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Design principles and algorithms for automated air traffic management

This paper presents design principles and algorithm for building a real time scheduler. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high altitude airspace far from the airport and low altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time.

Erzberger, Heinz↗

Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

Strategy↗

Human Factors Research Considerations for Terminal Area Urban Air Mobility Operations

In this presentation, we discuss the human factors research challenges from introducing greater levels of automation in a future air transportation concept called Urban Air Mobility (UAM). UAM is an air transportation concept that aims to provide air transportation services to the daily commuter, as well as emergency response and package delivery. The principal innovation over current day large air transport system is the greater distribution of important safety functions to automated and human agents; these functions include air traffic management, traditionally an air traffic controller responsibility. A central aspect of UAM is the development of an automated air traffic manager, whose primary responsibility is to approve airspace access for vehicle operators. Vehicle operator roles may include onboard and remote pilots, as well as a human manager who will supervise an entire fleet. Alternatively, both fleet manager and vehicle operators can be merged into a single role – a feasible option if UAM aircraft are autonomous. In lieu of tower controllers, vertiport managers, with the assistance of automation, will manage arrival and departure schedules between vertiports, as well as supervise surface operations. Our approach here will be to introduce use cases currently being developed by NASA, and then provide preliminary definitions for each of the roles introduced above and how coordination between them can be configured to support the operations within the use cases described. Subsequently, we review the tools and interfaces being developed to support the various roles. To conclude, we present current human factors work related to defining the roles above and suggest future work to advance the UAM concept.

trial planning↗

Development of a Safety Hazards Risk Assessment Tool for Uncrewed Aircraft System Traffic Management during Preflight Planning

Tremendous growth in the uncrewed and remotely piloted vehicle market is expected in low-altitude, uncontrolled airspace, resulting in potential decreases in safety without systems that support monitoring, assessing, and mitigating risk. At NASA, the System-Wide Safety (SWS) project has been developing a suite of data-driven tools to predict hazards so that the potential risks that these hazards pose can be mitigated. Services to predict various hazards have been developed, including battery capacity, proximity to static obstacles, population risks, global positioning system signal strength, radio frequency spectrum interference risk, and vertiport congestion. These services can monitor hazards along a flight path and if any risks posed by these hazards exceed a threshold, the uncrewed aircraft system (UAS) fleet manager can be alerted to mitigate the risk by modifying the flight path, changing the scheduled departure or arrival times, and/or diverting the vehicle to an alternate vertiport. These services were originally developed to monitor and assess risks during flight, but they have been adapted to assess hazard risks prior to departure so that a fleet manager can evaluate the potential risks for a fleet of UAS along their planned flight paths. These services have been integrated into a prototype tool called the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD), developed at NASA Ames Research Center. The tool consists of a dashboard which provides a comprehensive overview for a number of risks and a map display that shows the details of the hazards along each flight’s path. Based on the findings from three previous studies, the SDSP-CD has been updated with new design elements and functions. In this paper, we describe lessons learned from the previous studies, changes made to the interface, and the feedback received during a follow-up usability study. Overall, participants reported that there is a substantial benefit of having a fleet manager use a consolidated dashboard to assess hazards for the vehicles in their fleet and to provide situational awareness to potential risks so that they can be mitigated prior to flight. Once the SDSP-CD matures, it will need to be integrated into flight and mission planning tools. Some initial thoughts on how this integration should be accomplished are shared in this paper. Finally, the functional differences between preflight vs. in-flight risk assessment and the differences in fleet manager vs. UAS pilot roles that may require different information and user interactions are discussed.

preflight↗

Evaluation of the Terminal Area Precision Scheduling and Spacing System for Performance-Based Navigation Arrivals

