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NASA NTRS2014

Benefits Analysis of Multi-Center Dynamic Weather Routes

Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

NAS based Benefits Analysis↗
NASA NTRSDate not supplied

Detect and Avoid and Collision Avoidance Flight Test Results with ACAS Xr

In October 2023, the National Aeronautics and Space Administration (NASA) completed its Integration of Automated Systems flight test series, conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. Approximately half of the flight test was devoted to assessing the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. The ownship was equipped with ACAS Xr and the intruder was equipped with Automatic Dependent Surveillance-Broadcast (ADS-B). The test points were blocked by ACAS Xr configuration, with individual encounters varying the ownship speed (90 knots or 20 knots), the intruder designation (en-route, terminal area, or structured airspace), and method of RA execution (automated or manually executed). Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗
NASA NTRSDate not supplied

Detect and Avoid and Collision Avoidance Flight Test Results with ACAS Xr

In October 2023, the National Aeronautics and Space Administration (NASA) completed its Integration of Automated Systems flight test series, conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. Approximately half of the flight test was devoted to assessing the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. The ownship was equipped with ACAS Xr and the intruder was equipped with Automatic Dependent Surveillance-Broadcast (ADS-B). The test points were blocked by ACAS Xr configuration, with individual encounters varying the ownship speed (90 knots or 20 knots), the intruder designation (en-route, terminal area, or structured airspace), and method of RA execution (automated or manually executed). Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗
NASA NTRS2010

Generic Airspace Concepts and Research

The purpose of this study was to evaluate methods for reducing the training and memorization required to manage air traffic in mid-term, Next Generation Air Transportation System (NextGen) airspace. We contrasted the performance of controllers using a sector information display and NextGen automation tools while working with familiar and unfamiliar sectors. The airspace included five sectors from Oakland and Salt Lake City Centers configured as a "generic center" called "West High Center." The Controller Information Tool was used to present essential information for managing these sectors. The Multi Aircraft Control System air traffic control simulator provided data link and conflict detection and resolution. There were five experienced air traffic controller participants. Each was familiar with one or two of the five sectors, but not the others. The participants rotated through all five sectors during the ten data collection runs. The results addressing workload, traffic management, and safety, as well as controller and observer comments, supported the generic sector concept. The unfamiliar sectors were comparable to the familiar sectors on all relevant measures.

Mogford, Richard H.↗
NASA NTRS2013

Pilot and Controller Evaluations of Separation Function Allocation in Air Traffic Management

Two human-in-the-loop simulation experiments were conducted in coordinated fashion to investigate the allocation of separation assurance functions between ground and air and between humans and automation. The experiments modeled a mixed-operations concept in which aircraft receiving ground-based separation services shared the airspace with aircraft providing their own separation service (i.e., self-separation). Ground-based separation was provided by air traffic controllers without automation tools, with tools, or by ground-based automation with controllers in a managing role. Airborne self-separation was provided by airline pilots using self-separation automation enabled by airborne surveillance technology. The two experiments, one pilot-focused and the other controller-focused, addressed selected key issues of mixed operations, assuming the starting point of current-day operations and modeling an emergence of NextGen technologies and procedures. In the controller-focused experiment, the impact of mixed operations on controller performance was assessed at four stages of NextGen implementation. In the pilot-focused experiment, the limits to which pilots with automation tools could take full responsibility for separation from ground-controlled aircraft were tested. Results indicate that the presence of self-separating aircraft had little impact on the controllers' ability to provide separation services for ground-controlled aircraft. Overall performance was best in the most automated environment in which all aircraft were data communications equipped, ground-based separation was highly automated, and self-separating aircraft had access to trajectory intent information for all aircraft. In this environment, safe, efficient, and highly acceptable operations could be achieved for twice today's peak airspace throughput. In less automated environments, reduced trajectory intent exchange and manual air traffic control limited the safely achievable airspace throughput and negatively impacted the maneuver efficiency of self-separating aircraft through high-density airspace. In a test of scripted conflicts with ground-managed aircraft, flight crews of self-separating aircraft prevented separation loss in all conflicts with detection time greater than one minute. In debrief, pilots indicated a preference for at least five minute's alerting notice and trajectory intent information on all aircraft. When intent information on ground-managed aircraft was available, self-separating aircraft benefited from fewer conflict alerts and fewer required deviations from trajectory-based operations.

