Results for “ATCo”

NASA NTRS2014

Air Traffic Controller Performance and Acceptability of Multiple UAS in a Simulated NAS Environment

Previously, we showed that air traffic controllers (ATCos) rated UAS pilot verbal response latencies as acceptable when a 1.5 s delay was added to the UAS pilot responses, but a 5 s delay was rated as mostly unacceptable. In the present study we determined whether a 1.5 s added delay in the UAS pilots' verbal communications would affect ATCos interactions with UAS and other conventional aircraft when the number and speed of the UAS were manipulated. Eight radar-certified ATCos participated in this simulation. The ATCos managed a medium altitude sector containing arrival aircraft, en route aircraft, and one to four UAS. The UAS were conducting a surveillance mission and flew at either a "slow" or "fast" speed. We measured both UAS and conventional pilots' verbal communication latencies, and obtained ATCos' acceptability ratings for these latencies. Although the UAS pilot response latencies were longer than those of conventional pilots, the ATCos rated UAS pilot verbal communication latencies to be as acceptable as those of conventional pilots. Because the overall traffic load within the sector was held constant, ATCos only performed slightly worse when multiple UAS were in their sector compared to when only one UAS was in the sector. Implications of these findings for UAS integration in the NAS are discussed.

measured response↗

NASA NTRS2013

Influence of UAS Pilot Communication and Execution Delay on Controller's Acceptability Ratings of UAS-ATC Interactions

Successful integration of UAS in the NAS will require that UAS interactions with the air traffic management system be similar to interactions between manned aircraft and air traffic management. For example, UAS response times to air traffic controller (ATCo) clearances should be equivalent to those that are currently found to be acceptable with manned aircraft. Prior studies have examined communication delays with manned aircraft. Unfortunately, there is no analogous body of research for UAS. The goal of the present study was to determine how UAS pilot communication and execution delays affect ATCos' acceptability ratings of UAS pilot responses when the UAS is operating in the NAS. Eight radar-certified controllers managed traffic in a modified ZLA sector with one UAS flying in it. In separate scenarios, the UAS pilot verbal communication and execution delays were either short (1.5 s) or long (5 s) and either constant or variable. The ATCo acceptability of UAS pilot communication and execution delays were measured subjectively via post trial ratings. UAS verbal pilot communication delay, were rated as acceptable 92% of the time when the delay was short. This acceptability level decreased to 64% when the delay was long. UAS pilot execution delay had less of an influence on ATCo acceptability ratings in the present stimulation. Implications of these findings for UAS in the NAS integration are discussed.

communication↗

NASA NTRS2017

The Human Performance Envelope: Past Research, Present Activities and Future Directions

Air traffic controllers (ATCOs) must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness can co-occur, and interact, to effect performance. However, multifactor influences and the association with performance are under-researched. This study utilized a high fidelity human in the loop enroute air traffic control simulation to investigate the relationship between workload, situation awareness and ATCO performance. The study aimed to replicate and extend Edwards, Sharples, Wilson and Kirwans (2012) previous study and confirm multifactor interactions with a participant sample of ex-controllers. The study also aimed to extend Edwards et als previous research by comparing multifactor relationships across 4 automation conditions. Results suggest that workload and SA may interact to produce a cumulative impact on controller performance, although the effect of the interaction on performance may be dependent on the context and amount of automation present. Findings have implications for human-automation teaming in air traffic control, and the potential prediction and support of ATCO performance.

human performance envelope↗

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 NTRS2016

Multifactor Interactions and the Air Traffic Controller: The Interaction of Situation Awareness and Workload in Association with Automation

Air traffic controllers (ATCOs) must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness (SA) can co-occur, and interact, to affect performance. However, multifactor influences and the association with performance are under-researched. This study utilized a high fidelity human in the loop enroute air traffic control simulation to investigate the relationship between workload, situation awareness and ATCO performance. The study aimed to replicate and extend Edwards, Sharples, Wilson and Kirwan's (2012) previous study and confirm multifactor interactions with a participant sample of ex-controllers. The study also aimed to extend Edwards et al.'s previous research by comparing multifactor relationships across 4 automation conditions. Results suggest that workload and SA may interact to produce a cumulative impact on controller performance, although the effect of the interaction on performance may be dependent on the context and amount of automation present. Findings have implications for human-automation teaming in air traffic control, and the potential prediction and support of ATCO performance.