The growth of global demand for air transportation has put increasing strain on the nation's air traffic management system. To relieve this strain, the International Civil Aviation Organization has urged all nations to adopt Performance-Based Navigation (PBN), which can help to reduce air traffic congestion, decrease aviation fuel consumption, and protect the environment. NASA has developed a Terminal Area Precision Scheduling and Spacing (TAPSS) system that can support increased use of PBN during periods of high traffic, while supporting fuel-efficient, continuous descent approaches. In the original development of this system, arrival aircraft are assigned fuel-efficient Area Navigation (RNAV) Standard Terminal Arrival Routes before their initial descent from cruise, with routing defined to a specific runway. The system also determines precise schedules for these aircraft that facilitate continuous descent through the assigned routes. To meet these schedules, controllers are given a set of advisory tools to precisely control aircraft. The TAPSS system has been evaluated in a series of human-in-the-loop (HITL) air traffic simulations during 2010 and 2011. Results indicated increased airport arrival throughput up to 10 over current operations, and maintained fuel-efficient aircraft decent profiles from the initial descent to landing with reduced controller workload. This paper focuses on results from a joint NASA and FAA HITL simulation conducted in 2012. Due to the FAA rollout of the advance terminal area PBN procedures at mid-sized airports first, the TAPSS system was modified to manage arrival aircraft as they entered Terminal Radar Approach Control (TRACON). Dallas-Love Field airport (DAL) was selected by the FAA as a representative mid-sized airport within a constrained TRACON airspace due to the close proximity of a major airport, in this case Dallas-Ft Worth International Airport, one of the busiest in the world. To address this constraint, RNAV routes and Required Navigation Performance with the particular capability known as Radius-to-Fix (RNP-RF) approaches to a short final were used. The purpose of this simulation was to get feedback on how current operations could benefit with the TAPSS system and also to evaluate the efficacy of the advisory tools to support the broader use of PBN in the US National Airspace System. For this NASA-FAA joint experiment, an Air Traffic Control laboratory at NASA Ames was arranged to simulate arrivals into DAL in Instrument Meteorological Conditions utilizing parallel dependent approaches, with two feeder positions that handed off traffic to one final position. Four FAA controllers participated, alternately covering these three positions. All participants were Full-Performance Level terminal controllers and members of the National Air Traffic Controllers Association. During the simulation, PBN arrival operations were compared and contrasted in three conditions. They were the Baseline, where none of the TAPSS systems TRACON controller decision support advisories were provided, the Limited Advisories, reflecting the existing but dormant capabilities of the current terminal automation equipment with providing a subset of the TAPSS systems advisories; numerical delay, landing sequence, and runway assignment information, and the Full Advisories, with providing the following in addition to the ones in the Limited condition; trajectory slot markers, timelines of estimated times of arrivals and sched

Performance based navigation↗

Dynamic Routes for Arrivals in Weather (DRAW)

A brief overview of the ATD-3 DRAW tool for assisting Traffic Management Coordinators with rerouting flights impacted by convective weather in a arrival- metered air traffic environment.

Weather Avoidance, TBFM, Scheduling, TMC, Arrival ↗

Evaluation of Scheduling Methods for Multiple Runways

Several scheduling strategies are analyzed in order to determine the most efficient means of scheduling aircraft when multiple runways are operational and the airport is operating at different utilization rates. The study compares simulation data for two and three runway scenarios to results from queuing theory for an M/D/n queue. The direction taken, however, is not to do a steady-state, or equilibrium, analysis since this is not the case during a rush period at a typical airport. Instead, a transient analysis of the delay per aircraft is performed. It is shown that the scheduling strategy that reduces the delay depends upon the density of the arrival traffic. For light traffic, scheduling aircraft to their preferred runways is sufficient; however, as the arrival rate increases, it becomes more important to separate traffic by weight class. Significant delay reduction is realized when aircraft that belong to the heavy and small weight classes are sent to separate runways with large aircraft put into the 'best' landing slot.

Bolender, Michael A.↗

Enhancing the Traffic Management Advisor's Schedule by Time Advance

A time advance algorithm associated with the scheduling functionalities of the Traffic Management Advisor (TMA) for arrival flights is presented and evaluated. The algorithm enhances TMA's meter fix schedule by advancing the flights' Scheduled Time of Arrival (STA) by an amount that minimizes their systemic operating cost. The systemic operating cost leverages the inherent trade-off of time and fuel efficiency resident in the cost index of modern flight management systems. The resulting STAs are achievable by speeding up the leading flights from their desired nominal speed profiles. A key advantage of this approach is that it reduces systemic delay to tight groupings of arriving aircraft as well as increases sustained throughput of the operation. A fast-time, Monte Carlo simulation that emulates TMA's scheduling functionalities is performed for arrival flights to the Phoenix Airport to quantify the benefit of the time advance algorithm. Results show consistent time saving benefits, ranging from 3 to 50 minutes for 112 flights with varying levels of traffic congestion.

arrival traffic management↗

Reducing Departure Delays for Adjacent Center Airports using Time-Based Flow Management Scheduler: Checkbox On or Off?

