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NASA NTRS2018

Overview of NASA's Air Traffic Management - eXploration (ATM-X) Project

Projected increases in new vehicle types, new missions, and the continual growth in traditional (e.g., airlines, general aviation) aviation will require changes to the current air traffic system, particularly to accommodate the desire of operators to be more involved in air traffic decisions. To address these challenges, the National Airspace System needs to undergo a transformation to a more scalable, flexible, user-focused system that addresses safety and security requirements and resiliency for current and new users. A system designed to integrate modular software services, provided by users, third parties and government for air traffic management functions, will be scalable and more easily allow modernization and for collaboration between users and service providers. ATM-X is responding to NASA's pivot towards integrating projected new, diverse entrants into the NAS, while also leveraging NASA's prior ATM achievements that continue to improve traditional airspace operations. This project is a two-phased approach to conduct research and focused evaluations to assess the feasibility of a service-based approach and to identify critical design considerations to enable airspace access for new entrants, integrated with current traditional operations. Phase 1 research will be conducted to determine what is needed to reach the ATM-X goals based on specific use-cases to enable large-scale, passenger-carrying Urban Air Mobility operations in a metroplex environment, and also to improve traditional operations in the Northeast Region leveraging mature NASA technologies. Some of these evaluations will be conducted in simulations and field activities. Phase 2 will build upon Phase 1 towards more defined, focused research and field demonstrations in real-world environments to integrate multiple elements of a scalable, service-based ATM-X concept.

air traffic management↗
NASA NTRS2018

Simulation Evaluations of an Autonomous Urban Air Mobility Network Management and Separation Service

This paper presents an initial implementation of an autonomous Urban Air Mobility network management and aircraft separation service for urban airspace that does 1) departure and arrival scheduling across the network, 2) continuous trajectory management to ensure safe separation between aircraft, and 3) seamless integration with traditional operations. The highly-autonomous AutoResolver algorithm developed for traditional aviation was extended to provide these capabilities. An evaluation of this initial implementation was conducted in fast-time simulations using a dense, two-hour traffic scenario with Urban Air Mobility aircraft flying between a network of 20 vertiports in the Dallas-Fort Worth metroplex. When the spatial separation was reduced from 0:3nmi to 0:1nmi, the total de- lay decreased by 7:3%; when the temporal separation was reduced from 60s to 45s, the total delay decreased by 28:4%. The total number of conflict resolutions decreased by 26% and 17%, respectively. Furthermore, when a scheduling horizon greater than the duration of UAM flights was used (50min), most conflicts were resolved pre-departure producing ground delay. By comparison, when a shorter scheduling horizon was used (8min), most conflicts were resolved post-departure generating airborne delay. For all scheduling and separation constraints tested, AutoResolver prevented loss of separation from occurring. Urban Air Mobility operations have the ability to revolutionize how people and goods are transported and this paper presents initial research focusing on the high levels of autonomy required for an airspace system capable of scaling to handle significantly higher densities of aircraft.

Bosson, Christabelle S.↗
NASA NTRS2018

Simulation Evaluations of an Autonomous Urban Air Mobility Network Management and Separation Service

This presents an initial implementation of an autonomous Urban Air Mobility network management and aircraft separation service for urban airspace that does 1) departure and arrival scheduling across the network, 2) continuous trajectory management to ensure safe separation between aircraft, and 3) seamless integration with traditional operations. The highly-autonomous AutoResolver algorithm developed for traditional aviation was extended to provide these capabilities. An evaluation of this initial implementation was conducted in fast-time simulations using a dense, two-hour traffic scenario with Urban Air Mobility aircraft flying between a network of 20 vertiports in the Dallas-Fort Worth metroplex. When the spatial separation was reduced from 0:3 nmi (nautical miles) to 0:1nmi, the total delay decreased by 7:3 percent...

Bosson, Christabelle S.↗
NASA NTRS2015

Identifying Key Issues and Potential Solutions for Integrated Arrival, Departure, Surface Operations by Surveying Stakeholder Preferences

