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At least 19 records

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NASA NTRS2019

Modeling Uncertainty in Time and Fuel Benefit Estimation for TASAR Operational Evaluation

The Traffic Aware Strategic Aircrew Requests concept aims to reduce weather-induced delays, improve route efficiency, and efficiently share route modification options by combining onboard avionics data, Automatic Dependent Surveillance-Broadcast data, and broadband internet data to generate optimal, traffic-compatible trajectory changes based on real-time traffic and weather data. Time and fuel benefits due to use of the Traffic Aware Planner (TAP) software can be estimated by taking the difference in predicted flight time and fuel usage before and after a TAP-inspired trajectory change is completed. Although TAP’s optimization algorithm predicts flight and fuel usage based on the current flight route and weather data, it does not account for possible air traffic controller-initiated trajectory changes, reroutes due to sudden weather changes, or other pilot/controller actions that may occur during flight. This paper introduces an approach for quantifying the uncertainty in estimated time and fuel benefits.

Burris, Joseph↗

NASA NTRS2005

Virtual Observatories for Space Physics Observations and Simulations: New Routes to Efficient Access and Visualization

New tools for data access and visualization promise to make the analysis of space plasma data both more efficient and more powerful, especially for answering questions about the global structure and dynamics of the Sun-Earth system. We will show how new existing tools (particularly the Virtual Space Physics Observatory-VSPO-and the Visual System for Browsing, Analysis and Retrieval of Data-ViSBARD; look for the acronyms in Google) already provide rapid access to such information as spacecraft orbits, browse plots, and detailed data, as well as visualizations that can quickly unite our view of multispacecraft observations. We will show movies illustrating multispacecraft observations of the solar wind and magnetosphere during a magnetic storm, and of simulations of 3 0-spacecraft observations derived from MHD simulations of the magnetosphere sampled along likely trajectories of the spacecraft for the MagCon mission. An important issue remaining to be solved is how best to integrate simulation data and services into the Virtual Observatory environment, and this talk will hopefully stimulate further discussion along these lines.

Roberts, Aaron↗

NASA NTRS2013

Operational Evaluatioin of Dynamic Weather Routes at American Airlines

Dynamic Weather Routes (DWR) is a search engine that continuously and automatically analyzes inflight aircraft in en route airspace and proposes simple route amendments for more efficient routes around convective weather while considering sector congestion, traffic conflicts, and active Special Use Airspace. NASA and American Airlines (AA) are conducting an operational trial of DWR at the AA System Operations Center in Fort Worth, TX. The trial includes only AA flights in Fort Worth Center airspace. Over the period from July 31, 2012 through August 31, 2012, 45% of routes proposed by DWR and evaluated by AA users - air traffic control coordinators and flight dispatchers - were rated as acceptable as proposed or with some modifications. The wind-corrected potential flying time savings for these acceptable routes totals 470 flying min, and results suggest another 1,500 min of potential savings for flights not evaluated due to staffing limitations. A sector congestion analysis shows that in only two out of 83 DWR routes rated acceptable by AA staff were the flights predicted to fly through a congested sector inside of 30 min downstream of present position. This shows that users considered sector congestion data provided by DWR automation and in nearly all cases did not accept routes through over-capacity sectors. It is estimated that 12 AA flights were given reroute clearances as a direct result of DWR for a total savings of 67 flying min.

air traffic trajectory automation↗

NASA NTRS2016

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

ATD-3↗

NASA NTRS2017

Airspace Technology Demonstration 3 (ATD-3): Multi-Flight Common Route (MFCR) Technology Transfer Document Summary Version 1.0

This summary document and accompanying technology artifacts satisfy the second of three Research Transition Products (RTPs) defined in the ATD-3 Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's Multi-Flight Common Route (MFCR) research for efficient route corrections for en-route weather avoidance. The MFCR concept builds on the experience of the legacy Dynamic Weather Routes (DWR) and focuses on a better balance of potential savings with ATC acceptability, common route corrections options for multiple flights on similar routings, and better use of existing and/or modern automation for communication and coordination of route change options. All of these capabilities are expected to improve system performance significantly in terms of actual delay-reducing clearances issued to flights compared to that of the DWR tool and operating concept.

tech transfer↗

NASA NTRS2018

Airspace Technology Demonstration 3 (ATD-3) Multi-Flight Common Route (MFCR) Technology Transfer Document Summary Version 2.0

Airspace Technology Demonstration - 3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multi-year research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en-route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the second of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. The original transfer, completed in December 2017, consisted of NASA's Multi-Flight Common Route (MFCR) research for efficient route corrections for en-route weather avoidance. This transfer updates the Concept of Operations document to a publicly-available NASA Technical Memorandum. The MFCR concept builds on the experience of the legacy Dynamic Weather Routes (DWR) and focuses on a better balance of potential savings with ATC acceptability, common route corrections options for multiple flights on similar routings, and better use of existing and/or modern automation for communication and coordination of route change options. All of these capabilities are expected to improve system performance significantly in terms of actual delay-reducing clearances issued to flights compared to that of the DWR tool and operating concept.

