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NASA NTRS2019

Field Evaluation of the Baseline Integrated Arrival, Departure, and Surface Capabilities at Charlotte Douglas International Airport

NASA is currently developing a suite of decision support capabilities for integrated arrival, departure, and surface (IADS) operations in a metroplex environment. The effort is being made in three phases, under NASA's Airspace Technology Demonstration 2 (ATD-2) sub-project, through a strong partnership with the Federal Aviation Administration (FAA), air carriers, airport, and general aviation community. The Phase 1 Baseline IADS capabilities provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, tactical surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. The users of the IADS system include the personnel at the Charlotte Douglas International Airport (CLT) air traffic control tower, American Airlines ramp tower, CLT terminal radar approach control (TRACON), and Washington Center. This paper describes the Phase 1 Baseline IADS capabilities and field evaluation conducted at CLT from September 2017 for a year. From the analysis of operations data, it is estimated that 538,915 kilograms of fuel savings, and 1,659 metric tons of CO2 emission reduction were achieved during the period with a total of 944 hours of engine run time reduction. The amount of CO2 savings is estimated as equivalent to planting 42,560 urban trees. The results have also shown that the surface metering had no negative impact on on-time arrival performance of both outbound and inbound flights. The technology transfer of Phase 1 Baseline IADS capabilities has been made to the FAA and aviation industry, and the development of additional capabilities for the subsequent phases is underway.

Jung, Yoon C.↗

NASA NTRS2019

Field Evaluation of the Baseline Integrated Arrival, Departure, and Surface (IADS) Capabilities at Charlotte Douglas International Airport (CLT)

and Surface (IADS)↗

NASA NTRS2004

CTAS and NASA Air Traffic Management Fact Sheets for En Route Descent Advisor and Surface Management System

The Surface Management System (SMS) is a decision support tool that will help controllers, traffic managers, and NAS users manage the movements of aircraft on the surface of busy airports, improving capacity, efficiency, and flexibility. The Advanced Air Transportation Technologies (AATT) Project at NASA is developing SMS in cooperation with the FAA's Free Flight Phase 2 (FFP2) pro5ram. SMS consists of three parts: a traffic management tool, a controller tool, and a National Airspace System (NAS) information tool.

Lee, Katharine↗

NASA NTRS2011

Trajectory-Based Takeoff Time Predictions Applied to Tactical Departure Scheduling: Concept Description, System Design, and Initial Observations

Current aircraft departure release times are based on manual estimates of aircraft takeoff times. Uncertainty in takeoff time estimates may result in missed opportunities to merge into constrained en route streams and lead to lost throughput. However, technology exists to improve takeoff time estimates by using the aircraft surface trajectory predictions that enable air traffic control tower (ATCT) decision support tools. NASA s Precision Departure Release Capability (PDRC) is designed to use automated surface trajectory-based takeoff time estimates to improve en route tactical departure scheduling. This is accomplished by integrating an ATCT decision support tool with an en route tactical departure scheduling decision support tool. The PDRC concept and prototype software have been developed, and an initial test was completed at air traffic control facilities in Dallas/Fort Worth. This paper describes the PDRC operational concept, system design, and initial observations.

Engelland, Shawn A.↗

NASA NTRS2011

Precision Departure Release Capability (PDRC) Integration, Evaluation and Transition

NASA's Precision Departure Release Capability (PDRC) research activity is assessing the use of surface trajectory-based takeoff (OFF) time estimates for en route domain departure scheduling in Call For Release situations. Current aircraft departure release times computed by an Air Traffic Management decision support tool to meet Call For Release constraints are based on coarse estimates of aircraft OFF times. Uncertainty in OFF time estimates may result in missed opportunities to merge into an overhead stream and lost throughput. However, technology exists to improve OFF time estimates by using more accurate aircraft trajectory predictions available in NextGen airport surface management decision support tools. PDRC findings are expected to be broadly applicable to NextGen integrated arrival/departure/surface implementations. For concept development and evaluation purposes this research activity integrates NASA's Surface Management System (SMS) OFF time prediction capabilities with Traffic Management Advisor (TMA) departure scheduling functions. PDRC field evaluations are being conducted at the North Texas (NTX) Research Station. The NASA/FAA Integrated Arrival/Departure/Surface Research Transition Team is using PDRC as a pathfinder for developing technology transfer mechanisms and procedures.