NASA's Aeronautics Research Mission Directorate (ARMD) collaborates with the FAA and industry to provide concepts and technologies that enhance the transition to the next-generation air-traffic management system (NextGen). To facilitate this collaboration, ARMD has a series of Airspace Technology Demonstration (ATD) sub-projects that develop, demonstrate, and transitions NASA technologies and concepts for implementation in the National Airspace System (NAS). The second of these sub-projects, ATD-2, is focused on the potential benefits to NAS stakeholders of integrated arrival, departure, surface (IADS) operations. To determine the project objectives and assess the benefits of a potential solution, NASA surveyed NAS stakeholders to understand the existing issues in arrival, departure, and surface operations, and the perceived benefits of better integrating these operations. NASA surveyed a broad cross-section of stakeholders representing the airlines, airports, air-navigation service providers, and industry providers of NAS tools. The survey indicated that improving the predictability of flight times (schedules) could improve efficiency in arrival, departure, and surface operations. Stakeholders also mentioned the need for better strategic and tactical information on traffic constraints as well as better information sharing and a coupled collaborative planning process that allows stakeholders to coordinate IADS operations. To assess the impact of a potential solution, NASA sketched an initial departure scheduling concept and assessed its viability by surveying a select group of stakeholders for a second time. The objective of the departure scheduler was to enable flights to move continuously from gate to cruise with minimal interruption in a busy metroplex airspace environment using strategic and tactical scheduling enhanced by collaborative planning between airlines and service providers. The stakeholders agreed that this departure concept could improve schedule predictability and suggested several key attributes that were necessary to make the concept successful. The goals and objectives of the planned ATD-2 sub-project will incorporate the results of this stakeholder feedback.

integrated arrival/departure/surface operations↗
NASA NTRS2014

A Novel Application of TMA to Converging Runway Operations in a Simulated NextGen Environment

In 2013, the Airspace Operations Laboratory at NASA Ames Research Center conducted a human-in-the-loop simulation that examined the feasibility of applying a number of Next Generation Air Transportation System (NextGen) solutions to complex arrival operations in and around the New York metroplex. The delivery of arrivals to Newark Liberty International Airport (EWR) was the focus of this simulation, which involved extending the Terminal Sequencing and Spacing (TSS) scheduling capability to precisely schedule arrivals to intersecting runways 22 Left and 11. An important enabler for the concept was the availability of a dependent runway scheduler that was able to coordinate arrival times between aircraft landing on intersecting runways. At the time of the study, there was no functionality within the TSS scheduler to automatically create the dependent runway schedules. Instead, a Traffic Management Coordinator (TMC) manually created a de-conflicted schedule, which allowed for the concept to be tested as well as provided valuable insight into the tool requirements for a dependent runway scheduler. Throughout the course of preparations for the simulation, the individual serving as the TMC developed a number of strategies and procedures for manually adjusting the Scheduled Time of Arrival (STA) of the EWR arrivals in order to ensure that adequate spacing was provided between runway 22L and 11 arrival pairs. This paper describes the strategies and procedures that were developed and details how they were successfully applied during the simulation. Results will also be presented that shed additional light on exactly how the schedules were manipulated and their impact on delivery performance and safety. Ideas for additional TSS enhancements and next steps, based on participant feedback, will also be presented.

Homola, Jeffrey↗
NASA NTRSDate not supplied

Ground Stop Adjuster: A Machine Learning Approach to Improve Air Traffic Management Initiatives

Traffic Management Initiatives (TMIs) play a crucial role in balancing demand and capacity within the U.S. National Airspace System (NAS). In current practice, traffic management coordinators (TMCs) determine and issue TMIs and recent research has explored the use of machine learning tools to aid the TMCs. However, most studies have primarily focused on a particular type of TMI, i.e., Ground Delay Programs (GDPs) due to their higher rate of occurrence and longer duration. This study investigates a machine learning approach for monitoring and adjusting a different type of TMI, i.e., Ground Stop (GS), aiming to assist human decision-makers with accurate, consistent, and timely recommendations. Using data from three major airports in the New York metroplex, we evaluated models that predict GS parameters, such as duration and scope. Our results demonstrate that using data from all airports in the NY metroplex and increasing feature granularity improve the prediction accuracy of the ML models.

Farzan Masrour Shalmani↗
NASA NTRS2019

Automated Scenario Generation for Meeting Human-in-the-Loop Simulation Requirements

A two-step automated Multi-Aircraft Control System traffic scenario generation process for Human-in-the-Loop evaluations of air traffic management concepts is described. The first step of the two-step process employs the scenario generation capability currently available in NASA's Air Traffic Management Testbed. The second step refines the scenario by filtering flights from the traffic scenario based on route length, cruise speed, cruise altitude, entry time and the desired ratio of internal to external flights. A solution for achieving the desired ratio of internal to external flights, where internal flights are shorter flights and external flights are longer flights based on a distance threshold, is described. Finally, schedulers are described for shaping the hourly arrival traffic count as a function of time in response to airport capacity constraint or for increasing the traffic demand with respect to the available arrival capacity. Results generated for arrival traffic to the four major airports in the New York Metroplex on a busy day using the two-step procedure are discussed. These results show that traffic scenarios for Multi-Aircraft Control System that meet the Human-in-the-Loop and fast-time simulation requirements can be created automatically following the procedures described in the paper. The automated process will improve the accuracy and efficiency by eliminating the tedious manual process for scenario generation.