Workload↗

NASA NTRS2010

Advanced Catalysts for the Ambient Temperature Oxidation of Carbon Monoxide and Formaldehyde

The primary applications for ambient temperature carbon monoxide (CO) oxidation catalysts include emergency breathing masks and confined volume life support systems, such as those employed on the Shuttle. While Hopcalite is typically used in emergency breathing masks for terrestrial applications, in the 1970s, NASA selected a 2% platinum (Pt) on carbon for use on the Shuttle since it is more active and also more tolerant to water vapor. In the last 10-15 years there have been significant advances in ambient temperature CO oxidation catalysts. Langley Research Center developed a monolithic catalyst for ambient temperature CO oxidation operating under stoichiometric conditions for closed loop carbon dioxide (CO2) laser applications which is also advertised as having the potential to oxidize formaldehyde (HCHO) at ambient temperatures. In the last decade it has been discovered that appropriate sized nano-particles of gold are highly active for CO oxidation, even at sub-ambient temperatures, and as a result there has been a wealth of data reported in the literature relating to ambient/low temperature CO oxidation. In the shorter term missions where CO concentrations are typically controlled via ambient temperature oxidation catalysts, formaldehyde is also a contaminant of concern, and requires specially treated carbons such as Calgon Formasorb as untreated activated carbon has effectively no HCHO capacity. This paper examines the activity of some of the newer ambient temperature CO and formaldehyde (HCHO) oxidation catalysts, and measures the performance of the catalysts relative to the NASA baseline Ambient Temperature Catalytic Oxidizer (ATCO) catalyst at conditions of interest for closed loop trace contaminant control systems.

Nalette, Tim↗

NASA NTRS2013

Work Practice Simulation of Complex Human-Automation Systems in Safety Critical Situations: The Brahms Generalized berlingen Model

The transition from the current air traffic system to the next generation air traffic system will require the introduction of new automated systems, including transferring some functions from air traffic controllers to on-board automation. This report describes a new design verification and validation (V&V) methodology for assessing aviation safety. The approach involves a detailed computer simulation of work practices that includes people interacting with flight-critical systems. The research is part of an effort to develop new modeling and verification methodologies that can assess the safety of flight-critical systems, system configurations, and operational concepts. The 2002 Ueberlingen mid-air collision was chosen for analysis and modeling because one of the main causes of the accident was one crew's response to a conflict between the instructions of the air traffic controller and the instructions of TCAS, an automated Traffic Alert and Collision Avoidance System on-board warning system. It thus furnishes an example of the problem of authority versus autonomy. It provides a starting point for exploring authority/autonomy conflict in the larger system of organization, tools, and practices in which the participants' moment-by-moment actions take place. We have developed a general air traffic system model (not a specific simulation of Überlingen events), called the Brahms Generalized Ueberlingen Model (Brahms-GUeM). Brahms is a multi-agent simulation system that models people, tools, facilities/vehicles, and geography to simulate the current air transportation system as a collection of distributed, interactive subsystems (e.g., airports, air-traffic control towers and personnel, aircraft, automated flight systems and air-traffic tools, instruments, crew). Brahms-GUeM can be configured in different ways, called scenarios, such that anomalous events that contributed to the Überlingen accident can be modeled as functioning according to requirements or in an anomalous condition, as occurred during the accident. Brahms-GUeM thus implicitly defines a class of scenarios, which include as an instance what occurred at Überlingen. Brahms-GUeM is a modeling framework enabling "what if" analysis of alternative work system configurations and thus facilitating design of alternative operations concepts. It enables subsequent adaption (reusing simulation components) for modeling and simulating NextGen scenarios. This project demonstrates that BRAHMS provides the capacity to model the complexity of air transportation systems, going beyond idealized and simple flights to include for example the interaction of pilots and ATCOs. The research shows clearly that verification and validation must include the entire work system, on the one hand to check that mechanisms exist to handle failures of communication and alerting subsystems and/or failures of people to notice, comprehend, or communicate problematic (unsafe) situations; but also to understand how people must use their own judgment in relating fallible systems like TCAS to other sources of information and thus to evaluate how the unreliability of automation affects system safety. The simulation shows in particular that distributed agents (people and automated systems) acting without knowledge of each others' actions can create a complex, dynamic system whose interactive behavior is unexpected and is changing too quickly to comprehend and control.

