ATD-2 Integrated Arrival/ Departure/Surface (IADS) System Software Version 4.x Releases and Notes
This document summarizes the software releases and capabilities delivered to CLT and/or DFW during the ATD-2 Phase 2 field evaluation.
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This document summarizes the software releases and capabilities delivered to CLT and/or DFW during the ATD-2 Phase 2 field evaluation.
This document summarizes the 5.x series of ATD-2 software releases to Charlotte-Douglas International Airport (CLT) and/or Dallas-Fort Worth International Airport (DFW) during ATD-2 Phase 3. This is Version 2 of the document that provides updates since the original document was released in August 2020.
This document summarizes the 6.x series of ATD-2 software releases to Dallas-Fort Worth International Airport (DFW) during ATD-2 Phase 3.
This document describes the Arrival Runway Model (ARM) Machine Learning (ML) service developed under the ATD-2 subproject as a reference implementation and released by NASA as Open Source software on github.
This document describes the Airport Configuration Prediction Model (ACPM) Machine Learning (ML) service developed under the ATD-2 subproject as a reference implementation and released by NASA as Open Source software on github.
This document describes the Departure Runway Model (DRM) Machine Learning (ML) service developed under the ATD-2 subproject as a reference implementation and released by NASA as Open Source software on github.
This document describes the Impeded (ITIM) and Unimpeded Taxi In Time Prediction Model (UTIM) Machine Learning (ML) services developed under the ATD-2 subproject as a reference implementation and released by NASA as Open Source software on github.
This document describes the Impeded (ITOM) and Unimpeded Taxi Out Time Prediction Model (UTOM) Machine Learning (ML) services developed under the ATD-2 subproject as a reference implementation and released by NASA as Open Source software on github.
This document contains the system specifications and requirements verification matrix for the Metroplex and TOS concepts developed during ATD-2 Phase 3. This document was updated in September 2021 for the final Phase 3 tech transfer delivery.
This document describes the Estimated ON Model (EON) Machine Learning (ML) services developed under the ATD-2 subproject as a reference implementation and released by NASA as Open Source software on github.
This work involves the development of a concept that enhances integrated metroplex arrival and departure coordination, determines the temporal (the use of time separation for aircraft sharing the same airspace resources) and spatial (the use of different routes or vertical profiles for aircraft streams at any given time) impact of metroplex traffic coordination within the National Airspace System (NAS), and quantifies the benefits of the most desirable metroplex traffic coordination concept. Researching and developing metroplex concepts is addressed in this work that broadly applies across the range of airspace and airport demand characteristics envisioned for NextGen metroplex operations. The objective of this work is to investigate, formulate, develop models, and analyze an operational concept that mitigates issues specific to the metroplex or that takes advantage of unique characteristics of metroplex airports to improve efficiencies. The concept is an innovative approach allowing the NAS to mitigate metroplex interdependencies between airports, optimize metroplex arrival and departure coordination among airports, maximize metroplex airport throughput, minimize delay due to airport runway configuration changes, increase resiliency to disruptions, and increase the tolerance of the system to degrade gracefully under adverse conditions such as weather, traffic management initiatives, and delays in general.
NASA has been collaborating with the Federal Aviation Administration (FAA) and aviation industry partners to develop and demonstrate new concepts and technologies for the Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. The primary goal of the ATD-2 project is to improve the predictability and the operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure and surface prediction, scheduling, and management systems. In the Phase 1 Baseline IADS Demonstration, the tactical surface scheduling capability and the user interfaces for ramp controllers and ramp traffic managers were implemented for ramp operations. The purpose of the tactical surface scheduling capability is to provide the airline ramp controller with aircraft pushback advisories that prevent surface congestion and to respond to surface and airspace constraints that become known over relatively short time horizons. For this purpose, the tactical surface metering tool first estimates the capacity of current and near-future runway resources from flight schedule and surveillance data. With demand forecasts and predicted taxi trajectories, this tool computes an efficient runway schedule of aircraft in the planning horizon based on their readiness, Earliest Off-Block Times (EOBTs), and a ration by schedule (RBS) rule. Details on the implementation of the Tactical Surface Metering tool will be provided in the full paper. Both pushback and recommended hold times advisories provided by this surface metering tool are shown on the user interfaces for the ramp controller and the ramp traffic manager, called Ramp Traffic Console (RTC) and Ramp Manager Traffic Console (RMTC), respectively. There is excess queue time in the system due to demand capacity imbalance, this time can be taken as a hold on the runway queue or at the gate and was referred to as the Metering Value. This metering value can be adjusted by the Ramp Manager in collaboration with Air Traffic Controller-Tower Traffic Management Coordinator (TMC). They selected a set of metering values as default values for the tool during human-in-the-loop simulation. As the metering value increases, there is a decrease in the gate hold and increase in the queue time at the runway. Procedures and Information needs related to managing the surface metering procedures were researched in the simulated environment. These procedures will be compared to the procedures adopted at Charlotte Douglas International Airport when the tools were deployed and adopted in November 2017 for one departure push bank per day. Feedback regarding initial issues, information needs such as the need to see EOBTs on the flight data tags and how they compare to scheduled times will also be discussed in the full paper. Initial results will be provided regarding the choice of the metering value and how it was adjusted on a daily basis and what procedures evolved will also be presented in the paper.