Engelland, Shawn A.↗

NASA NTRSDate not supplied

Machine Learning Airport Surface Model

Future needs of the National Airspace System require decision support tools to adopt a service-oriented architecture in alignment with the FAA’s vision for an Info-Centric NAS. To achieve this, many existing systems will need to undergo a digital transformation from a monolithic decision support tool to a service-oriented architecture where individual services are exposed through well defined Application Programming Interfaces (APIs). To enable this transformation, NASA has developed the Digital Information Platform as a cloud based foundation for development of aviation services with a special focus towards Artificial Intelligence and Machine Learning (ML) services. This paper describes the work required for the transformation of NASA’s legacy surface management system to a real-time ML based decision support system deployed in the cloud. Details of the Machine Learning Operations (MLOps) infrastructure and best practices are described which enabled the end-toend lifecycle management of ML within an integrated software system. Validation results are provided from an operational field evaluation where performance was benchmarked against the legacy approach.

Jeremy Coupe↗

NASA NTRS2016

Methods for Determining Aircraft Surface State at Lesser-Equipped Airports

Tactical departure scheduling within a terminal airspace must accommodate a wide spectrum of surveillance and communication capabilities at multiple airports. The success of such a scheduler is highly dependent upon the knowledge of a departure's state while it is still on the surface. Airports within a common Terminal RAdar CONtrol (TRACON) airspace possess varying levels of surface surveillance infrastructure which directly impacts uncertainties in wheels-off times. Large airports have access to surface surveillance data, which is shared with the TRACON, while lesser-equipped airports still rely solely on controllers in Air Traffic Control Towers (Towers). Coordination between TRACON and Towers can be greatly enhanced when the TRACON controller has access to the surface surveillance and the associated decision-support tools at well-equipped airports. Similar coordination at lesser-equipped airports is still based on verbal communications. This paper investigates possible methods to reduce the uncertainty in wheels-off time predictions at the lesser-equipped airports through the novel use of Over-the-Air (OTA) data transmissions. We also discuss the methods and equipment used to collect sample data at lesser-equipped airports within a large US TRACON, as well as the data evaluation to determine if meaningful information can be extracted from it.

departure scheduling↗

NASA NTRS2006

Thermal Band Atmospheric Correction Using Atmospheric Profiles Derived from Global Positioning System Radio Occultation and the Atmospheric Infrared Sounder

This Rapid Prototyping Capability study explores the potential to use atmospheric profiles derived from GPS (Global Positioning System) radio occultation measurements and by AIRS (Atmospheric Infrared Sounder) onboard the Aqua satellite to improve surface temperature retrieval from remotely sensed thermal imagery. This study demonstrates an example of a cross-cutting decision support technology whereby NASA data or models are shown to improve a wide number of observation systems or models. The ability to use one data source to improve others will be critical to the GEOSS (Global Earth Observation System of Systems) where a large number of potentially useful systems will require auxiliary datasets as input for decision support. Atmospheric correction of thermal imagery decouples TOA radiance and separates surface emission from atmospheric emission and absorption. Surface temperature can then be estimated from the surface emission with knowledge of its emissivity. Traditionally, radiosonde sounders or atmospheric models based on radiosonde sounders, such as the NOAA (National Oceanic & Atmospheric Administration) ARL (Air Resources Laboratory) READY (Real-time Environmental Application and Display sYstem), provide the atmospheric profiles required to perform atmospheric correction. Unfortunately, these types of data are too spatially sparse and too infrequently taken. The advent of high accuracy, global coverage, atmospheric data using GPS radio occultation and AIRS may provide a new avenue for filling data input gaps. In this study, AIRS and GPS radio occultation derived atmospheric profiles from the German Aerospace Center CHAMP (CHAllenging Minisatellite Payload), the Argentinean Commission on Space Activities SAC-C (Satellite de Aplicaciones Cientificas-C), and the pair of NASA GRACE (Gravity Recovery and Climate Experiment) satellites are used as input data in atmospheric radiative transport modeling based on the MODTRAN (MODerate resolution atmospheric TRANsmittance) radiative transport software to separate out the atmospheric component of measured top of atmosphere radiance. Simulated water bodies across a variety of MODTRAN model atmospheres including desert, mid-latitude, tropical and sub-artic conditions provide test bed conditions. Atmospherically corrected radiance and surface temperature results were compared to those obtained using traditional radiosonde balloon data and models. In general, differences between the different techniques were less than 2 percent indicating the potential value satellite derived atmospheric profiles have to atmospherically correct thermal imagery.

