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NASA NTRS2004

NASA Tech Briefs, November 2004

Topics include: Multifunction Imaging and Spectroscopic Instrument; Position-Finding Instrument Built Around a Magnetometer; Improved Measurement of Dispersion in an Optical Fiber; Probe for Sampling of Interstitial Fluid From Bone; Neuropsychological Testing of Astronauts; Method of Calibration for a Large Cathetometer System; Four-Channel PC/104 MIL-STD-1553 Circuit Board; Improved Method of Locating Defects in Wiring Insulation; Strobe Traffic Lights Warn of Approaching Emergency Vehicles; Improved Timing Scheme for Spaceborne Precipitation Radar; Concept for Multiple-Access Free-Space Laser Communications; Variable Shadow Screens for Imaging Optical Devices; Verifying Diagnostic Software; Initial Processing of Infrared Spectral Data; Activity-Centric Approach to Distributed Programming; Controlling Distributed Planning; New Material for Surface-Enhanced Raman Spectroscopy; Treated Carbon Nanofibers for Storing Energy in Aqueous KOH; Advanced Infant Car Seat Would Increase Highway Safety; Development of Biomorphic Flyers; Second-Generation Six-Limbed Experimental Robot; Miniature Linear Actuator for Small Spacecraft; Process for Making Single-Domain Magnetite Crystals; A New Process for Fabricating Random Silicon Nanotips; Resin-Transfer-Molding of a Tool Face; Improved Phase-Mask Fabrication of Fiber Bragg Gratings; Tool for Insertion of a Fiber-Optic Terminus in a Connector; Nanofluidic Size-Exclusion Chromatograph; Lightweight, Low-CTE Tubes Made From Biaxially Oriented LCPs; Using Redundancy To Reduce Errors in Magnetometer Readings; Compact Instrument for Measuring Profile of a Light Beam; Multilayer Dielectric Transmissive Optical Phase Modulator; Second-Generation Multi-Angle Imaging Spectroradiometer; Real-Time Adaptive Color Segmentation by Neural Networks; Research and Development in Optical Communications; Tests of Multibeam Scintillation Mitigation on Laser Uplinks; and Spaceborne Infrared Atmospheric Sounder.

Source record↗

NASA NTRS2017

Evolution of A Distributed Live, Virtual, Constructive Environment for Human in the Loop Unmanned Aircraft Testing

NASA's Unmanned Aircraft Systems Integration in the National Airspace System Project is conducting human in the loop simulations and flight testing intended to reduce barriers associated with enabling routine airspace access for unmanned aircraft. The primary focus of these tests is interaction of the unmanned aircraft pilot with the display of detect and avoid alerting and guidance information. The projects integrated test and evaluation team was charged with developing the test infrastructure. As with any development effort, compromises in the underlying system architecture and design were made to allow for the rapid prototyping and open-ended nature of the research. In order to accommodate these design choices, a distributed test environment was developed incorporating Live, Virtual, Constructive, (LVC) concepts. The LVC components form the core infrastructure support simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This LVC infrastructure enables efficient testing by leveraging the use of existing assets distributed across multiple NASA Centers. Using standard LVC concepts enable future integration with existing simulation infrastructure.

UAS in the NA↗

NASA NTRS2017

Evolution of A Distributed Live, Virtual, Constructive Environment for Human in the Loop Unmanned Aircraft Testing

NASA's Unmanned Aircraft Systems Integration in the National Airspace System Project is conducting human in the loop simulations and flight testing intended to reduce barriers associated with enabling routine airspace access for unmanned aircraft. The primary focus of these tests is interaction of the unmanned aircraft pilot with the display of detect and avoid alerting and guidance information. The project's integrated test and evaluation team was charged with developing the test infrastructure. As with any development effort, compromises in the underlying system architecture and design were made to allow for the rapid prototyping and open-ended nature of the research. In order to accommodate these design choices, a distributed test environment was developed incorporating Live, Virtual, Constructive, (LVC) concepts. The LVC components form the core infrastructure support simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This LVC infrastructure enables efficient testing by leveraging the use of existing assets distributed across multiple NASA Centers. Using standard LVC concepts enable future integration with existing simulation infrastructure.