The Federal Aviation Administration (FAA) has enhanced the Time-Based Flow Management (TBFM) scheduling tool with a "Checkbox ON" vs. "OFF" function which allows Traffic Management Coordinators (TMCs) to make room in a crowded arrival stream for a departure. When scheduling a departure, having the checkbox ON can delay the Scheduled Times of Arrivals (STAs) of the airborne flights upstream of the TBFM freeze horizons and can compress these flights to their minimum required spacing, thereby creating a slot for a departure. Hence, having the checkbox ON can reduce the frequent ground delays of aircraft departing near high volume airports but can increase delays for airborne arrivals. A Human-in-the-Loop (HITL) simulation compared arrival and departure delays to Newark Airport (EWR) with the checkbox ON vs. OFF as the default position. Three other conditions in this HITL involved various National Airspace System (NAS)-wide approaches for timely delivery of aircraft to the TBFM region. These conditions were: Baseline, using current Mile-in-Trail (MIT) spacing restrictions; Integrated Demand Management (IDM), where all aircraft were given departure times (Expect Departure Clearance Times, or EDCTs), ultimately based on the EWR Airport Arrival Rate; and IDM plus Required Time of Arrival (RTA), a flight deck tool which allowed some aircraft to meet a controlled time of arrival to the TBFM area more precisely. Results showed that the checkbox tool was powerful: with the checkbox ON, departure delays decreased and airborne delays increased, as predicted. However, assuming that the cost ratio of a minute of airborne delay to a minute of departure delay is in the range of 1.2 to 3, as commonly indicated by the literature, checkbox ON and checkbox OFF conditions showed approximately equal total delay costs, i.e., the cost of delays in the air balanced the cost of the delay on the ground. The three scheduling conditions also had approximately equal total delay costs, although a simulation artifact may have reduced the delays in the Baseline condition. In the debrief following the simulation, the TMCs concluded that the checkbox should be used flexibly depending on the current delay situation, and suggested modifications to the checkbox tool which would help them use it in this way, along with enhanced training. The relatively similar total cost of both checkbox default options in this simulation indicates that this might be a fruitful approach, and replace the necessity to have the checkbox rigidly set to either ON or OFF.

departure delay↗

Analyzing Double Delays at Newark Liberty International Airport (EWR)

When weather or congestion impacts the National Airspace System, multiple different Traffic Management Initiatives can be implemented, sometimes with unintended consequences. One particular perceived inequity that is commonly identified is in the interaction between Ground Delay Programs (GDPs) and time based scheduling of internal departures by the Traffic Management Advisor (TMA) (now operationally superseded by the FAA's the Time-Based Flow Management system). Internal departures under TMA scheduling can take large GDP delays, followed by large TMA scheduling delays, because they cannot easily fit into the arrival flow at the runway. In this paper we examine the causes of these double delays through an analysis of arrival operations at Newark Liberty International Airport (EWR) from June to August 2010. TMA scheduling delays are found to be generally higher than TMA airborne metering delays, regardless of prior GDP delays. Depending on how the double delay is defined, between 42 and 62 of all internal departures in GDP and TMA scheduling experienced double delays in this period. A deep dive into the data reveals that contributors to double delays include upstream flights departing before their Expect Departure Clearance Times (EDCTs); differences in the rates used for setting EDCTs and TMA Scheduled Times of Arrival; differences in the arrival demand expected based on EDCTs and the arrival demand entering TMA; and shorter en route times between takeoff and entry into TMA than assumed in the calculation of flight EDCTs, all of which undermine the sequencing and spacing underlying flight EDCTs. Double delays are also found to coincide with periods in which the virtual runway arrival queue being served by a TMA is large, there are periods of high demand relative to capacity, and there are high airborne metering delays. Data mining techniques are used to confirm that each of these factors contribute to the occurrence of double delay andor high internal departure scheduling delay across three months of data from June to August 2010. Predictors of the occurrence of double delay and high TMA scheduling delay are built using logistic regression, providing prediction accuracies of 69 and 73, respectively.

