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At least 1,063 records · Page 59

In-Flight Evaluation of the Traffic Aware Planner on the NASA HU-25A Guardian Aircraft

NASA’s Traffic Aware Planner (TAP) software is a research-prototype decision support tool that provides pilots with time- and fuel-saving route recommendations that optimize their current trajectory. The software runs on a first-of-a-kind system architecture onboard three aircraft in revenue service conducting operational evaluations with a major domestic airline. Therefore, significant NASA-internal testing is required prior to releasing the software to the partner airline. This paper describes a flight test plan that exercises the functionality of the TAP software in a representative operational environment, describes the system architecture developed and implemented for the NASA Langley HU-25A Guardian aircraft to support the test objectives, presents outcomes of the flight test campaign, and discusses use cases that demonstrate the value of flight testing for this activity.Research into flight path optimization of transport aircraft conducted by the National Aeronautics and SpaceAdministration (NASA) has produced an operational concept known as Traffic Aware Strategic Aircrew Requests(TASAR) [1, 2]. This near-term concept [3] provides the aircrew with a flight deck decision support tool known asthe Traffic Aware Planner (TAP). The TAP software leverages a growing number of information sources on the flightdeck to make time- and fuel-saving route optimization recommendations to the aircrew while en route. The aircrewcan then use the suggestions provided by the tool to make route change requests with a greater likelihood of acceptanceby air traffic control (ATC). Since TASAR is a concept intended for the current operational environment, it isintentionally designed to have no safety-critical impact or require any changes to current Federal AviationAdministration (FAA) rules and procedures [4, 5].The research prototype TAP system [6–8], explained further in Section III.C, continually incorporates up-to-dateaircraft state data from onboard avionics, as well as the latest position of surrounding traffic, the most recent windforecast, and the most recent convective weather forecast, in order to calculate candidate trajectory modifications thatimprove upon the current active route. These trajectories account for user-selectable objective functions [3] of reducedfuel burn, reduced flight time, or an airline-derived combination of factors known as trip cost. Previous analyses andsimulations have estimated substantial savings for airlines employing this technique within the U.S. National AirspaceSystem (NAS) [9–11]. Operational evaluations with Alaska Airlines seek to validate these projected benefits usingmeasured data while simultaneously providing benefits to the airline [12, 13].The TAP software has undergone a number of human-in-the-loop simulations [14] and flight test activities[15–17] in order to validate the operational concept, evaluate human factors considerations (e.g., workload, usability,distraction, etc.), and to assess the ability of the software to function in a representative operational environment (e.g.,connected to live avionics data, using in-flight internet connectivity, etc.). However, these simulations and flight testcampaigns did not account for the hardware architecture implemented on the three aircraft for Alaska Airlines’operational evaluations of the TAP software. Therefore, a need was identified to thoroughly test the functionality ofthe software in a similar hardware architecture to that of the partner airline’s aircraft. Information regarding testapparatus and environments used to evaluate TAP prior to testing on the HU-25A can be found in reference [18].A campaign of flight trials on a NASA aircraft, the HU-25A Guardian, was conducted to ensure that the researchprototype TAP system functions well in a configuration similar to the Alaska Airlines aircraft prior to deployment.This airborne, networked environment enables an assessment of the operational factors unique to the flight environment. Additionally, this activity evaluated the effectiveness and benefit of new TAP functionality andoperation in a relevant flight environment while allowing the rapid prototyping of new concepts and features.This paper is organized as follows: Section II discusses the details of the flight test plan, flight profiles, and theduties of personnel involved with conducting flight operations. Section III describes the test platform, avionicsequipage, and system architecture. Section IV presents a discussion of results, and Section V contains concludingremarks.