LVC↗

NASA NTRSDate not supplied

Runway Configuration Management with Offline Reinforcement Learning

Runway configuration management (RCM) is a challenging task, and it affects the efficiency of the National Airspace System (NAS) and airport surface operations significantly. Each airport, depending on the geometry, capacity, local climate patterns, etc. has multiple configurations for the runway usage for arriving and departing flights. Many factors such as the incoming/outgoing traffic load, wind direction and speed, convective weather, cloud ceiling and other environmental factors might affect the choice of a runway configuration at any point in time. However, other factors such as safety measures and regulations, noise abatement, capacity of each configuration, and preference of the air traffic controllers (ATCs) can also play a significant role in selecting the configuration. A sub-optimal selection of the runway configuration, or delay in making configuration changes might result in significant increase in taxi times for aircraft on the surface of the airport, fuel and energy use of the aircraft, and maintenance costs. It can also lead to safety concerns, such as an aircraft performing one or more go-arounds before being able to land. All these factors make RCM an extremely important and challenging decision-making process for the ATCs. The current state of practice sets the runway configuration by the ATCs based on relevant information available at the time including weather, traffic, noise abatement, safety bounds, etc. This makes the decision-making process subjective based on the accuracy of the available information and the bias in human decision making. Unfortunately, this approach yields poor results (e.g., significant delays) if the predicted outcomes are uncertain and their relative impact is not well understood. This is especially evident when the uncertainty increases the size of possible predicted outcomes (combinatorial explosion in possible scenarios) that cannot be handled by human reasoning. On the other hand, an automated approach based on machine intelligence can make use of historical data and search through all (or significant amount of) possible scenarios under uncertainty and make well-informed decisions.

Milad Memarzadeh↗

NASA NTRS2010

Automated Conflict Resolution, Arrival Management and Weather Avoidance for ATM

The paper describes a unified solution to three types of separation assurance problems that occur in en-route airspace: separation conflicts, arrival sequencing, and weather-cell avoidance. Algorithms for solving these problems play a key role in the design of future air traffic management systems such as NextGen. Because these problems can arise simultaneously in any combination, it is necessary to develop integrated algorithms for solving them. A unified and comprehensive solution to these problems provides the foundation for a future air traffic management system that requires a high level of automation in separation assurance. The paper describes the three algorithms developed for solving each problem and then shows how they are used sequentially to solve any combination of these problems. The first algorithm resolves loss-of-separation conflicts and is an evolution of an algorithm described in an earlier paper. The new version generates multiple resolutions for each conflict and then selects the one giving the least delay. Two new algorithms, one for sequencing and merging of arrival traffic, referred to as the Arrival Manager, and the other for weather-cell avoidance are the major focus of the paper. Because these three problems constitute a substantial fraction of the workload of en-route controllers, integrated algorithms to solve them is a basic requirement for automated separation assurance. The paper also reviews the Advanced Airspace Concept, a proposed design for a ground-based system that postulates redundant systems for separation assurance in order to achieve both high levels of safety and airspace capacity. It is proposed that automated separation assurance be introduced operationally in several steps, each step reducing controller workload further while increasing airspace capacity. A fast time simulation was used to determine performance statistics of the algorithm at up to 3 times current traffic levels.

Erzberger, H.↗

NASA NTRS2018

Modeling Key Predictors of Airport Runway Configurations Using Learning Algorithms

Advanced traffic flow management automation will need accurate predictions of airport runway configurations. Terminal area weather and traffic demand are generally considered to be the most significant factors in predicting runway configuration. Weather information is forecasted across multiple features, including wind direction, wind speed, gusts, cloud ceilings, visibility, temperature, and precipitation, among many others. We use machine learning techniques on historical weather and runway data to determine weather features that correlate well with runway configurations. We analyze the predictive capability of weather features using different learning models trained on data from four major U.S. airports: Atlanta (ATL), Washington – Dulles (IAD), New York – Kennedy (JFK), and San Francisco (SFO). Wind direction alone is strongly correlated with runway configurations above all other examined factors, as expected. This correlation is the most significant component of the ~80% prediction accuracy in selecting between the two most frequently used runway configurations. However, individual airports show variations on how well the runway configuration decisions correlate with wind direction. While wind direction was identified as the most significant indicator of configuration decisions in ATL, IAD, and JFK, it did not emerge as such at SFO. Traffic demand was not found to be a strong factor in predicting runway configurations at any of the airports analyzed. In rare instances, when high demand cannot be accommodated within the current configuration, temporary changes are likely to be attributable to demand. However, these occurrences are so limited in number that their overall effect is not sufficient to consider traffic demand as a major indicator of runway configuration at the airports analyzed.

