrics are presented and discussed. One of these metrics is then used to match advisories to Playbook plays. With the development and implementation of NextGen technologies, there is currently a trend of moving away from the pre-defined Playbook plays (and related advisories) in favor of a more precise specification of trajectories using GPS based navigation tools, such as area navigation (RNAV). Moving towards ubiquitous use of RNAV routes, the objective of rerouting flights will be met with more precisely specified and accurately flown RNAV routes. In the final version of this paper, significant RNAV routes will be identified by finding RNAV routes that are flown frequently. This will require a trajectory comparison technique to compare actually flown flight tracks to specified RNAV routes. The metrics developed here will be used or modified for this task.

weather required reroutes↗

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↗

The dissociation between subjective workload and performance A multiple resource approach

A theory of the dissociation between subjective measures of mental workload and performance is described. The theory proposes that subjective measures are heavily driven by the number of tasks or task elements that a subject must perform concurrently. However they are relatively less sensitive to whether these tasks compete for common or separate resources, and to the difficulty of a single task, particularly if this difficulty is related to response factors. Performance, on the other hand, is particularly influenced by single task difficulty of both a perceptual and response nature and by resource competition between tasks. A set of three experiments are described to examine the dissociation between subjective difficulty measures and performance. These experiments employ different combinations of three tasks: tracking, memory search, and a simulated air traffic control problem. The results supported all forms of dissociation predicted by the theory and the implications of results to workload measurement are discussed.

Wickens, C. D.↗

Modeling and Performance Simulation of the Mass Storage Network Environment

This paper describes the application of modeling and simulation in evaluating and predicting the performance of the mass storage network environment. Network traffic is generated to mimic the realistic pattern of file transfer, electronic mail, and web browsing. The behavior and performance of the mass storage network and a typical client-server Local Area Network (LAN) are investigated by modeling and simulation. Performance characteristics in throughput and delay demonstrate the important role of modeling and simulation in network engineering and capacity planning.

Kim, Chan M.↗

Analysis of a Dynamic Multi-Track Airway Concept for Air Traffic Management

The Dynamic Multi-track Airways (DMA) Concept for Air Traffic Management (ATM) proposes a network of high-altitude airways constructed of multiple, closely spaced, parallel tracks designed to increase en-route capacity in high-demand airspace corridors. Segregated from non-airway operations, these multi-track airways establish high-priority traffic flow corridors along optimal routes between major terminal areas throughout the National Airspace System (NAS). Air traffic controllers transition aircraft equipped for DMA operations to DMA entry points, the aircraft use autonomous control of airspeed to fly the continuous-airspace airway and achieve an economic benefit, and controllers then transition the aircraft from the DMA exit to the terminal area. Aircraft authority within the DMA includes responsibility for spacing and/or separation from other DMA aircraft. The DMA controller is responsible for coordinating the entry and exit of traffic to and from the DMA and for traffic flow management (TFM), including adjusting DMA routing on a daily basis to account for predicted weather and wind patterns and re-routing DMAs in real time to accommodate unpredicted weather changes. However, the DMA controller is not responsible for monitoring the DMA for traffic separation. This report defines the mature state concept, explores its feasibility and performance, and identifies potential benefits. The report also discusses (a) an analysis of a single DMA, which was modeled within the NAS to assess capacity and determine the impact of a single DMA on regional sector loads and conflict potential; (b) a demand analysis, which was conducted to determine likely city-pair candidates for a nationwide DMA network and to determine the expected demand fraction; (c) two track configurations, which were modeled and analyzed for their operational characteristic; (d) software-prototype airborne capabilities developed for DMA operations research; (e) a feasibility analysis of key attributes in the concept design; (f) a near-term, transitional application of the DMA concept as a proving ground for new airborne technologies; and (g) conclusions. The analysis indicates that the operational feasibility of a national DMA network faces significant challenges, especially for interactions between DMAs and between DMA and non-DMA traffic. Provided these issues are resolved, sectors near DMAs could experience significant local capacity benefits.