Underwood, Matthew C.↗

Initial TASAR Operations Onboard Alaska Airlines

NASA and Alaska Airlines jointly conducted an operational evaluation of NASA’s Traffic Aware Strategic Aircrew Request (TASAR) concept. Featuring a NASA-developed cockpit automation tool, the Traffic Aware Planner (TAP), and leveraging the emerging “connected aircraft” architecture, TASAR enables pilots to identify route changes compatible with nearby traffic and airspace constraints that improve flight efficiency and are more likely to receive Air Traffic Control approval. TASAR was developed in anticipation of saving fuel and flight time, thereby providing immediate and pervasive benefits to the aircraft operator. Following a previously reported, extensive program of integration and preliminary in-flight testing, the operational evaluation of TASAR in revenue service by Alaska Airlines took place from July 2018 to April 2019. This paper describes the operational evaluation, the methodology for quantifying operational benefits, preliminary benefit results, and other unexpected impacts of TASAR operations during revenue flights. Based on the subset of data available at publication, preliminary estimated benefits averaged about $92 per flight across all flights including those without benefit. Identified factors indicate the estimated benefit per flight was likely a conservative estimate. Benefit categories including home runs, cumulative small gains, and plan validation benefits are illustrated with specific examples observed during the operational evaluation.

Wing, David J.↗

ACES Study of DAA-Mitigated UAS Operations SC-228 Requirements Sub Group

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements as well as the safety substantiation and end-to-end assessment of DAA system performance. A recent study conducted using NASA's ACES (Airspace Concept Evaluation System) simulation capability begins to address questions surrounding the development of draft MOPS for DAA systems by assessing DAA performance in a NAS-wide context. ACES analyses were conducted to determine the impact of varying elements of UAS pilot performance and uncertainty mitigations on DAA system performance. Simulations were conducted with recorded cooperative and non-cooperative VFR (Visual Flight Rules) traffic to accurately model UAS encounters with other NAS traffic (ATC (Air Traffic Control) being responsible for separation with other IFR (Instrument Flight Rules) aircraft) and with roughly 25, 000 simulated UAS operations The number of Loss of Well Clear (LoWC) events were recorded across the range of independent variables: pilot response time, horizontal LoWC prediction buffer and horizontal LoWC resolution buffer. The number of LoWC events was compared to the unmitigated case (without the benefit of a DAA system) to determine the resultant risk-ratio for each of 8 simulation conditions. The parameter trades presented by the resultant DAA system performance (risk ratio) will be used by SC 228 to inform decisions about future requirements development and validation efforts.

Detect-and-Avoid↗

Automated Discovery of Flight Track Anomalies

As new technologies are developed to handle the complexities of the Next Generation Air Transportation System (NextGen), it is increasingly important to address both current and future safety concerns along with the operational, environmental, and efficiency issues within the National Airspace System (NAS). In recent years, the Federal Aviation Administration’s (FAA) safety offices have been researching ways to utilize the many safety databases maintained by the FAA, such as those involving flight recorders, radar tracks, weather, and many other high- volume sensors, in order to monitor this unique and complex system. Although a number of current technologies do monitor the frequency of known safety risks in the NAS, very few methods currently exist that are capable of analyzing large data repositories with the purpose of discovering new and previously unmonitored safety risks. While monitoring the frequency of known events in the NAS enables mitigation of already identified problems, a more proactive approach of finding unidentified issues still needs to be addressed. This is especially important in the proactive identification of new, emergent safety issues that may result from the planned introduction of advanced NextGen air traffic management technologies and procedures. Development of an automated tool that continuously evaluates the NAS to discover both events exhibiting flight characteristics indicative of safety-related concerns as well as operational anomalies will heighten the awareness of such situations in the aviation community and serve to increase the overall safety of the NAS. This paper discusses the extension of previous anomaly detection work to identify operationally significant flights within the highly complex airspace encompassing the New York area of operations, focusing on the major airports of Newark International (EWR), LaGuardia International (LGA), and John F. Kennedy International (JFK). In addition, flight traffic in the vicinity of Denver International (DEN) airport/airspace is also investigated to evaluate the impact on operations due to variances in seasonal weather and airport elevation. From our previous research, subject matter experts determined that some of the identified anomalies were significant, but could not reach conclusive findings without additional supportive data. To advance this research further, causal examination using domain experts is continued along with the integration of air traffic control (ATC) voice data to shed much needed insight into resolving which flight characteristic(s) may be impacting an aircraft's unusual profile. Once a flight characteristic is identified, it could be included in a list of potential safety precursors. This paper also describes a process that has been developed and implemented to automatically identify and produce daily reports on flights of interest from the previous day.

