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NASA NTRS2018

ADS-B Mixed sUAS and NAS System Capacity Analysis and DAA Performance

Automatic Dependent Surveillance-Broadcast (ADS-B) technology was introduced more than twenty years ago to improve surveillance within the US National Airspace Space (NAS) as well as in many other countries. Via the NextGen initiative, implementation of ADS-B technology across the US is planned in stages between 2012 and 2025. ADS-B's automatic one second epoch packet transmission exploits on-board GPS-derived navigational information to provide position information, as well as other information including vehicle identification, ground speed, vertical rate and track angle. The purpose of this technology is to improve surveillance data accuracy and provide access to better situational awareness to enable operational benefits such as shorter routes, reduced flight time and fuel burn, and reduced traffic delays, and to allow air traffic controllers to manage aircraft with greater safety margins. Other than the limited amount of information bits per packet that can be sent, ADS-B's other hard-limit limitation is capacity. Small unmanned aircraft systems (sUAS) can utilize limited ADS-B transmission power, in general, thus allowing this technology to be considered for use within a combined NAS and sUAS environment, but the potential number and density of sUAS predicted for future deployment calls into question the ability of ADS-B systems to meet the resulting capacity requirement. Hence, studies to understand potential limitations of ADS-B to fulfill capacity requirements in various sUAS scenarios are of great interest. In this paper we, validate/improve on, previous work performed by the MITRE Corporation concerning sUAS power and capacity in a sUAS and General Aviation (GA) mixed environment. In addition, we implement its inherent media access control layer capacity limitations which was not shown in the MITRE paper. Finally, a simple detect and avoid (DAA) algorithm is implemented to display that ADS-B technology is a viable technology for a mixed NAS/sUAS environment even in proposed larger mixed density environments.

Matheou, Konstantin J.↗
NASA NTRS2018

ADS-B Mixed sUAS and NAS System Capacity Analysis and DAA Performance

Automatic Dependent Surveillance-Broadcast (ADS-B) technology was introduced more than twenty years ago to improve surveillance within the US National Airspace Space (NAS) as well as in many other countries. Via the NextGen initiative, implementation of ADS-B technology across the US is planned in stages between 2012 and 2025. ADS-B's automatic one second epoch packet transmission exploits on-board GPS-derived navigational information to provide position information, as well as other information including vehicle identification, ground speed, vertical rate and track angle. The purpose of this technology is to improve surveillance data accuracy and provide access to better situational awareness to enable operational benefits such as shorter routes, reduced flight time and fuel burn, and reduced traffic delays, and to allow air traffic controllers to manage aircraft with greater safety margins. Other than the limited amount of information bits per packet that can be sent, ADS-B's other hard-limit limitation is capacity. Small unmanned aircraft systems (sUAS) can utilize limited ADS-B transmission power, in general, thus allowing this technology to be considered for use within a combined NAS and sUAS environment, but the potential number and density of sUAS predicted for future deployment calls into question the ability of ADS-B systems to meet the resulting capacity requirement. Hence, studies to understand potential limitations of ADS-B to fulfill capacity requirements in various sUAS scenarios are of great interest. In this paper we, validate/improve on, previous work performed by the MITRE Corporation concerning sUAS power and capacity in a sUAS and General Aviation (GA) mixed environment. In addition, we implement its inherent media access control layer capacity limitations which was not shown in the MITRE paper. Finally, a simple detect and avoid (DAA) algorithm is implemented to display that ADS-B technology is a viable technology for a mixed NAS/sUAS environment even in proposed larger mixed density environments.

Matheou, Konstantin↗
NASA NTRS2018

Utility of Visual and Auditory Warning Alerting for Traffic Avoidance During UAS Operations

This presentation covers the results of a human-in-the-loop simulation that examined the effect of caution versus warning-level alerting in the context of Unmanned Aircraft System (UAS) operations in civil airspace. Minimum Operational Performance Standards (MOPS) are currently being developed by RTCA Special Committee 228 for UAS Detect-and-Avoid (DAA) systems. Input from subject matter experts and multiple research studies have informed display requirements for DAA systems aimed at supporting timely and appropriate pilot responses to collision hazards. DAA alerting is designed to inform pilots of potential threats to DAA "well clear"; the two highest alert levels - caution and warning - indicate how soon pilot action is required and whether there is adequate time to coordinate with the air traffic controller (ATC). Additional empirical support is needed to clarify the extent to which warning-level alerting impacts DAA task performance. The present study explores the differential effects of the auditory and visual cues provided by the DAA Warning alert, and performance implications compared to caution-only alerting are discussed.