traffic flow management↗

Methodology to Define Delivery Accuracy Under Current Day ATC Operations

In order to enable arrival management concepts and solutions in a NextGen environment, ground- based sequencing and scheduling functions have been developed to support metering operations in the National Airspace System. These sequencing and scheduling algorithms as well as tools are designed to aid air traffic controllers in developing an overall arrival strategy. The ground systems being developed will support the management of aircraft to their Scheduled Times of Arrival (STAs) at flow-constrained meter points. This paper presents a methodology for determining the undelayed delivery accuracy for current day air traffic control operations. This new method analyzes the undelayed delivery accuracy at meter points in order to understand changes of desired flow rates as well as enabling definition of metrics that will allow near-future ground automation tools to successfully achieve desired separation at the meter points. This enables aircraft to meet their STAs while performing high precision arrivals. The research presents a possible implementation that would allow delivery performance of current tools to be estimated and delivery accuracy requirements for future tools to be defined, which allows analysis of Estimated Time of Arrival (ETA) accuracy for Time-Based Flow Management (TBFM) and the FAA's Traffic Management Advisor (TMA). TMA is a deployed system that generates scheduled time-of-arrival constraints for en- route air traffic controllers in the US. This new method of automated analysis provides a repeatable evaluation of the delay metrics for current day traffic, new releases of TMA, implementation of different tools, and across different airspace environments. This method utilizes a wide set of data from the Operational TMA-TBFM Repository (OTTR) system, which processes raw data collected by the FAA from operational TMA systems at all ARTCCs in the nation. The OTTR system generates daily reports concerning ATC status, intent and actions. Due to its availability, ease of use, and vast collection of data across several airspaces it was determined that the OTTR data set would be the best method to utilize moving forward with this analysis. The particular variables needed for further analysis were determined along with the necessary OTTR reports, by working closely with the repository team additional analysis reports were developed that provided key ETA and STA information at the freeze horizon. One major benefit of the OTTR data is that using the correct reports the data across several airports could be analyzed over large periods of time. The OTTR data processes the TBFM data daily and is stored in various formats across several airspaces. This allowed us to develop our own parsing methods and raw data processing that would not rely on other computationally expensive tools that perform more in depth analysis of similar sets of data. The majority of this work consisted of the development of the ability to filter flights to create a subset of flights that could be considered undelayed, which is defined as a flight at the freeze horizon with an ETA and STA difference that was minimal or close to zero. This was a broad method that allowed the consideration of a large data set which consisted of all the traffic across a two month period in 2013, the hottest and coldest months, arriving into four airports: George Bush Intercontinental, Denver International, Los Angeles International, and Phoenix Sky Harbor.

delivery accuracy↗

Feasibility Criteria for Interval Management Operations as Part of Arrival Management Operations

Interval Management (IM) is a future airborne spacing concept that aims to provide more precise inter-aircraft spacing to yield throughput improvements and greater use of fuel efficient trajectories for arrival and approach operations. To participate in an IM operation, an aircraft must be equipped with avionics that provide speeds to achieve and maintain an assigned spacing interval relative to another aircraft. It is not expected that all aircraft will be equipped with the necessary avionics, but rather that IM fits into a larger arrival management concept developed to support the broader mixed-equipage environment. Arrival management concepts are comprised of three parts: a ground-based sequencing and scheduling function to develop an overall arrival strategy, ground-based tools to support the management of aircraft to that schedule, and the IM tools necessary for the IM operation (i.e., ground-based set-up, initiation, and monitoring, and the flight-deck tools to conduct the IM operation). The Federal Aviation Administration is deploying a near-term ground-automation system to support metering operations in the National Airspace System, which falls within the first two components of the arrival management concept. This paper develops a methodology for determining the required delivery precision at controlled meter points for aircraft that are being managed to a schedule and aircraft being managed to a relative spacing interval in order to achieve desired flow rates and adequate separation at the meter points.