Tech transfer↗

NASA NTRS2018

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 2.0

This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. The original transfer, completed in September 2016, consisted of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. This transfer updates the Concept of Operations document to a publicly-available NASA Technical Memorandum. Dynamic Weather Routes (DWR) is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions.

DWR↗

NASA NTRS1997

The Flight Track Noise Impact Model

To meet its objective of assisting the U.S. aviation industry with the technological challenges of the future, NASA must identify research areas that have the greatest potential for improving the operation of the air transportation system. To accomplish this, NASA is building an Aviation System Analysis Capability (ASAC). The Flight Track Noise Impact Model (FTNIM) has been developed as part of the ASAC. Its primary purpose is to enable users to examine the impact that quieter aircraft technologies and/or operations might have on air carrier operating efficiency at any one of 8 selected U.S. airports. The analyst selects an airport and case year for study, chooses a set of flight tracks for use in the case, and has the option of reducing the noise of the aircraft by 3, 6, or 10 decibels. Two sets of flight tracks are available for each airport: one that represents actual current conditions, including noise abatement tracks, which avoid flying over noise-sensitive areas; and a second set that offers more efficient routing. FTNIM computes the resultant noise impact and the time and distance saved for each operation on the more efficient, alternate tracks. Noise impact is characterized in three ways: the size of the noise contour footprint, the number of people living within the contours, and the number of homes located in the same contours. Distance and time savings are calculated by comparing the noise abatement flight path length to the more efficient alternate routing.

Burn, Melissa↗

NASA NTRS2016

Strategic Design of Long-Haul and Oceanic Aircraft Trajectories in Aviation Operations

Long-Haul Aircraft consume most of their fuel during the cruise phase of flight. The inefficiency in cruise flights compared to efficient routes varies is around 3 to 4. The efficiency of oceanic flights is low due to limited navigational and communication equipment, congestion and airspace restrictions. The availability of Automated Dependent Surveillance-Broadcast (ADS-B) and other improvements provides opportunity for better strategic planning of trajectories. Transatlantic flights between US and Europe constitute one of the busiest oceanic airspace regions in the world. This talk examines the benefits of a wind-optimal trajectory concept with a strategic de-confliction component compared to the current flight planning using the North Atlantic Tracks. The analysis is based on air traffic between US and Europe during July 2012. The potential fuel savings are in the range of (420-970) kg per flight for a Boeing 767-300, the most widely used aircraft between the city-pairs in this study. The talk also describes a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASAs Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to characterize the evolution of global air traffic, analyze fuel savings and seasonal variations in the long-haul wind-optimal traffic patterns in six major regions of the world.

strategic trajectory design↗

NASA NTRS2015

Dynamic Weather Routes: Two Years of Operational Testing at American Airlines

The Dynamic Weather Routes (DWR) tool continuously analyzes active flights in en-route airspace and finds simple route corrections to achieve more time- and fuel-efficient routes around convective weather. A strong partnership between NASA, American Airlines (AA), and the Federal Aviation Administration has enabled testing of DWR in real-world air traffic operations. NASA and AA have been conducting a trial of DWR at AA’s Integrated Operations Center in Fort Worth, Texas since July 2012. This paper describes test results based on AA’s use of DWR for their flights in and around Fort Worth Center (ZFW). Results indicate an actual savings of 3,290 flying minutes for 526 AA revenue flights from January 2013 through September 2014. Of these, 48 flights each indicate a savings of 15 minutes or more. Potential savings for all flights in ZFW airspace, corrected for savings flights achieve today through normal pilot requests and controller clearances, is about 100,000 flying minutes for 15,000 flights in 2013. Results indicate that AA flights with DWR in use realize about 20 percent more savings than non-AA flights. A weather forecast analysis examines the extent to which DWR routes rated acceptable by AA users remain clear of downstream weather. A sector congestion analysis indicates congestion could be reduced 19-38 percent if all flights fly DWR routes rather than nominal weather-avoidance routes.