Matthews, Bryan↗

Future Surface Decision Support Overview

This presentation presents the capabilities of the Airspace Technology Demonstration 2 (ATD-2) Integrated Arrival, Departure, and Surface (IADS) system as a surface decision support tool for users, including Air Traffic Control (ATC) personnel working at the tower and Center facilities and airline Ramp personnel. The ATD-2 IADS capabilities include data exchange and integration, modeling and scheduling, surface metering, and departure scheduling for overhead stream insertion of constrained flights.

Surface Decision Support↗

Prognostics As-A-Service: A Scalable Cloud Architecture for Prognostics

Comprehensive aircraft system health-state awareness is critical for maintaining safe, efficient growth in global operations, enabling higher levels of autonomy, and facilitating new forms of aviation. Maintainers, vehicle operators, air traffic controllers, dispatchers, pilots, autonomous systems, and other decision-makers must have reliable real-time knowledge of the vehicle health, the health of its critical composite systems, predictions of how health changes with time, and forecasts of how its capabilities change with health degradation to preserve safety and efficiency. Providing this information in a reliable manner in computationally constrained environments and across a wide range of vehicles and systems continues to be a challenge. This challenge can be partially resolved through cloud computing, where the execution of prognostic and diagnostic algorithms is performed on a network of remote servers hosted on the internet. NASA is developing a cloud computing service, Prognostics As-A-Service (PaaS), that explores the feasibility and challenges of cloud-enhanced prognostics. Though such a system has broad applicability, this research effort is focused on aviation applications.

Prognostics↗

Autonomous Operating System (AOS)

The Autonomy Operating System (AOS) is a software system that enables core capabilities for the autonomous operations for an unmanned aircraft. It is based on the NASA cFS system and provides a higher-level layer of infrastructure and applications for the execution of flight plans, natural-language communication with Air Traffic Control, Diagnostics, Prognostics, and contingency planning.

Lowry, Michael R.↗

Flight Awareness Collaboration Tool

NASA is developing the Flight Awareness Collaboration Tool (FACT) to support airline and airport operations during winter storms. The goal is to reduce flight delays and cancellations due to winter weather. FACT concentrates relevant information from the Internet and FAA databases on one screen for easy access. It provides collaboration tools for those managing the winter weather event including the airline operations center, airport authority (runway treatment), the Federal Aviation Administration air traffic control tower, and de-icing operators. Prediction tools are being added to improve FACT capabilities including one that anticipates changes in airport departure rates from weather forecasts. Future work includes adding more automated capabilities and collaborating with industry.

Mogford, Richard H.↗

Pattern-Based Genetic Algorithm for Airborne Conflict Resolution

NASA has developed the Autonomous Operations Planner (AOP) airborne decision support tool to explore advanced air traffic control concepts that include delegating separation authority to aircraft. A key element of the AOP is its strategic conflict resolution (CR) algorithm, which must resolve conflicts while maintaining conformance with traffic flow management constraints. While a previous CR algorithm, which focused on broader flight plan optimization objectives as a part of conflict resolution, had successfully been developed, new research has identified the need for resolution routes the users find more acceptable (i.e., simpler and more intuitive). A new CR algorithm is presented that uses a combination of pattern-based maneuvers and a genetic algorithm to achieve these new objectives. Several lateral and vertical maneuver patterns are defined and the application of the genetic algorithm explained. A new approach to defining a conflicted fitness function using estimates of the local conflict region around a conflicted trajectory is also presented. Preliminary performance characteristics of the implemented algorithm are provided.

Vivona, Robert A.↗

Flight Awareness Collaboration Tool Development

NASA is developing the Flight Awareness Collaboration Tool (FACT) to support airline and airport operations during winter storms. The goal is to reduce flight delays and cancellations due to winter weather. FACT concentrates relevant information from the Internet and FAA databases on one screen for easy access. It provides collaboration tools for those managing the winter weather event including the airline operations center, airport authority (runway treatment), the Federal Aviation Administration air traffic control tower, and de-icing operators. Prediction tools are being added to improve FACT capabilities including one that anticipates changes in airport departure rates from weather forecasts. We have formed two user teams from affected airports to guide the design and evaluate the web-based prototype. Future work includes adding more automated capabilities and conducting a simulation to evaluate FACT in a realistic environment.

