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NASA NTRSDate not supplied

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 coopertive, 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 an overview of discussions and industry news covering the time since the previous group meeting, a presentation on initial work titled 'Sensitivity Study of Minimum Reserved Airspace in ETM Operations,' and a high level discussion titled 'Separation Management Service Framework for ETM.'

Upper E↗

NASA NTRSDate not supplied

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 an overview of discussions and industry news covering the time since the previous group meeting, a recap of the group's history and road ahead, a discussion of industry's initial position on, 'Industry principles for ETM rules of the road: Conflict identification and resolution,' and a simulation roadmap for planned work ahead.

Upper E↗

NASA NTRSDate not supplied

Achieving Equilibrium for Dense, Integrated, Vehicle Navigation

Drone usage has proliferated in recent years with many applications that have market-changing potential. Applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. In this paper, the term drone is used to mean both Unmanned Aerial Vehicle and small Unmanned Aircraft System vehicles. Flight infrastructure can currently only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay atone airport sends ripple effects through the system, causing more delays and missed connections. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the NAS is expected to skyrocket to millions, potentially congesting the airspace resulting in possible separation violations. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is a safety critical property for drones in the airspace. This paper addresses separation in time and in distance for high volume corridors (en-route) and lanes(on ground). The requirements and necessary conditions for maintaining proper separation and reaching maximum throughput for a given corridor/lane are addressed assuming unidirectional corridors/lanes where an aircraft arrives from one side and departs from the opposite side. Simulation results are presented that show the presented solution guarantees a set of drones to reach the equilibrium state by adjusting their speed based on their distance to the aircraft in front of them. The equilibrium state is defined as a state when a set of n aircraft moving at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as a state when the aircraft cannot move at their maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach using a large number of drones and evaluate the scalability of the proposed solution.

Mahyar R. Malekpour↗

NASA NTRSDate not supplied

NASA ETM Modeling and Simulation Upper E Traffic Management Meeting December 2020

This is a slide set to be used 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 Class 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 Class 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 an overview of the past accomplishments, current project structure, and a simulation roadmap for planned work ahead.

NASA ETM modeling and simulation↗

NASA NTRSDate not supplied

ETM: 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 an overview of discussions and industry news covering the time since the previous group meeting, a discussion of industry's position on operation intent and negotiation strategies in ETM airspace, applications of that position as captured through use cases, and a simulation roadmap for NASA's planned work ahead into CY21.

Upper E↗

NASA NTRS2021

Characteristics of the RFI Environment at L-band as Observed from SMAP

This manuscript presents some characteristics of RFI sources as they were observed by the SMAP L-band radiometer. Knowledge of the nature of RFI can help improve design of future detection algorithms. For example, observations with airborne instruments demonstrating the pulse-like nature of RFI in the protected L-band spectrum at 1.413 GHz (attributed to air-traffic control radar) informed the design of the Aquarius radiometer and its RFI detection algorithm. The experience of Aquarius and SMOS in space led to the advanced detection system on SMAP. The fully polarimetric SMAP radiometer with spectral and time domain processing, provides sophisticated detection but also the opportunity to look at the temporal and spectral characteristics of the L-band RFI globally. The examples and categorization presented are based on a global sample but over a limited time. They are not meant to be complete. Rather, they are intended to provide insight into the time-frequency characteristics of RFI with the goal that knowledge of the characteristics can help improve detection in future missions.

Yan Soldo↗

NASA NTRSDate not supplied

Multitasking

Multitasking is endemic in modern life and work: drivers talk on cell phones, office workers type while answering phone calls, students do homework while text messaging, nurses prepare injections while responding to doctor’s calls, and air traffic controllers direct aircraft in one sector while handling additional traffic in another. Whether in daily life or at work, we are constantly bombarded with multiple concurrent demands, and we have all somehow come to believe in the myth that we can, and in fact are expected to, easily address them all - without any repercussions. However, accumulating scientific evidence is now suggesting that multitasking increases the probability of human error. This talk presents a set of NASA studies that characterize concurrent demands in routine airline flight operations, in order to illustrate the ways operational task demands together with the proclivity to manage them all concurrently make human performance in this and in any domain vulnerable to potentially serious errors and to accidents.

multitasking↗

NASA NTRSDate not supplied

Identifying Emerging Safety Threats Through Topic Modeling in the Aviation Safety Reporting System: A Covid-19 Study