Wing, David J.↗

Automation for Accommodating Fuel-Efficient Descents in Constrained Airspace

Continuous descents at low engine power are desired to reduce fuel consumption, emissions and noise during arrival operations. The challenge is to allow airplanes to fly these types of efficient descents without interruption during busy traffic conditions. During busy conditions today, airplanes are commonly forced to fly inefficient, step-down descents as airtraffic controllers work to ensure separation and maximize throughput. NASA in collaboration with government and industry partners is developing new automation to help controllers accommodate continuous descents in the presence of complex traffic and airspace constraints. This automation relies on accurate trajectory predictions to compute strategic maneuver advisories. The talk will describe the concept behind this new automation and provide an overview of the simulations and flight testing used to develop and refine its underlying technology.

Coopenbarger, Richard A.↗

Spot and Runway Departure Advisor (SARDA)

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation also discusses the latest status of NASA's current surface research through a collaboration with an airline partner, where a tool is developed for airline ramp operators to assist departure pushback operations. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for Dallas-Ft. Worth International Airport and 2014 for Charlotte airport ramp tower.

surface management↗

Human Factors in Aeronautics at NASA

This is a briefing to a regularly meeting DoD group called the Human Systems Community of Interest: Mission Effectiveness. I was asked to address human factors in aeronautics at NASA. (Exploration (space) human factors has apparently already been covered.) The briefing describes human factors organizations at NASA Ames and Langley. It then summarizes some aeronautics tasks that involve the application of human factors in the development of specific tools and capabilities. The tasks covered include aircrew checklists, dispatch operations, Playbook, Dynamic Weather Routes, Traffic Aware Strategic Aircrew Requests, and Airplane State Awareness and Prediction Technologies. I mention that most of our aeronautics work involves human factors as embedded in development tasks rather than basic research.

NASA↗

NASA Research to Support the Airlines

This is a PowerPoint presentation that was a review of NASA projects that support airline operations. It covered NASA tasks that have provided new tools to the airline operations center and flight deck including the Flight Awareness Collaboration Tool, Dynamic Weather Routes, Traffic Aware Strategic Aircrew Requests, and Airplane State Awareness and Prediction Technologies. This material is very similar to other previously approved presentations with the same title.

NASA↗

Prediction of Noise-Power-Distance Data for Urban Air Mobility Vehicles

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise-power-distance (NPD) data for use within AEDT. One utilizes the AEDT fixed-wing aircraft modeling approach and the other utilizes the AEDT rotary-wing aircraft modeling approach.

noise-power-distance↗

Departure Approval Request Compliance Effects on Overhead Stream Insertion

Integrated Arrival-Departure-Surface (IADS) air traffic management relies on information sharing and integration between automation systems for efficiency, predictability, and throughput improvements throughout the National Airspace System (NAS). The NASA Airspace Technology Demonstration 2 (ATD-2) project supports this effort by integrating SWIM (System Wide Information Management) information and evaluating and refining potential TFDM (Terminal Flight Data Manager) functionality in a surface traffic management system fielded at Charlotte-Douglas International Airport (CLT). Among the IADS areas under study during ATD-2 is the use of electronically negotiated departure times for efficiently inserting flights into overhead traffic streams. Stream-insertion accuracy is important for reducing excessive vectoring that negatively impacts the NAS by increasing controller workload along with aircraft fuel burn and emissions. Departure-time approval requests (APREQs) provide center-approved departure times to allow for smooth stream insertion. In this presentation, TBFM (Time-Based Flow Management) and ATD-2 flight summary data are used to empirically show that APREQ compliance leads to improved stream insertion.

Overhead-Stream Insertion↗

Analysis of Runway Incursion Data

A statistical analysis of runway incursion (RI) events was conducted to ascertain relevance to the top ten challenges of the National Aeronautics and Space Administration Aviation Safety Program (AvSP). The information contained in the RI database was found to contain data that may be relevant to several of the AvSP top ten challenges. When combined with other data from the FAA documenting air traffic volume from calendar year 2000 through 2011, the structure of a predictive model emerges that can be used to forecast the frequency of RI events at various airports for various classes of aircraft and under various environmental conditions.

Runway incursions↗

TPSAS-NF1676L-17064-DND

A statistical analysis of runway incursion (RI) events was conducted to ascertain relevance to the top ten challenges of the National Aeronautics and Space Administration Aviation Safety Program (AvSP). The information contained in the RI database was found to contain data that may be relevant to several of the AvSP top ten challenges. When combined with other data from the FAA documenting air traffic volume from calendar year 2000 through 2011, the structure of a predictive model emerges that can be used to forecast the frequency of RI events at various airports for various classes of aircraft and under various environmental conditions.

Runway incursions↗