Levitt, Ian M.↗

Exact and Heuristic Algorithms for Runway Scheduling

This paper explores the Single Runway Scheduling (SRS) problem with arrivals, departures, and crossing aircraft on the airport surface. Constraints for wake vortex separations, departure area navigation separations and departure time window restrictions are explicitly considered. The main objective of this research is to develop exact and heuristic based algorithms that can be used in real-time decision support tools for Air Traffic Control Tower (ATCT) controllers. The paper provides a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the SRS problem, but may prove unusable for application in real-time environment due to large computation times for moderate sized problems. We next propose a second algorithm that uses heuristics to restrict the search space for the DP based algorithm. A third algorithm based on a combination of insertion and local search (ILS) heuristics is then presented. Simulation conducted for the east side of Dallas/Fort Worth International Airport allows comparison of the three proposed algorithms and indicates that the ILS algorithm performs favorably in its ability to find efficient solutions and its computation times.

safe & surface operations↗

Effect of Uncertainty on Deterministic Runway Scheduling

Active runway scheduling involves scheduling departures for takeoffs and arrivals for runway crossing subject to numerous constraints. This paper evaluates the effect of uncertainty on a deterministic runway scheduler. The evaluation is done against a first-come- first-serve scheme. In particular, the sequence from a deterministic scheduler is frozen and the times adjusted to satisfy all separation criteria; this approach is tested against FCFS. The comparison is done for both system performance (throughput and system delay) and predictability, and varying levels of congestion are considered. The modeling of uncertainty is done in two ways: as equal uncertainty in availability at the runway as for all aircraft, and as increasing uncertainty for later aircraft. Results indicate that the deterministic approach consistently performs better than first-come-first-serve in both system performance and predictability.

Gupta, Gautam↗

Airspace Technology Demonstration 2 (ATD-2) Phase 2 Technology Description Document (TDD)

This Technology Description Document (TDD) provides an overview of the technology for the Phase 1 Baseline and Phase 2 Fused demonstrations of the Integrated Arrival, Departure, and Surface (IADS) prototype system of the National Aeronautics and Space Administration’s (NASA) Airspace Technology Demonstration 2 (ATD-2) project, which has been demonstrated since October of 2017 at Charlotte Douglas International Airport (CLT). Development, integration, and field demonstration of relevant technologies of the IADS system directly address recommendations made by the Next Generation Air Transportation System (NextGen) Integration Working Group (NIWG) on Surface and Data Sharing and the Surface Collaborative Decision Making (Surface CDM) concept of operations developed jointly by the Federal Aviation Administration (FAA) and aviation industry partners. NASA has been developing the IADS traffic management system under the ATD-2 project in coordination with the FAA, flight operators, CLT airport operators, and the National Air Traffic Controllers Association (NATCA). The primary goal of ATD-2 is to improve the predictability and operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation’s most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 project is a 5-year research activity beginning in 2015 and extending through 2020. The Phase 1 Baseline IADS capability resulting from the ATD-2 research has been demonstrated at the CLT airport since the beginning of October 2017. Phase 1 provided data exchange and integration with the initial demonstration of the integrated system of strategic and tactical scheduling, collaborative tactical surface metering, tactical departure scheduling to an en route meter point and overhead stream insertion, initial integration of a TFDM SWIM prototype feed, and an early implementation prototype of a Terminal Flight Data Manager (TFDM) Electronic Flight Data (EFD) system. The strategic surface scheduling element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 The Phase 2 Fused IADS system provided substantial updates to baseline IADS Demonstration capability. Improvements were made to the IADS modeler; tactical surface scheduling, and metering; tactical departure scheduling for overhead stream insertion; Electronic Flight Data (EFD) and the integration with the FAA Advanced Electronic Flight Strip (AEFS); RTC/RMTC, and departure trajectories. New capabilities included a TFDM SWIM prototype feed and delivery of IADS data via the TFDM Terminal Publication (TTP) service of the FAA’s SWIM system; strategic surface scheduling and metering as well as fusion with tactical surface metering; integration and ingestion of data from TTP-connected Mobile App and texting industry for General Aviation (GA) flights; and expansion of airspace deployments to include adjacent Center automation, in particular interface with the Atlanta Center (ZTL) arrival metering TBFM system to evaluate pre-scheduling of flights. Improvements in Data Analysis and System Health (DASH) monitoring and updates were completed as well.