Pagnutti, Mary↗

NASA NTRS2008

Enhancements and Evolution of the Real Time Mission Monitor

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM has proven extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, mission scientists, instrument scientists and program managers alike appreciate the contributions that RTMM makes to their flight projects. We have received numerous plaudits from a wide variety of scientists who used RTMM during recent field campaigns including the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) missions, the 2007-2008 NOAA-NASA Aerosonde Hurricane flights and the 2008 Soil Moisture Active-Passive Validation Experiment (SMAP-VEX). Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated for altitude, latitude, longitude, flight leg distance, cumulative distance, flight leg time, cumulative time, and satellite overpass intersections. The resultant flight plan is then generated in KML and quickly posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and then compare it to the actual real time flight progress. A description of the system architecture, components, and applications along with reviews and animations of RTMM during the field campaigns, plus planned enhancements and future opportunities will be presented.

Goodman, Michael↗

NASA NTRS2009

Integrating and Visualizing Tropical Cyclone Data Using the Real Time Mission Monitor

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the NASA Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM is extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, scientists, and managers appreciate the contributions that RTMM makes to their flight projects. A broad spectrum of interdisciplinary scientists used RTMM during field campaigns including the hurricane-focused 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 NOAA-NASA Aerosonde Hurricane Noel flight, 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), plus a soil moisture (SMAP-VEX) and two arctic research experiments (ARCTAS) in 2008. Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated "on the fly". The resultant flight plan is then immediately posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and subsequently compare it to the actual real time flight progress. We are planning additional capabilities to RTMM including collaborations with the Jet Propulsion Laboratory in the joint development of a Tropical Cyclone Integrated Data Exchange and Analysis System (TC IDEAS) which will serve as a web portal for access to tropical cyclone data, visualizations and model output.

Goodman, H. Michael↗

NASA NTRS2020

ATD-2 Benefits Mechanism

NASA has been developing and demonstrating a suite of decision support capabilities for integrated arrival, departure, and surface (IADS) operations in a metroplex environment. The effort is being made in three phases, under NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project, through a close partnership with the Federal Aviation Administration (FAA), air carriers, airport, and general aviation community. The Phase 1 Baseline IADS capabilities provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, tactical surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. The Phase 2 Fused IADS capabilities include the fusion of strategic and tactical surface metering, Atlanta Center airspace tactical scheduling, Electronic Flight Data (EFD) integration, Terminal Flight Data Manager (TFDM) Terminal Publication (TTP) prototype, and Mobile App for General Aviation (GA) community. In the Phase 2 field evaluation, strategic surface metering provides advance notice of metering and additional stability to the assigned gate holds. The users of the IADS system in Phases 1 and 2 include the personnel at Charlotte Douglas International Airport (CLT) air traffic control tower, American Airlines ramp tower, CLT terminal radar approach control (TRACON), and Washington and Atlanta Center. This document describes the ATD-2 benefits mechanism used to assess the Phases 1 and 2 IADS capabilities and field evaluation conducted at CLT since September 2017. The ATD-2 benefits mechanism mainly consists of surface metering and overhead stream insertion. This document provides detailed calculation methods of major benefit metrics, such as fuel savings, gas emissions savings, and engine runtime reduction, which can be obtained through surface metering, gate hold of Approval Request (APREQ) flights prior to pushback, and the renegotiation of release time while taxiing. As of March 31, 2020, it is estimated that 5,075,981 pounds of fuel savings and 15,634,022 pounds of CO2 emission reduction have been achieved so far, with a reduction of 3,832 hours in total engine runtime. The amount of CO2 savings is estimated to be equivalent to planting 116,254 urban trees. The pre- and post-metering comparison results using FAA’s Aviation System Performance Metrics (ASPM) data have also shown that the surface metering had no negative impact on the on-time arrival performance of both outbound and inbound flights at CLT.