detect and avoid↗
NASA NTRS2019

Flyover-Noise Reduction of Commercial Aircraft via Reduced Slat Deflections and Modified Flight Procedures

Current regulation and operation of commercial aircraft result in flyover noise that generates public protest from residents well outside the recognized noise footprint of modern airports. This noise issue was recently exacerbated by the implementation of NextGen air-traffic control which uses GPS-navigation for predictable flight paths and improved efficiency. A side-effect of the narrow flight corridors is a perceived increase in noise level and annoyance experienced by the residents directly under the flight paths. As a possible solution to the community noise issue, the feasibility of a lower slat deflections and modified flight procedures were explored. To document the maximum potential noise reduction, field measurements were conducted on the ground at locations before and after slat deployment. For safety considerations, the stall margin of a lower slat deflection was computed for a realistic geometry based on a modern commercial aircraft. The logistics of setting lower slat angles on current aircraft were also investigated through discussions with the FAA (Federal Aviation Administration) and aircraft manufacturers. The results suggest that community flyover noise could be reduced via lower slat deflections during early approach, but that modifying current aircraft would be difficult due to existing control systems and hurdles in certification. Alternatively, modifications to existing flight procedures could reduce the perceived noise of the NextGen flight patterns. For next generation commercial aircraft, reduced slat deflections could be considered if mandated by FAA noise requirements during early approach.

Storms, Bruce L.↗
NASA NTRS2016

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↗
NASA NTRS2018

Participant Training for a Flight Test Evaluation of Interval Management

Interval Management is a concept designed to be used by air traffic controllers and flight crews to more efficiently and precisely manage inter-aircraft spacing. NASA, in cooperation with Boeing, Honeywell, and United Airlines, tested an avionics prototype onboard flight test aircraft. A critical need was identified to train the pilots participating in the flight test prior to the first flight. This paper documents the flight training regimen that successfully trained the pilots on the Interval Management concepts and flight crew procedures and suggests potential improvements to future training regimens for industry use.

Roper, Roy↗
NASA NTRS2015

Measured Response for UAS Integration into the National Airspace System

The measured response (MR) is the response time of aircraft to Air Traffic Controller (ATCo) commands and clearances. The overall MR can be broken up into several components, including the pilot verbal latencies (MR1), the time between the end of an ATCo clearance and the beginning of the pilots read back, and the execution initiation latency (MR2), the time between the end of the ATCos clearance and when the pilot begins to execute a maneuver. The MR is a crucial concern for the integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) due to potentially greater latencies stemming from remote pilot communication and command execution. As a result, it is important to quantify what latencies in verbal responding and command execution are acceptable for safe and efficient operations in the NAS. The present studies begin to address these issues in a series of four simulations supported by the UAS Integration into the NAS program.

UAS in the NAS↗
NASA NTRS2015

A Heuristic Approach to Correlating ERAM Flight Data from Twenty Centers

Among its many other functions, the Federal Aviation Administration’s En Route Automation Modernization (ERAM) provides external systems with real-time air traffic data for flights in enroute airspace in the National Airspace System. It replaced the En Route Host computer and backup system used at 20 FAA Air Route Traffic Control Centers (Centers) nationwide. Among the new features of ERAM, its output data stream of flight plan and track data includes a unique identifier for a flight originating in any one of the 20 ERAM Centers. The unique identifier, called the Global Unique Flight Identifier (GUFI), is persistent across all the Centers that track the flight. However, certain factors make it difficult to correlate data using the GUFI. First, the value of the GUFI is only unique within a time window of seven days. Second, the GUFI is attached only to flight-plan related data messages. Finally, track positions reported by ERAM do not reference the GUFI. In order to correlate historical as well as real time flight-plan and position related ERAM data, an efficient, heuristic approach was developed, and a prototype was developed. The approach showed that the processing speed, through parallel processing, is sufficient to correlate ERAM data in real-time. As described in this paper, when there are multiple track positions reported from multiple Centers within a few seconds, each position is assigned with a weighted score to indicate the quality of the position relative to its last know position. The weighted score can be used to eliminate potentially duplicate track positions. The approach is database-agnostic, and can be implemented in a Big Data system such as an Apache Hadoop system, as well as in traditional database systems.