NASA's Airspace Technology Demonstration-2 (ATD-2) integrates arrival, departure, and surface operations to extend integrated traffic sequencing all the way from the gate to the overhead stream and back again for multi-airport, metroplex environments. A key concept of ATD-2 centers on surface scheduling that allows aircraft to taxi, climb, and insert within the overhead stream with minimal interruptions. A core principle is to allow aircraft to absorb delay at the gate prior to engine start in order to reduce overall fuel burn and emissions. To achieve these goals, it is necessary for the scheduler to properly balance the demand at the runway with the available capacity while also predicting accurate takeoff times. This paper provides a data-driven analysis of the runway demand capacity balancing and measures the accuracy of schedules that are generated while running in a live operational environment at the Charlotte Douglas International Airport. We found that using minimum-time wake vortex separation constraints to define runway capacity resulted in scheduling departure operations at a slightly higher rate than the runway was operating and we discovered a surprising relationship between the runway rate and the accuracy of the schedules.
NASA's Airspace Technology Demonstration-2 (ATD-2) integrates arrival, departure, and surface operations to extend integrated traffic sequencing all the way from the gate to the overhead stream and back again for multi-airport, metroplex environments. A key concept of ATD-2 centers on surface scheduling that allows aircraft to taxi, climb, and insert within the overhead stream with minimal interruptions. A core principle is to allow aircraft to absorb delay at the gate prior to engine start in order to reduce overall fuel burn and emissions. To achieve these goals, it is necessary for the scheduler to properly balance the demand at the runway with the available capacity while also predicting accurate takeoff times. This paper provides a data-driven analysis of the runway demand capacity balancing and measures the accuracy of schedules that are generated while running in a live operational environment at the Charlotte Douglas International Airport. We found that using minimum-time wake vortex separation constraints to define runway capacity resulted in scheduling departure operations at a slightly higher rate than the runway was operating and we discovered a surprising relationship between the runway rate and the accuracy of the schedules.
Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA) are investigating scheduling algorithms that will be a part of an integrated arrival and departure management system. Inha University, one of the Korean collaborators of KARI, developed an Extended First-Come First-Served (EFCFS) algorithm that is robust and efficient. However, since the EFCFS algorithm sequentially computes the schedule based on priority, the end results may not be optimal for system efficiency. The approach based on Mixed Integer Linear Programming (MILP) originally developed by NASA and modified by KARI is known to produce better schedules at the expense of computational cost. In this paper, the two different scheduling approaches are compared using common traffic scenarios and constraints at Incheon International Airport. Capabilities to apply weight class based wake turbulence runway separation minima and Miles-in-Trail (MIT) restrictions at selected meter fixes are added to the previously developed EFCFS scheduler. Based on historic data, 40 departures and 20 arrivals are chosen in a one-hour period and 100 scenarios were created by randomly assigning gate numbers, gate departure times, and runway landing times. With the current runway separation requirements, MILP resulted in about ten to twenty percent smaller average delays depending on the constraints. With artificially increased separation minima, the difference between MILP and EFCFS became more noticeable. However, the EFCFS was about ten times faster with smaller variations among different scenarios and constraints. The comparison suggests that the MILP-based algorithm has a small advantage at the current traffic level; however, has potential to be more effective in higher demand or severe weather situations. The EFCFS algorithm may be better suited for real-time applications or investigating larger scale scheduling problems.
This presentation describes the objectives and high level setup for the human-in-the-loop simulation of the integrated surface and airsapce simulation of the ATD-2 Integrated Arrival, Departure, Surface (IADS) system. The purpose of the simulation is to evaluate the functionality of the IADS system, including tactical surface scheduler, negotiation of departure times for the flights under Traffic Management Initiatives (TMIs), and data exchange between ATC Tower and airline Ramp. The same presentation was presented to serve the experiment review prior to the simulation.
NASA is conducting a field test of the Airspace Technology Demonstration2 (ATD-2) to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system. The IADS system was deployed to Charlotte Douglas International Airport (CLT) in 2017 for a three-year field evaluation. The Phase 1 field evaluation included tactical surface metering, which manages departure excess taxi time by tactically assigning gate holds. Phase 2 built upon the lessons learned from Phase 1 to extend surface metering into the strategic metering timeframes. In this paper, we describe the strategic metering capabilities of the ATD-2 IADS system and the operational results from CLT.
Data Exchange and Integration is necessary for progress towards an Integrated Arrival, Departure, and Surface (IADS) traffic management capability. In collaboration with the FAA, NASA has introduced new data exchange elements to Charlotte-Douglas International Airport air traffic facilities, including the American Airlines ramp, as part of the Airspace Technology Demonstration 2 (ATD2). This paper describes the new tools that deliver these elements, and the human factors impact of the tools as measured by post-bank surveys. Workload was unaffected by ATD2 tool use, and situational awareness was improved in the Tower and with Ramp controllers in the second round of surveys. Respondents described their tools as more helpful if they included ATD2 tools 1) in the Tower for insuring compliance for aircraft under a Traffic Management Initiative, 2) in the TRACON when actively used for many TRACON tasks, and 3) in the Ramp in the second round of surveys.