ATD-2↗

NASA NTRS2020

ATD-2 Benefits Mechanism

NASA has been developing and demonstrating a suite of decision support capabilities for integrated arrival, departure, and surface (IADS) operations in a metroplex environment. The effort is being made in three phases, under NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project, through a close partnership with the Federal Aviation Administration (FAA), air carriers, airport, and general aviation community. The Phase 1 Baseline IADS capabilities provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, tactical surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. The Phase 2 Fused IADS capabilities include the fusion of strategic and tactical surface metering, Atlanta Center airspace tactical scheduling, Electronic Flight Data (EFD) integration, Terminal Flight Data Manager (TFDM) Terminal Publication (TTP) prototype, and Mobile App for General Aviation (GA) community. In the Phase 2 field evaluation, strategic surface metering provides advance notice of metering and additional stability to the assigned gate holds. The users of the IADS system in Phases 1 and 2 include the personnel at Charlotte Douglas International Airport (CLT) air traffic control tower, American Airlines ramp tower, CLT terminal radar approach control (TRACON), and Washington and Atlanta Center. This document describes the ATD-2 benefits mechanism used to assess the Phases 1 and 2 IADS capabilities and field evaluation conducted at CLT since September 2017. The ATD-2 benefits mechanism mainly consists of surface metering and overhead stream insertion. This document provides detailed calculation methods of major benefit metrics, such as fuel savings, gas emissions savings, and engine runtime reduction, which can be obtained through surface metering, gate hold of Approval Request (APREQ) flights prior to pushback, and the renegotiation of release time while taxiing. As of April 30, 2020, it is estimated that 5,097,173 pounds of fuel savings and 15,699,292 pounds of CO2 emission reduction have been achieved so far, with a reduction of 3,831 hours in total engine runtime. The amount of CO2 savings is estimated to be equivalent to planting 116,739 urban trees. The pre- and post-metering comparison results using FAA’s Aviation System Performance Metrics (ASPM) data have also shown that the surface metering had no negative impact on the on-time arrival performance of both outbound and inbound flights at CLT.

ATD-2↗

NASA NTRS2021

ATD-2 Phase 3 Benefits Mechanism

ATD-2 Phase 3↗

NASA NTRS2006

Construction and Resource Utilization Explorer (CRUX): Implementing Instrument Suite Data Fusion to Characterize Regolith Hydrogen Resources

CRUX is a modular suite of geophysical and borehole instruments combined with display and decision support system (MapperDSS) tools to characterize regolith resources, surface conditions, and geotechnical properties. CRUX is a NASA-funded Technology Maturation Program effort to provide enabling technology for Lunar and Planetary Surface Operations (LPSO). The MapperDSS uses data fusion methods with CRUX instruments, and other available data and models, to provide regolith properties information needed for LPSO that cannot be determined otherwise. We demonstrate the data fusion method by showing how it might be applied to characterize the distribution and form of hydrogen using a selection of CRUX instruments: Borehole Neutron Probe and Thermal Evolved Gas Analyzer data as a function of depth help interpret Surface Neutron Probe data to generate 3D information. Secondary information from other instruments along with physical models improves the hydrogen distribution characterization, enabling information products for operational decision-making.