Mogford, Richard↗

UAS Concept of Operations and Vehicle Technologies Demonstration

In 2017 and 2018, under National Aeronautics and Space Administration (NASA) sponsorship, the New York Unmanned Aircraft Systems (UAS) Test Site and Northeast UAS Airspace Integration Research (NUAIR) Alliance conducted a year-long research project that culminated in a UAS technology flight demonstration. The research project included the creation of a concept of operations, and development and demonstration of UAS technologies. The concept of operations was focused on an unmanned aircraft transiting from cruise through Class E airspace into a high-density urban terminal environment. The terminal environment in which the test was conducted was Griffiss International Airport, under Syracuse Air Traffic Control (ATC) approach control and Griffiss control tower. Employing an Aurora Centaur optionally piloted aircraft (OPA), this project explored six scenarios aimed at advancing UAS integration into the National Airspace System (NAS) under both nominal and off-nominal conditions. Off-nominal conditions were defined to include complete loss of the communications link between the remote pilot’s control station on the ground and the aircraft. The off-nominal scenarios that were investigated included lost-link conditions with and without link recovery, an automated ATC initiated go-around, autonomous rerouting around a dynamic airspace obstruction (in this case simulated weather), and autonomous taxi operations to clear the runway.

Swieringa, Kurt↗

TPSAS-NF1676L-12168-DND

The Federal Aviation Administration’s Surveillance and Broadcast Services Program Office considers Interval Management (IM) to be one of the three key, near-term applications to make use of ADS-B-In, the receiving and processing of Automatic Dependent Surveillance – Broadcast data on-board an aircraft. Interval Management is used to describe a wide range of operational applications and uses of airborne spacing technology. Interval Management makes use of improved scheduling and sequencing capabilities for the air traffic controllers (ATC) and precise, relative spacing of aircraft, to improve airport throughput, increase the use of Optimized Profile Descents (OPD), and reduce tactical controller workload. The IM applications are subdivided into two categories: one where the flight crew is authorized to manage their speed to achieve the IM goal while the controller retains separation responsibility and a second where the flight crew takes responsibility for both managing speed but also for separation from the specified target aircraft. The former is referred to as Interval Management-Spacing (IM-S) and the latter as Interval Management-Delegated Separation (IM-DS). For the past 10 years NASA has been working on a specific IM application called Airborne Precision Spacing (APS). This concept has focused on increasing runway throughput while enabling OPDs. It is seen as a specific application within the IM class of applications. This talk will present the current state of the APS concept including support for dependent parallel runway operations and how NASA is working to have APS support the broader IM activities. Planned development and testing of APS, including extensions to support IM-DS and FAA-planned flight trials will be presented along with several up-coming simulations.

Bryan E Barmore↗

TPSAS-NF1676L-12329-DND

The Federal Aviation Administration’s Surveillance and Broadcast Services Program Office considers Interval Management (IM) to be one of the three key, near-term applications to make use of ADS-B-In, the receiving and processing of Automatic Dependent Surveillance – Broadcast data on-board an aircraft. Interval Management is used to describe a wide range of operational applications and uses of airborne spacing technology. Interval Management makes use of improved scheduling and sequencing capabilities for the air traffic controllers (ATC) and precise, relative spacing of aircraft, to improve airport throughput, increase the use of Optimized Profile Descents (OPD), and reduce tactical controller workload. The IM applications are subdivided into two categories: one where the flight crew is authorized to manage their speed to achieve the IM goal while the controller retains separation responsibility and a second where the flight crew takes responsibility for both managing speed but also for separation from the specified target aircraft. The former is referred to as Interval Management-Spacing (IM-S) and the latter as Interval Management-Delegated Separation (IM-DS). For the past 10 years NASA has been working on a specific IM application called Airborne Precision Spacing (APS). This concept has focused on increasing runway throughput while enabling OPDs. It is seen as a specific application within the IM class of applications. This talk will present the current state of the APS concept including support for dependent parallel runway operations and how NASA is working to have APS support the broader IM activities. Planned development and testing of APS, including extensions to support IM-DS and FAA-planned flight trials will be presented along with several up-coming simulations.