The NASA Aviation Safety Reporting System (ASRS) is a voluntary, confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants, and others involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts, and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in many ways, including via an online database, Safety Alert Bulletins, For Your Information Notices, and the CALLBACK newsletter. In this work, we consider whether we can improve the grouping, linking, and understanding of safety concerns through topic modeling. Specifically, we use topic modeling as a building block to identify emerging safety threats over time. This unsupervised approach, we argue, offers the flexibility to identify new emerging themes in this large dataset by constructing different timelines based on the content similarity of ASRS report narratives. This method's unsupervised nature improves upon related research, which is limited to pre-defined labels and therefore can not fully capture emerging safety threats. We apply our method to all ASRS reports in 2020 to assess if the generated timelines can highlight COVID-19 as it is emerging as a safety threat in incoming ASRS reports. We perform both a quantitative and qualitative evaluation of the automatically constructed timelines. The qualitative evaluation is performed by describing the evolution of top terms in the timelines, generated by our method, which we found explicitly convey the themes of COVID-19. Separately, we use a set of 1,213 COVID-19 reports from 2020 that were manually identified by ASRS analysts to quantitatively evaluate the COVID-19 reports distribution across the timelines. Our results have shown that COVID-19 emergence can be identified using the top terms that were generated by topic modeling. The top terms in topic modeling therefore can serve as a summary alternative to manually inspecting reports. Moreover, leveraging the manually identified COVID-19 reports, we found the manually identified timelines accounted for over 70% of the COVID-19 reports curated by the ASRS analysts, which demonstrates the potential of this approach for facilitating the understanding of safety concerns as they emerge and evolve. This method shows great potential to understand aerospace safety threats and other narrative- driven incident report databases.

ASRS↗

NASA NTRSDate not supplied

ETM: 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 an overview of discussions and industry news covering the time since the previous group meeting, a discussion of industry's feedback regarding a specific use case, a presentation on lexicon and the definition of Common Operating Practices, and an update on modeling and simulation work.

Upper E↗

NASA NTRSDate not supplied

The Effects of Chronic Sleep Restriction on Multiple Object Tracking

The ability to simultaneously track numerous moving objects in the presence of irrelevant stimuli is essential for carrying out a variety of tasks. Sleep loss has been found to impair neurocognitive functioning and, as a result, attentional processing capacity is reduced. A common form of sleep loss is chronic sleep restriction (CSR), in which an inadequate amount of sleep is obtained over consecutive days. The objective of the current study was to determine if performance on the multiple object tracking (MOT) task was adversely impacted by a week of CSR. Twelve healthy participants (6 males, 6 females) kept a fixed sleep-wake schedule, with a constant waketime, at home for four weeks (activity monitors worn on the participant’s nondominant wrist were used to confirm compliance). Weeks one and three were deemed washout weeks, during which participants maintained a 9-hour sleep-wake schedule. Weeks two and four were deemed experimental weeks, during which participants were randomly assigned a 5-hour (CSR) and 9-hour (sleep satiation) sleep-wake schedule. Following night seven of each experimental week, participants completed a 13-hour laboratory visit under dim light (less than 15 lux) where they maintained a constant posture and were provided with hourly isocaloric snacks. MOT was presented at approximately 6 and 8 hours after waking. Participants were required to track four, five, or six moving targets in the presence of identical distractors (always 12 total objects). It was found that participants slept significantly less during the week of CSR compared to the week of sleep satiation. There was no difference in the overall proportion of correct MOT responses following the CSR and sleep satiation weeks. However, an additional analysis examining only the 6 target condition found that the proportion of correct responses was significantly lower following the week of CSR. These findings suggest that CSR has an adverse impact on tracking performance when the cognitive demand was higher. This has implications for individuals, such as air traffic controllers and truck drivers, who must visually track multiple moving objects under high workload situations, often while chronically sleep deprived.

sleep restriction↗

NASA NTRS2021

ATD-2 Phase 3 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. ATD-2 Phase 1 & 2 have successfully demonstrated new technologies developed to manage the IADS capabilities at a single airport. The Phase 3 builds upon Phases 1 and 2 by extending the capabilities to a Metroplex environment where multiple airports are interacting and competing for resources at the terminal boundary. This document describes the metrics used to inform the flight operators, Air Traffic Control (ATC) tower, FAA, and even broader aviation community about opportunities to reroute aircraft and the metrics used to assess the performance of the ATD-2 Phase 3 system including benefits. This document provides definitions and detailed calculation methods of identified Phase 3 benefit metrics such as OFF Delay Savings, IN Delay Savings, and Aggregate System-Wide Savings. This document also describes the mechanism to translate delay savings metrics into fuel and emissions savings.

ATD-2 Phase 3↗

NASA NTRSDate not supplied

Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violation

Current forecasts on the future of aeronautics suggest an in- creasing number of unmanned aerial vehicles entering the low- altitude airspace in the next decades (FAA, 2018; Kopardekar et al., 2016). Small vehicles for package delivery as well as larger vehicles for urban air mobility will change the airspace drastically, increasing density of operations both in time, i.e. high number of take-off and landings per unit time, and in space, operating in dense urban environment. This scenario poses challenges to the current approach to air traffic control, and large efforts from academia, industry and regulatory bodies are dedicated to the development of new traffic management strategies that leverage higher computing and simulating capabilities available today. In this paper, we propose a simple look-ahead approach to predict potential minimum separation violations at the strategic level, that is before vehicles start flying, depending on the predefined 4D trajectories and uncertainty affecting the wind acting along those routes. The wind field is extracted from the NOAA North America Mesoscale Forecast System and interpolated using Gaussian process regression, while uncertainty affecting the expected cruise airspeed is propagated through error intervals. The approach allows the prediction of aircraft separation as a function of time, highlighting potential safety violations that would go undetected if uncertainty affecting the expected 4D trajectories is not considered. The paper will also discuss issues related to accuracy and scalability of the approach to multiple vehicle operations.