Talebi, Ehsan↗

Galileo: Challenges enroute to Jupiter

The Galileo spacecraft is now on its three-year direct Earth-to-Jupiter transfer trajectory. Jupiter arrived (Probe entry) is scheduled for 2:05 pm PST, December 7, 1995. The Galileo Probe will be the first human-made object to enter the atmosphere of an outer planet, while the Orbiter will be the first artificial satellite of an outer planet. A two-year Jupiter orbital mission is planned. Following launch on October 18, 1989, Galileo spent just over three years executing its Venus-Earth-Earth Gravity Assist (VEEGA) mission phase to achieve the heliocentric energy necessary to reach Jupiter. Midway through its Earth-to-Earth leg, on October 29, 1991, Galileo became the first spacecraft to encounter an asteroid. Six months earlier in April 1991, the spacecraft's high-gain antenna (HGA) failed to deploy properly. The special guidance, navigation, and control (GN&C) problems associated with a 20-month campaign of maneuvers to free the stuck antenna and successfully perform the asteroid encounter without it are described. The overall mission and spacecraft status are also reported.

O'Neil, William J.↗

Evaluation of the Terminal Sequencing and Spacing System for Performance Based Navigation Arrivals

NASA has developed the Terminal Sequencing and Spacing (TSS) system, a suite of advanced arrival management technologies combining timebased scheduling and controller precision spacing tools. TSS is a ground-based controller automation tool that facilitates sequencing and merging arrivals that have both current standard ATC routes and terminal Performance-Based Navigation (PBN) routes, especially during highly congested demand periods. In collaboration with the FAA and MITRE's Center for Advanced Aviation System Development (CAASD), TSS system performance was evaluated in human-in-the-loop (HITL) simulations with currently active controllers as participants. Traffic scenarios had mixed Area Navigation (RNAV) and Required Navigation Performance (RNP) equipage, where the more advanced RNP-equipped aircraft had preferential treatment with a shorter approach option. Simulation results indicate the TSS system achieved benefits by enabling PBN, while maintaining high throughput rates-10% above baseline demand levels. Flight path predictability improved, where path deviation was reduced by 2 NM on average and variance in the downwind leg length was 75% less. Arrivals flew more fuel-efficient descents for longer, spending an average of 39 seconds less in step-down level altitude segments. Self-reported controller workload was reduced, with statistically significant differences at the p less than 0.01 level. The RNP-equipped arrivals were also able to more frequently capitalize on the benefits of being "Best-Equipped, Best- Served" (BEBS), where less vectoring was needed and nearly all RNP approaches were conducted without interruption.

terminal sequencing↗

ATD-2 Field Evaluation of Pre-Departure Trajectory Option Set Reroutes in North Texas Metroplex

The NASA Airspace Technology Demonstration-2 Phase 3 capabilities extend Integrated Arrival, Departure and Surface scheduling to a Metroplex environment where multiple airports are interacting and sharing resources along the terminal boundary. The Phase 3 coordinated scheduling provides pre-departure reroute recommendations to flight operators which reduce delay caused by terminal restrictions. This paper reports results of the Phase 3 Stormy 2021 Field Evaluation conducted between November 2020 and September 2021 in the North Texas Metroplex. During the field evaluation NASA partnered with the FAA, American Airlines, Southwest Airlines, and Envoy Airlines to evaluate Phase 3 capabilities in an operational environment. The benefits results are provided as delay savings metrics measured in time and converted to fuel and emissions savings using detailed fuel flow models provided by flight operators.

ATD-2 Field Evaluation, Trajectory Option Set, Pre↗