Wing, David↗
NASA NTRS2016

Function Allocation between Automation and Human Pilot for Airborne Separation Assurance

Maintaining safe separation between aircraft is a key determinant of the airspace capacity to handle air transportation. With the advent of satellite-based surveillance, aircraft equipped with the needed technologies are now capable of maintaining awareness of their location in the airspace and sharing it with their surrounding traffic. As a result, concepts and cockpit automation are emerging to enable delegating the responsibility of maintaining safe separation from traffic to the pilot; thus increasing the airspace capacity by alleviating the limitation of the current non-scalable centralized ground-based system. In this paper, an analysis of allocating separation assurance functions to the human pilot and cockpit automation is presented to support the design of these concepts and technologies. A task analysis was conducted with the help of Petri nets to identify the main separation assurance functions and their interactions. Each function was characterized by three behavior levels that may be needed to perform the task: skill, rule and knowledge based levels. Then recommendations are made for allocating each function to an automation scale based on their behavior level characterization and with the help of Subject matter experts.

Idris, Husni↗
NASA NTRS2019

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↗
NASA NTRS2016

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

ATD-3↗
NASA NTRS2014

Controller Inhibition of Automated Conflict Resolutions in a Maximum NextGen Condition

With the continued projection of increases in air traffic density, operations in the National Airspace System are expected to exceed human capabilities in the near future. In order to address the bottleneck of human workload capacity, highly automated safety-critical systems are under development to support air traffic controllers. A human-in-the-loop experiment examined controllers transition through four NextGen automation stages: Current-Day, Minimum, Moderate, and Maximum. Maximum NextGen simulated a fully automated environment where the automation was responsible for detecting and resolving conflicts within simulation parameters in high-density airspace. By allocating these tasks to the automation, the controllers task changed. The human moved to primarily a supervisory position- typically only regaining control over separation assurance tasks during conflict situations deferred by the automation. While tasks were allocated a-priori between the controller and automated agent, controllers maintained authority to inhibit the automation from interacting with particular aircraft. Preliminary work is complete, where significant differences were found in inhibition frequency between simulation participants. However, the contexts in which the controllers inhibited the automation, and their reasons for doing so, remain unclear. This analysis attempts to identity factors contributing to human controllers inhibition of the automation in the Maximum NextGen condition.

adaptable automation↗
NASA NTRS2013

Simulations of Continuous Descent Operations with Arrival-management Automation and Mixed Flight-deck Interval Management Equipage

Air traffic management simulations conducted in the Airspace Operations Laboratory at NASA Ames Research Center have addressed the integration of trajectory-based arrival-management automation, controller tools, and Flight-Deck Interval Management avionics to enable Continuous Descent Operations (CDOs) during periods of sustained high traffic demand. The simulations are devoted to maturing the integrated system for field demonstration, and refining the controller tools, clearance phraseology, and procedures specified in the associated concept of operations. The results indicate a variety of factors impact the concept's safety and viability from a controller's perspective, including en-route preconditioning of arrival flows, useable clearance phraseology, and the characteristics of airspace, routes, and traffic-management methods in use at a particular site. Clear understanding of automation behavior and required shifts in roles and responsibilities is important for controller acceptance and realizing potential benefits. This paper discusses the simulations, drawing parallels with results from related European efforts. The most recent study found en-route controllers can effectively precondition arrival flows, which significantly improved route conformance during CDOs. Controllers found the tools acceptable, in line with previous studies.

arrival management↗
NASA NTRS2016

Unmanned Aerial Systems Traffic Management (UTM): Safely Enabling UAS Operations in Low-Altitude Airspace

Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS flight operations. Given this, and understanding that the FAA faces a mandate to modernize the present air traffic management system through computer automation and significantly reduce the number of air traffic controllers by FY 2020, the FAA maintains that a comprehensive, yet fully automated UAS traffic management (UTM) system for low-altitude airspace is needed. The concept of UTM is to begin by leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today. Building on its legacy of work in air traffic management (ATM), NASA is working with industry to develop prototype technologies for a UAS Traffic Management (UTM) system that would evolve airspace integration procedures for enabling safe, efficient low-altitude flight operations that autonomously manage UAS operating in an approved low-altitude airspace environment. UTM is a cloud-based system that will autonomously manage all traffic at low altitudes to include UASs being operated beyond visual line of sight of an operator. UTM would thus enable safe and efficient flight operations by providing fully integrated traffic management services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning re-routing, separation management, sequencing spacing, and contingency management. UTM removes the need for human operators to continuously monitor aircraft operating in approved areas. NASA envisions concepts for two types of UTM systems. The first would be a small portable system, which could be moved between geographical areas in support of operations such as precision agriculture and public safety. The second would be a Persistent system, which would support low-altitude operations in an approved area by providing continuous automated coverage. Both would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. UTM is creating an airspace management tool that allows the ATM system to accommodate the number of UAS that will operate in the low altitude airspace. The analogy is just because we have a car, whether its autonomous or someone is driving, does not diminish the need for a road or road signs or rules of the road.

traffic management↗
NASA NTRS2013

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

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

ATC↗
NASA NTRS2023

Procedure Automation Rating Matrix

The National Aeronautics and Space Administration (NASA) Advanced Air Mobility (AAM) National Campaign (NC) is researching the means by which future Urban Air Mobility (UAM) aircraft will operate safely in an integrated and scalable airspace architecture. Consistent with this objective, the NASA NC Airspace Procedures team designed a matrix to evaluate UAM instrument flight procedure design, flyability and interoperability of candidate departure, enroute, and approach architectures in live flight or simulation. The Procedure Automation Rating Matrix (PARM) is a multi-dimensional rating scale designed to provide direct feedback from test pilots and operators to airspace procedure designers developing airspace constructs for the integration and scalability of AAM operations in the National Airspace System (NAS). The PARM is assessed using a hierarchical decision tree that guides the operator through a ten-point alpha-numeric rating scale initiated either with or without the use of automation.

National Campaign↗
NASA NTRS1997

Automation for Air Traffic Control: The Rise of a New Discipline

The current debate over the concept of Free Flight has renewed interest in automated conflict detection and resolution in the enroute airspace. An essential requirement for effective conflict detection is accurate prediction of trajectories. Trajectory prediction is, however, an inexact process which accumulates errors that grow in proportion to the length of the prediction time interval. Using a model of prediction errors for the trajectory predictor incorporated in the Center-TRACON Automation System (CTAS), a computationally fast algorithm for computing conflict probability has been derived. Furthermore, a method of conflict resolution has been formulated that minimizes the average cost of resolution, when cost is defined as the increment in airline operating costs incurred in flying the resolution maneuver. The method optimizes the trade off between early resolution at lower maneuver costs but higher prediction error on the one hand and late resolution with higher maneuver costs but lower prediction errors on the other. The method determines both the time to initiate the resolution maneuver as well as the characteristics of the resolution trajectory so as to minimize the cost of the resolution. Several computational examples relevant to the design of a conflict probe that can support user-preferred trajectories in the enroute airspace will be presented.

Erzberger, Heinz↗
NASA NTRS2010

Functional Allocation for Ground-Based Automated Separation Assurance in NextGen

As part of an ongoing research effort into functional allocation in a NextGen environment, a controller-in-the-loop study on ground-based automated separation assurance was conducted at NASA Ames' Airspace Operations Laboratory in February 2010. Participants included six FAA front line managers, who are currently certified professional controllers and four recently retired controllers. Traffic scenarios were 15 and 30 minutes long where controllers interacted with advanced technologies for ground-based separation assurance, weather avoidance, and arrival metering. The automation managed the separation by resolving conflicts automatically and involved controllers only by exception, e.g., when the automated resolution would have been outside preset limits. Results from data analyses show that workload was low despite high levels of traffic, Operational Errors did occur but were closely tied to local complexity, and safety acceptability ratings varied with traffic levels. Positive feedback was elicited for the overall concept with discussion on the proper allocation of functions and trust in automation.

Prevot, Thomas↗