Correlating ERAM Flight Data↗
NASA NTRS2019

Reliability, Safety, and Performance for Two Aerospace Revolutions - UAS/ODM and Commercial Deep Space

Aerospace is in the midst of a renaissance, expanding on both the air and space side into major new commercial areas including unmanned air systems (UAS), on demand mobility (ODM), personal air vehicles (PAV), and commercial deep space. These new areas require, in the initial planning, consideration of new safety, reliability, and in some cases, enabling performance approaches for viability. For example, due to their huge numbers, if current accident rates prevail, UAS/ODM/PAV aircraft could crash at an unacceptable rate, causing life and property damage. Also, if humans in commercial space activities have serious health issues and/or there are unacceptable rocket viability issues/crash rates, these new, major markets (order of 1 trillion dollars per year) could be rapidly curtailed until agreeable and effective changes are instituted, producing additional expense, delay, and reduced revenue. This report addresses such safety and reliability issues and includes: performance enhancement possibilities such as an enabling Air Traffic Control System (ATC), crash proof vehicles, increased range for aero, space debris removal, and human health for space.

Crash Proof↗
NASA NTRS2015

Air Traffic Management Technology Demonstration (ATD-1) - Concept to 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 research presented provides an outline of the challenge of bringing time based scheduling to the terminal environment and the steps that were taken to bring the technology from concept to testing in an operational environment, and finally acquisition by the FAA. ATM Technology Demonstration-1 (ATD-1), is a set of technologies that provides an efficient solution for managing arrival aircraft beginning from just prior to top-of-descent and continuing down to the runway. The ATD-1 suite of technologies has been tested separately, and each has demonstrated benefits in throughput, delay, and fuel-efficiency. Together, the integration of terminal arrival tools allow arrival aircraft to safely fly closer together on more fuel-efficient routes to increase capacity, and reduce delay, fuel burn, noise, and greenhouse gas emissions.

DEMO↗
NASA NTRS2019

CNS Simulation Tool Development for Increasingly Complex Airspace Operation Evaluation

As unmanned aircraft operations continue to grow and new vehicles such as air taxi, supersonic aircraft and high-altitude long endurance aircraft seek access to the airspace, it is anticipated that National Airspace System (NAS) operations will increase in density and complexity. To manage the influx, demand and safe integration of these new aircraft and missions into the NAS, a careful evaluation of existing and new operational concepts, vehicle characteristics and technology performance is required. Communications, Navigation and Surveillance (CNS) technologies operating in the NAS have evolved to meet changing needs of the Air Traffic Control System and the vehicles operating in the airspace. Today's CNS systems have been architected to deliver critical services to a carefully designed airspace configuration and to serve airborne vehicles equipped with standardized systems that enable global air navigation. The introduction of new vehicles is projected to expand NAS operations beyond today's configuration to include a new breed of aircraft operating from non-conventional aerodromes, resulting in a mix of vehicles operating in the same airspace. To enable this expansion, it is anticipated that modeling and simulation will play an important role in the evaluation of new management concept of operations.In this regard, NASA is developing simulation capabilities that will enable the evaluation of new concepts of operation and CNS technology performance in an increasingly dense, high-tempo operational environment. The NASA Glenn Research Center is working on the development of CNS simulation capabilities intended to support the integrated evaluation of operational concepts and emerging technologies. This presentation describes simulation capability development efforts that, together with other simulation tools, will enable evaluation of new concepts and technologies for the integration of new vehicles and services into the NAS. [Also discussed: NASA Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART NAS)]

Surveillance↗
NASA NTRS2019

Evaluation of a Dynamic Weather-Avoidance Rerouting Tool in Adjacent-Center Arrival Metering

Dynamic Reroutes for Arrivals in Weather (DRAW) is a NASA-developed decision-support tool for Traffic Management Coordinators (TMCs) at the Federal Aviation Administration's Air Route Traffic Control Centers ("Centers"). DRAW proposes weather-avoidance reroutes for en route arrival flights subject to metering restrictions when transitioning into a busy terminal airspace. The prior DRAW study demonstrated that TMCs' use of DRAW promotes earlier reroutes of arrivals, and reduces the number of routes conflicting with weather in the Center. The present paper focuses on how DRAW benefits metering delivery accuracy when schedule freeze horizon distance was altered. A human-in-the-loop simulation was conducted at NASA Ames Research Center in October-November 2018, where retired TMCs and controllers performed simulated metering operations for southeast arrivals through the Atlanta and Jacksonville Centers to the Hartsfield-Jackson Atlanta International Airport during convective weather periods. Results demonstrated that DRAW use reduced the frequency of manual adjustments of Scheduled Times of Arrival and lowered TMC workload. DRAW use also made the metering accuracy, the number of reroute amendments after the freeze horizon, and the en route sector controller workload more robust to the effect of different freeze horizon distance.

Hayashi, Miwa↗
NASA NTRS2019

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.↗
NASA NTRS2014

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↗
NASA NTRS2014

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↗
NASA NTRS2019

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↗
NASA NTRS2019

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↗
NASA NTRS2019

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.↗