in situ resource utilization (ISRU)↗

NASA NTRS2016

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗

NASA NTRS2005

Development of the Surface Management System Integrated with CTAS Arrival Tools

The Surface Management System (SMS) developed by NASA Ames Research Center in coordination with the Federal Aviation Administration (FAA) is a decision support tool to help tower traffic coordinators and Ground/Local controllers in managing and controlling airport surface traffic in order to increase capacity, efficiency, and flexibility. SMS provides common situation awareness to personnel at various air traffic control facilities such as airport traffic control towers (ATCT s), airline ramp towers, Terminal Radar Approach Control (TRACON), and Air Route Traffic Control Center (ARTCC). SMS also provides a traffic management tool to assist ATCT traffic management coordinators (TMCs) in making decisions such as airport configuration and runway load balancing. The Build 1 of the SMS tool was installed and successfully tested at Memphis International Airport (MEM) and received high acceptance scores from ATCT controllers and coordinators, as well as airline ramp controllers. NASA Ames Research Center continues to develop SMS under NASA s Strategic Airspace Usage (SAU) project in order to improve its prediction accuracy and robustness under various modeling uncertainties. This paper reports the recent development effort performed by the NASA Ames Research Center: 1) integration of Center TRACON Automation System (CTAS) capability with SMS and 2) an alternative approach to obtain airline gate information through a publicly available website. The preliminary analysis results performed on the air/surface traffic data at the DFW airport have shown significant improvement in predicting airport arrival demand and IN time at the gate. This paper concludes with recommendations for future research and development.

Jung, Yoon C.↗

NASA NTRSDate not supplied

Objective Measurement Assessment of Departure Advisories for Ramp Controllers from a Human-In-The-Loop Simulation

NASA has developed and demonstrated an integrated arrival, departure, and surface concept and technology for efficient air traffic management in busy terminal environments under the Airspace Technology Demonstration 2 (ATD-2) subproject. In April/May 2019, NASA conducted a human-in-the-loop (HITL) simulation with ramp and tower controllers having experience at Dallas/Fort Worth International Airport (DFW). The purpose of this HITL was to evaluate the impacts of various surface metering goals in ramp operations at DFW and test new features of the ATD-2 ramp controller decision support tools. This paper evaluates the quantitative metrics from the simulation results related to airport performance and surface metering given various departure scheduling advisories for ramp controllers. The objective measurements compared include the controller’s compliance with the target times for pushback and spot arrival, the number of metered flights, aircraft gate hold and taxi time, runway throughput, and the number of aircraft on the surface. The simulation results show that there were no statistically significant benefits from surface metering at DFW for airport performance due to several simulation artifacts notably different from real operations. Considering controller workload and situation awareness, following either gate pushback or spot arrival advisory could be a better metering option than utilizing both advisories when surface metering is applied at DFW.

airport ramp traffic control decision support↗

NASA NTRS2005

Using Dynamic Simulations and Automated Decision Tools to Design Lunar Habitats

This paper describes the role of transient simulations, heuristic techniques, and closed loop integrated control in designing and sizing habitat life support systems. The integration of these three elements allows for more accurate requirements to be derived in advance of hardware choices. As a test case, we used a typical lunar surface habitat. Large numbers of habitat configurations were rapidly tested and evaluated using automated decision support tools. Through this process, preliminary sizing for habitat life support systems were derived. Our preliminary results show that by using transient simulations and closed loop control , we substantially reduced the system mass required to meet mission goals. This has greater implications for general systems analyses and for life support systems. It is likely that transient models, realtime integrated control, and other analyses capable of capturing the uncertainties of systems can be useful for systems analyses much earlier in the system development life cycle than has previously been considered.

Bell, Scott↗