Bilimoria, Karl D.↗

NASA NTRSDate not supplied

Strategic and Tactical Functions in an Autonomous Air Traffic Management System

This paper evaluates, by means of fast-time simulation, performance of a candidate system for autonomous air traffic management. Advancing towards autonomy in air traffic management may be necessary in order for new air vehicle types such as electric Vertical Take Off and Landing (eVTOL) to operate safely and efficiently in airspace shared with conventional traffic. To account for uncertain prediction, autonomous air traffic management was divided into two integrated and coordinated subsystems: strategic scheduling, performed at predeparture, and tactical conflict detection and resolution, performed throughout the flight. The conflict detection and resolution subsystem contained a second tactical scheduling function that applied to flights operating in the airspace near the destination airport. This paper compares and contrasts the two subsystems and uses fast-time simulation to demonstrate the comparisons. A scenario of 54 flights inbound to Newark Liberty International Airport was simulated multiple times with different parameters. The scenario was created using flight plans recorded from the National Airspace System on a low weather, average traffic day in April 2018. Whereas the routes were not changed, the departure times of the flights were modified to increase arrival rates at the Newark runway and arrival meter fixes. Results of the simulations showed that the autonomous air traffic management system was able to safely manage the traffic, even with prediction uncertainty. In addition, they showed the importance of including flight holding maneuvers, in addition to path stretching, in conflict detection and resolution and of coordinating strategic and tactical scheduling. Finally, a tradeoff between absorbing the delay calculated by strategic scheduling on the ground versus in the air showed that taking most of the delay on the ground is cost effective for a simple idealized cost function. However, taking a little of the delay in the air prevented throughput on the runway from dropping for short periods due to trajectory prediction uncertainty.

air traffic control↗

NASA NTRS2021

Strategic and Tactical Functions in an Autonomous Air Traffic Management System

air traffic control↗

NASA NTRS1967

Place experiment description

Experiment to demonstrate multiple access technique in Position Location and Aircraft Communication Equipment studies using ATS-F satellite for air traffic control

Allen, W. K.↗

NASA NTRS2012

Flying Schedule-Matching Descents to Explore Flight Crews' Perceptions of Their Load and Task Feasibility

Multiple studies have investigated the development and use of ground-based (controller) tools to manage and schedule traffic in future terminal airspace. No studies have investigated the impacts that such tools (and concepts) could have on the flight-deck. To begin to redress the balance, an exploratory study investigated the procedures and actions of ten Boeing-747-400 crews as they flew eight continuous descent approaches in the Los Angeles terminal airspace, with the descents being controlled using speed alone. Although the study was exploratory in nature, four variables were manipulated: speed changes, route constraints, clearance phraseology, and winds. Despite flying the same scenarios with the same events and timing, there was at least a 50 second difference in the time it took crews to fly the approaches. This variation is the product of a number of factors but highlights potential difficulties for scheduling tools that would have to accommodate this amount of natural variation in descent times. The primary focus of this paper is the potential impact of ground scheduling tools on the flight crews performance and procedures. Crews reported "moderate to low" workload, on average; however, short periods of intense and high workload were observed. The non-flying pilot often reported a higher level of workload than the flying-pilot, which may be due to their increased interaction with the Flight Management Computer, when using the aircraft automation to assist with managing the descent clearances. It is concluded that ground-side tools and automation may have a larger impact on the current-day flight-deck than was assumed and that studies investigating this impact should continue in parallel with controller support tool development.