Trajectory Prediction↗

NASA NTRSDate not supplied

Establishing the Framework for e-VTOL Flight Mission Scenario Development for Urban Air Mobility Research using Cognitive Task Analysis

This paper focuses on applying specific protocol aspects of Cognitive Task Analysis (CTA) methods to formulate non-routine flight mission use-case scenarios in support of a potential research study at the National Aeronautics and Space Administration (NASA) Langley Research Center under the Air Traffic Management – eXploration (ATM-X) Urban Air Mobility (UAM) sub-project. The objective of use-case scenarios is to provide a hypothetical situation to elicit expert knowledge and feedback in a specific subject matter area. Use-case scenarios in the field of aviation, including UAM, can help to support the safe integration of these vehicles into the National Airspace System (NAS) through the examination of airspace procedures during non-routine events. Inherent in this type of research is the need to study in-flight non-routine scenarios that the UAM vehicle could encounter. Situations categorized as non-routine events are any events that occur outside of the original flight plan such as a mechanical malfunction or other in-flight emergency requiring special procedures, which can include diversions to a specified, or non-specified, emergency landing area. In specific instances, some non-routine events could be considered as “routine” during in-flight operations, such as the need to perform a go-around due to a balked landing. As the rate of technological expansion surrounding UAM grows rapidly in modern aviation, so does the need for research that focuses on the safe integration of these vehicles including research with a focus on the methods and development of airspace operational procedures. Research rooted in CTA methods provides a framework for developing use-case scenarios appropriate for environments where mental demands are substantial. Substantial mental demands exist while operating in the NAS for pilots, airline dispatchers, and air traffic controllers among many others. With the focus on UAM in mind, it is critical to frame a baseline use-case scenario using information as it pertains to current-day airspace operations. According to Dr. Robert R. Hoffman’s “Protocols for Cognitive Task Analysis,” one of the first steps to applying CTA methods to research is the concept of “bootstrapping” in which the researcher(s) familiarize themselves with the domain that is being studied. To formulate the non-routine flight mission use-case scenarios for the purpose of this potential NASA ATM-X UAM research study, and to inform the baseline use-case scenario, the practice of bootstrapping was utilized to acquire knowledge of current-day airspace procedures.

Heidi S Glaudel↗

NASA NTRSDate not supplied

Upper Class E Traffic Management (ETM)

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 Class 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 Class 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 an overview of discussions and industry news covering the time since the previous group meeting, a discussion of service applicability to the ETM environment and examples from UAS Traffic Management, an update on modeling and simulation work, and an announcement of an upcoming ETM workshop.

Upper E↗

NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.

machine learning↗

NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

machine learning↗

NASA NTRS2021

Evolution of National Airspace System Protection for Space Shuttle Launch and Landing

The breakup of the Space Shuttle Columbia on 1 February 2003 during the entry phase of the STS-107mission occurred above a significant number of aircraft operating in the National Airspace System (NAS).Although no aircraft were struck by falling debris, the incident led the Federal Aviation Administration(FAA) and the National Aeronautics and Space Administration (NASA) to seek cooperative ways to betterprotect aircraft operating in the NAS during Space Shuttle launch and landing operations. Applicationswere developed and improved by both the FAA and NASA to provide pre-operation and near real-timegroundtracks and debris footprints to enable Air Traffic Controllers (ATC) to vector aircraft away from thedebris field in the event of a Space Shuttle breakup. Real-time coordination processes were also developedto provide the FAA data and insight into ongoing Space Shuttle operations in order to protect the NAS.The processes and procedures developed for Space Shuttle operations are extensible and applicable tofuture NASA and commercial spacecraft.

Doyle W Hensley↗

NASA NTRSDate not supplied

Urban Air Mobility Airspace Dynamic Density

Airspace safety must be assured for Urban Air Mobility (UAM) to become reality. Emerging operations need to safely integrate with existing and future air traffic. UAM is anticipated to evolve in stages. Early stages, characterized by low-density operations, may be accommodated by traditional air traffic management approaches. However, to enable the scale of UAM operations necessary to reach ubiquitous integration into daily life, new paradigms that utilize collaborative and automated systems are being considered. Correspondingly, traditional approaches for determining a safe number of simultaneous operations in an airspace must be adapted to suit evolving traffic management paradigms. In this paper, we examine dynamic density as an approach to determine when an airspace is excessively populated, and safety may become compromised. We review previous work on dynamic density as it relates to air traffic controller workload and propose factors that may be more fitting for UAMs. Rather than considering controller workload, we propose factors that suggest increased likelihood of loss of separation and may lead to conflicts that require tactical avoidance maneuvers. In addition to monitoring dynamic density for tactical decision making, we endeavor to predict airspace dynamic density with adequate look-ahead to allow for strategic route selection.

UAM↗