Trajectory Automation↗

NASA NTRS1996

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

Corker, Kevin M.↗

NASA NTRS1987

Route planning in a four-dimensional environment

Robots must be able to function in the real world. The real world involves processes and agents that move independently of the actions of the robot, sometimes in an unpredictable manner. A real-time integrated route planning and spatial representation system for planning routes through dynamic domains is presented. The system will find the safest most efficient route through space-time as described by a set of user defined evaluation functions. Because the route planning algorthims is highly parallel and can run on an SIMD machine in O(p) time (p is the length of a path), the system will find real-time paths through unpredictable domains when used in an incremental mode. Spatial representation, an SIMD algorithm for route planning in a dynamic domain, and results from an implementation on a traditional computer architecture are discussed.

Slack, M. G.↗

NASA NTRS1997

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

Corker, Kevin M.↗

NASA NTRS1990

Adaptive fault-tolerant routing in hypercube multicomputers

A connected hypercube with faulty links and/or nodes is called an injured hypercube. To enable any non-faulty node to communicate with any other non-faulty node in an injured hypercube, the information on component failures has to be made available to non-faulty nodes so as to route messages around the faulty components. A distributed adaptive fault tolerant routing scheme is proposed for an injured hypercube in which each node is required to know only the condition of its own links. Despite its simplicity, this scheme is shown to be capable of routing messages successfully in an injured hypercube as long as the number of faulty components is less than n. Moreover, it is proved that this scheme routes messages via shortest paths with a rather high probabiltiy and the expected length of a resulting path is very close to that of a shortest path. Since the assumption that the number of faulty components is less than n in an n-dimensional hypercube might limit the usefulness of the above scheme, a routing scheme is introduced based on depth-first search which works in the presence of an arbitrary number of faulty components. Due to the insufficient information on faulty components, the paths chosen by the above scheme may not always be the shortest. To guarantee that all messages be routed via shortest paths, it is proposed that every mode be equipped with more information than that on its own links. The effects of this additional information on routing efficiency are analyzed, and the additional information to be kept at each node for the shortest path routing is determined. Several examples and remarks are also given to illustrate the results.

Chen, Ming-Syan↗

NASA NTRS2014

Traffic Management Coordinator Evaluation of the Dynamic Weather Routes Concept and System

Dynamic Weather Routes (DWR) is a weather-avoidance system for airline dispatchers and FAA traffic managers that continually searches for and advises the user of more efficient routes around convective weather. NASA and American Airlines (AA) have been conducting an operational trial of DWR since July 17, 2012. The objective of this evaluation is to assess DWR from a traffic management coordinator (TMC) perspective, using recently retired TMCs and actual DWR reroutes advisories that were rated acceptable by AA during the operational trial. Results from the evaluation showed that the primary reasons for a TMC to modify or reject airline reroute requests were related to airspace configuration. Approximately 80 percent of the reroutes evaluated required some coordination before implementation. Analysis showed TMCs approved 62 percent of the requested DWR reroutes, resulting in 57 percent of the total requested DWR time savings.

weather avoidance↗

NASA NTRS2011

Contact Graph Routing

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic. The information carried by CGR contact plan messages is useful not only for dynamic route computation, but also for the implementation of rate control, congestion forecasting, transmission episode initiation and termination, timeout interval computation, and retransmission timer suspension and resumption.

Burleigh, Scott C.↗

NASA NTRS2013

Scheduling and Separating Departures Crossing Arrival Flows in Shared Airspace

Flight efficiency and reduction of flight delays are among the primary goals of NextGen. In this paper, we propose a concept of shared airspace where departures fly across arrival flows, provided gaps are available in these flows. We have explored solutions to separate departures temporally from arrival traffic and pre-arranged procedures to support controllers' decisions. We conducted a Human-in-the-Loop simulation and assessed the efficiency and safety of 96 departures from the San Jose airport (SJC) climbing across the arrival airspace of the Oakland and San Francisco arrival flows. In our simulation, the SJC tower had a tool to schedule departures to fly across predicted gaps in the arrival flow. When departures were mistimed and separation could not be ensured, a safe but less efficient route was provided to the departures to fly under the arrival flows. A coordination using a point-out procedure allowed the arrival controller to control the SJC departures right after takeoff. We manipulated the accuracy of departure time (accurate vs. inaccurate) as well as which sector took control of the departures after takeoff (departure vs. arrival sector) in a 2x2 full factorial plan. Results show that coordination time decreased and climb efficiency increased when the arrival sector controlled the aircraft right after takeoff. Also, climb efficiency increased when the departure times were more accurate. Coordination was shown to be a critical component of tactical operations in shared airspace. Although workload, coordination, and safety were judged by controllers as acceptable in the simulation, it appears that in the field, controllers would need improved tools and coordination procedures to support this procedure.

shared airspace↗

NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

route advisories↗