Martin, Lynne Hazel↗

NASA NTRS2020

ATD-2 Phase 3 Scheduling in a Metroplex Environment Incorporating Trajectory Option Sets

The NASA Airspace Technology Demonstration 2 Phase 1 and 2 Field Evaluations have successfully demonstrated new technologies developed to manage the Integrated Arrival, Departure, and Surface traffic flows at a single airport. The Phase 3 Field Evaluation extends the capabilities to a Metroplex environment where multiple airports are interacting and sharing resources along the terminal boundary. This paper describes the scheduling algorithm enabling the coordinated scheduling and describes the interaction between airports within the Metroplex and the terminal boundary. We describe the metrics developed to inform flight operators about reroute opportunities and discuss the potential benefits to the rerouted flight and the system-wide aggregate benefits of a single reroute. We believe that the capabilities developed and the lessons learned during the Phase 3 Field Evaluation will set up the National Airspace System for future success.

Airspace Technology Demonstration 2↗

NASA NTRS2014

Development of Super Ensemble-Based Aviation Turbulence Guidance (SEATG) for Air Traffic Management

A new method for forecasting turbulence is developed and evaluated using the high resolution weather model and in situ turbulence observations from commercial aircraft. The new method is an ensemble of various turbulence metrics from multiple time-lagged ensemble forecasts created using a sequence of four procedures. These include weather modeling, calculation of turbulence metrics, mapping the metrics into a common turbulence-scale, and production of final forecast. The new method uses similar methodology as current operational turbulence forecast with three improvements. First, it uses a higher resolution ((delta)x = 3 km) weather model to capture cloud resolving scale phenomena. Second, it computes the metrics for multiple forecasts that are combined at the same valid time resulting in a time-lagged ensemble of multiple turbulence metrics. Finally, it provides both deterministic and probabilistic turbulence forecasts. Results show the new forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on research period. Overall performance skill of the new turbulence forecast compared with the observed EDR data during the research period is superior to any single turbulence metric. The probabilistic turbulence forecast is used in an example air traffic management application for creating a wind-optimal route considering turbulence information. The wind-optimal route passing through areas of 50% potential for moderate-or-greater turbulence and the lateral turbulence avoidance routes starting from three different waypoints along the wind-optimal route from Los Angeles international airport to John F. Kennedy international airport are calculated using different turbulence forecasts. This example shows additional flight time is required to avoid potential turbulence encounters.

modeling↗

NASA NTRS2011

User Centered, Application Independent Visualization of National Airspace Data

This paper describes an application independent software tool, IV4D, built to visualize animated and still 3D National Airspace System (NAS) data specifically for aeronautics engineers who research aggregate, as well as single, flight efficiencies and behavior. IV4D was origin ally developed in a joint effort between the National Aeronautics and Space Administration (NASA) and the Air Force Research Laboratory (A FRL) to support the visualization of air traffic data from the Airspa ce Concept Evaluation System (ACES) simulation program. The three mai n challenges tackled by IV4D developers were: 1) determining how to d istill multiple NASA data formats into a few minimal dataset types; 2 ) creating an environment, consisting of a user interface, heuristic algorithms, and retained metadata, that facilitates easy setup and fa st visualization; and 3) maximizing the user?s ability to utilize the extended range of visualization available with AFRL?s existing 3D te chnologies. IV4D is currently being used by air traffic management re searchers at NASA?s Ames and Langley Research Centers to support data visualizations.

Murphy, James R.↗

NASA NTRS2015

NASA's ATM Ontology: Semantic Integration and Querying Across NAS Data Sources

NASA is developing an Air Traffic Management (ATM) Ontology as part of an advanced prototyping activity that demonstrates the utility of semantic technologies for integrating, querying, and searching over various sources of heterogeneous ATM data. The ontology encodes an overarching data model that functions as the backbone upon which to overlay data from multiple sources published by FAA, NOAA, NASA, and others. The integrated data can be queried to produce results not achievable using any single source alone. The ontology incorporates flight data, weather data, traffic management advisory data, airport delay data, and national airspace infrastructure data for a very limited spatial and temporal slice of airspace operations (one day of operations at a major airport).

air traffic management↗

NASA NTRS2013

How do Air Traffic Controllers Use Automation and Tools Differently During High Demand Situations?