Brian T Baxley↗

An Examination of Two Non-Cooperative Detect and Avoid Well Clear Definitions

NASA’s Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. The present study explored the differential effects of two candidate non-cooperative Detect-and-Avoid Well Clear (DWC)definitions on pilot and system performance in a human-in-the-loop simulation. Active-duty UAS pilots were recruited to maintain DWC against representative Class 4 encounter types with a low size, weight, and power (SWaP) radar declaration range of 3.5 nautical miles (nmi). Objective performance indicated that pilots could consistently maintain DWC against non-cooperative intruders with either DWC candidate, with negligible differences in response times and separation performance against caution and warning-level threats. While losses of DWC were avoided at rates comparable to Phase 1 findings, pilots uploaded their responses to caution-level alerts over 5 seconds faster in the current setup relative to Phase 1. Encounters with faster closure rates were susceptible to shortened caution-level alert durations, especially when employing the DWC criterion with the additional ‘Tau’ (temporal) component. Consequently, caution-level threats frequently elevated to warning-level status (nearly twice as often with theTau candidate). The variable caution alert durations appeared to impact pilots’ coordination with air traffic control (ATC), as ATC approval rates were lower with the ‘Tau’and ‘Disc’ candidates relative to Phase 1 research. Ultimately, the increased alerting time enabled by the Disc candidate deemed it more suitable for any reductions to the assumed radar declaration range requirement, which was re-evaluated in a follow-on study. Findings from this study will inform Phase 2 Minimum Operational Performance Standards (MOPS)development for UAS with alternative surveillance equipment and performance capabilities.

Kevin J Monk↗

Upper E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a cooperative, service-based approach that provides services and capabilities in areas (e.g., Upper E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes partner feedback on the following concept elements: Upper E Traffic Management (ETM) planning processes, transit phase of operation, data sharing, time horizons for data sharing, and cooperative integration of military operations. An additional segment of the slides consists of an overview of the UAS Traffic Management (UTM) concept and its relationship to ETM.

Upper E↗

Upper E Traffic Management

This is a slide set as part of a meeting series with members of a working group aimed at the development of a concept that addresses needs and gaps in the management of high altitude airspace operations. This concept leverages elements developed through the UAS Traffic Management project with respect to a cooperative, service-based approach that provides services and capabilities in areas (e.g., Upper E airspace) that currently receive no or limited service from Air Traffic Control. This concept is meant to provide a safe, fair, and scalable approach to management of Upper E operations that reduces the burden on ATC while providing the flexibility and access desired by current and new users of the airspace. This set of slides includes a presentation of Communication, Navigation, and Surveillance assessments as they relate to the ETM environment, a review of Industry thoughts on equitable airspace access and associated rules of the road, and an initial presentation of the separation assurance process and related negotiation aspect.

Upper E↗

Evaluation, Analysis and Results of the DANTi Flight Test Data, the DAIDALUS Detect and Avoid Algorithm, and the DANTi Concept for Detect and Avoid in the Cockpit

The DAIDALUS Detect and Avoid Algorithm [1] was developed to address the operational needs of Unmanned Aerial Systems (UAS) and meet the Minimum Operational Performance Standards for Detect and Avoid [2]. The DANTi (Detect and Avoid iN the cockpit) concept [3], developed at the National Aeronautics and Space Administration (NASA) Langley Research Center, leverages advancements achieved in surveillance and Detect and Avoid technologies for unmanned aircraft systems as a safety enhancing capability for pilots of manned aircraft. Pilots operating under Visual Flight Rules and not receiving Air Traffic Control radar services rely on see and avoid to remain well clear of other aircraft and avoid collisions. The DANTi concept has been conceived as a safety enhancement capability to remain well clear and avoid potential collisions. The DANTi concept uses a traffic display to provide situational awareness, conflict detection, alerting, and guidance to remain well clear.

Detect and Avoid↗

Surface Trajectory-Based Operations (STBO) Client User Manual

This document serves as a user manual for the ATD-2 Surface Trajectory-Based Operations (STBO) Client (version 5.11) utilized by Air Traffic Control in the Tower. It describes the elements of the STBO Client interface and provides step-by-step instructions for using the tool. STBO Client functionality includes the display of live flight information, management of traffic restrictions, and prediction of expected traffic demand. The STBO Client is a component of the NASA Airspace Technology Demonstration 2 (ATD‑2) sub-project.

Louise Kay Morgan Ruszkowski↗