Automated Scenario Generation↗
NASA NTRS2019

Automated Scenario Generation for Meeting Human-In-The-Loop Simulation Requirements

A two-step automated Multi-Aircraft Control System traffic scenario generation process for Human-in-the-Loop evaluations of air traffic management concepts is described. The first step of the two-step process employs the scenario generation capability currently available in NASA's Air Traffic Management Testbed. The second step refines the scenario by filtering flights from the traffic scenario based on route length, cruise speed, cruise altitude, entry time and the desired ratio of internal to external flights. A solution for achieving the desired ratio of internal to external flights, where internal flights are shorter flights and external flights are longer flights based on a distance threshold, is described. Finally, schedulers are described for shaping the hourly arrival traffic count as a function of time in response to airport capacity constraint or for increasing the traffic demand with respect to the available arrival capacity. Results generated for arrival traffic to the four major airports in the New York Metroplex on a busy day using the two-step procedure are discussed. These results show that traffic scenarios for Multi-Aircraft Control System that meet the Human-in-the-Loop and fast-time simulation requirements can be created automatically following the procedures described in the paper. The automated process will improve the accuracy and efficiency by eliminating the tedious manual process for scenario generation.

Automated Scenario Generation↗
NASA NTRS2018

Operational Impact of the Baseline Integrated Arrival, Departure, and Surface System Field Demonstration

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known as Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. The ATD-2 field demonstration is organized into three phases. Phase I illustrates a Baseline IADS demonstration and includes all components of ATD-2 running in operational environments. Subsequent phases will fuse together strategic scheduling components as well as take into account metroplex considerations. This paper describes the baseline IADS system that was deployed at the end of 2017 and is continuing to run as part of the ATD-2 demonstration taking place at Charlotte-Douglas International Airport (CLT). The primary areas of deployment and system use are in the CLT Air Traffic Control Tower, CLT TRACON, CLT American Airlines ramp tower, Washington Center facility and American Airlines Integration Operations Center (IOC). In addition to describing the functions and capabilities that are part of the baseline IADS system, this paper also provides metrics regarding operational use as well as initial benefits metrics. Benefit metrics continue to be collected and aggregated across the areas of system delay, throughput, taxi time, fuel burn savings, and emissions savings. Furthermore, benefits as a result of common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are described. The overall benefit of improved predictability and efficiency as a result of the baseline IADS system demonstration is also discussed.

operational system↗
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 NTRS2015

Benefit Assessment for Metroplex Tactical Runway Configuration Management (mTRCM) in a Simulated Environment

The System-Oriented Runway Management (SORM) concept is a collection of capabilities focused on a more efficient use of runways while considering all of the factors that affect runway use. Tactical Runway Configuration Management (TRCM), one of the SORM capabilities, provides runway configuration and runway usage recommendations, and monitoring the active runway configuration for suitability given existing factors. This report focuses on the metroplex environment, with two or more proximate airports having arrival and departure operations that are highly interdependent. The myriad of factors that affect metroplex opeations require consideration in arriving at runway configurations that collectively best serve the system as a whole. To assess the metroplex TRCM (mTRCM) benefit, the performance metrics must be compared with the actual historical operations. The historical configuration schedules can be viewed as the schedules produced by subject matter experts (SMEs), and therefore are referred to as the SMEs' schedules. These schedules were obtained from the FAA's Aviation System Performance Metrics (ASPM) database; this is the most representative information regarding runway configuration selection by SMEs. This report focused on a benefit assessment of total delay, transit time, and throughput efficiency (TE) benefits using the mTRCM algorithm at representative volumes for today's traffic at the New York metroplex (N90).

Phojanamongkolkij, Nipa↗
NASA NTRS2011

TPSAS-NF1676L-12441-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗
NASA NTRS2011

TPSAS-NF1676L-12263-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗
NASA NTRS2018

A Data-Driven Analysis of a Tactical Surface Scheduler

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.

Tactical Surface Scheduler↗
NASA NTRS2018

A Data-Driven Analysis of a Tactical Surface Scheduler

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.

Tactical Surface Scheduler↗