In a human-in-the-loop simulation, two air traffic controllers managed identical airspace while burdened with higher than average workload, and while using advanced tools and automation designed to assist with scheduling aircraft on multiple arrival flows to a single meter fix. This paper compares the strategies employed by each controller, and investigates how the controllers' strategies change while managing their airspace under more normal workload conditions and a higher workload condition. Each controller engaged in different methods of maneuvering aircraft to arrive on schedule, and adapted their strategies to cope with the increased workload in different ways. Based on the conclusions three suggestions are made: that quickly providing air traffic controllers with recommendations and information to assist with maneuvering and scheduling aircraft when burdened with increased workload will improve the air traffic controller's effectiveness, that the tools should adapt to the strategy currently employed by a controller, and that training should emphasize which traffic management strategies are most effective given specific airspace demands.

ATC↗

NASA NTRS2019

Complex Dynamics of Air Traffic Flow

Air traffic in the United States has continued to grow at a steady pace since 1980, except for a dip immediately after the tragic events of September 11, 2001. There are different growth scenarios associated both with the magnitude and the composition of the future air traffic. The Terminal Area Forecast (TAF), prepared every year by the FAA, projects the growth of traffic in the United States. Both Boeing and Airbus publish market outlooks for air travel annually. Although predicting the future growth of traffic is difficult, there are two significant trends: heavily congested major airports continue to see an increase in traffic, and the emergence of regional jets and other smaller aircraft with fewer passengers operating directly between non-major airports. The interaction between air traffic demand and the ability of the system to provide the necessary airport and airspace resources can be modeled as a network. The size of the resulting network varies depending on the choice of its nodes. It would be useful to understand the properties of this network to guide future design and development. Many questions, such as the growth of delay with increasing traffic demand and impact of the en route weather on future air traffic, require a systematic understanding of the properties of the air traffic network. There has been a major advance in the understanding of the behavior of networks with a large number of components. Several theories have been advanced about the evolution of large biological and engineering networks by authors in diversified disciplines like physics, mathematics, biology and computer science. Several networks exhibit a scale-free property in the sense that the probabilistic distribution of their nodes as a function of connections decreases slower than an exponential. These networks are characterized by the fact that a small number of components have a disproportionate influence on the performance of the network. Scale-free networks are tolerant to random failure of components, but are vulnerable to selective attack on components. This paper examines two network representations for the baseline air traffic system. A network defined with the 40 major airports as nodes and with standard flight routes as links has a characteristic scale: all nodes have 60 or more links and no node has more than 460 links. Another network is defined with baseline aircraft routing structure exhibits an exponentially truncated scale-free behavior. Its degree ranges from 2 connections to 2900 connections, and 225 nodes have more than 250 connections. Furthermore, those high-degree nodes are homogeneously distributed in the airspace. A consequence of this scale-free behavior is that the random loss of a single node has little impact, but the loss of multiple high-degree nodes (such as occurs during major storms in busy airspace) can adversely impact the system. Two future scenarios of air traffic growth are used to predict the growth of air traffic in the United States. It is shown that a three-times growth in the overall traffic may result in a ten-times impact on the density of traffic in certain parts of the United States.

Scale-free Networks↗

NASA NTRS2009

Serial Network Flow Monitor

Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

Robinson, Julie A.↗

NASA NTRS1984

Simulation of a cockpit-display concept for executing a wake-vortex avoidance procedure

A piloted simulation study has been undertaken to determine the feasibility and potential benefits of utilizing a forward-looking display to provide information that would enable aircraft to reduce their in-trail separation, and hence increase runway capacity, through the application of multiple glide-path approach techniques. This portion of the study was an initial exploration into a concept in which traffic information was added to a head-up display (HUD) format to allow the pilot to monitor the traffic situation and to self-space on a lead aircraft during a single glide-path approach task. The tests were conducted in a motion-base cockpit simulator configured as a current-generation transport aircraft and include the dynamic effects of the vortices generated by the lead aircraft. The information provided on the HUD included typical aircraft-guidance information and the current and past positions of the lead aircraft. Additionally, the displayed information provided self-separation cues which allowed the pilot to maintain separation on the lead aircraft. The results of this study indicate that the display concept could provide sufficient information to the pilot for traffic monitoring and self-separation.

Abbott, T. S.↗