complex systems↗

NASA NTRS2017

Towards Designing Graceful Degradation into Trajectory Based Operations: A Human-Systems Integration Approach

One of the most fundamental changes to the air traffic management system in NextGen is the concept of trajectory based operations (TBO). With the introduction of such change, system safety and resilience is a critical concern, in particular, the ability of systems to gracefully degrade. In order to design graceful degradation into a TBO envrionment, knowledge of the potential causes of degradation, and appropriate solutions, is required. In addition, previous research has predominantly explored the technological contribution to graceful degradation, frequently neglecting to consider the role of the human operator, specifically, air traffic controllers (ATCOs). This is out of step with real-world operations, and potentially limits an ecologically valid understanding of achieving graceful degradation in an air traffic control (ATC) environment. The following literature review aims to identify and summarize the literature to date on the potential causes of degradation in ATC and the solutions that may be applied within a TBO context, with a specific focus on the contribution of the air traffic controller. A framework of graceful degradation, developed from the literature, is presented. It is argued that in order to achieve graceful degradation within TBO, a human-system integration approach must be applied.

human-system integration↗

NASA NTRS2017

Towards Designing Graceful Degradation into Trajectory Based Operations: A Human-Machine System Integration Approach

One of the most fundamental changes to the air traffic management system in NextGen is the concept of trajectory based operations (TBO). With the introduction of such change, system safety and resilience is a critical concern, in particular, the ability of systems to gracefully degrade. In order to design graceful degradation into a TBO envrionment, knowledge of the potential causes of degradation, and appropriate solutions, is required. In addition, previous research has predominantly explored the technological contribution to graceful degradation, frequently neglecting to consider the role of the human operator, specifically, air traffic controllers (ATCOs). This is out of step with real-world operations, and potentially limits an ecologically valid understanding of achieving graceful degradation in an air traffic control (ATC) environment. The following literature review aims to identify and summarize the literature to date on the potential causes of degradation in ATC and the solutions that may be applied within a TBO context, with a specific focus on the contribution of the air traffic controller. A framework of graceful degradation, developed from the literature, is presented. It is argued that in order to achieve graceful degradation within TBO, a human-system integration approach must be applied.

human-system integration↗

NASA NTRS2018

Designing Graceful Degradation into Complex Systems: The Interaction Between Causes of Degradation and the Association with Degradation Prevention and Recovery

System resilience is critical to safety in air traffic control. An important element of maintaining resilience is the ability of systems to degrade gracefully. Of the available graceful degradation research, a majority of studies have focused primarily on technological causes of degradation only, limiting an ecologically valid understanding of the causes of degradation in air traffic control, and the preventative and mitigative strategies that enable graceful degradation. The current study aimed to address this research gap by investigating causes of degradation in air traffic control (ATC) across the broad categories of technology, the environment, and the human operator, and the potential interactions between these causes. 12 retired controllers (ATCOs - Air Traffic Control Officers) participated in semi-structured interviews focused on previous experience of causes of degradation and mitigation strategies. Findings provide an understanding of causation of degradation in air traffic control, and the prevention and mitigation strategies that moderate the relationship between cause and system effect. Findings confirmed that causes appear to interact to create compound, multiple effects on overall system performance. Findings also revealed prevention and mitigation strategies utilized to moderate the effect of the cause on the system. In order to gain an ecologically valid understanding of the causes of degradation, and effective prevention or mitigation strategies, causes from multiple categories, and the interactions between them, must be identified. Findings have implications for designers of future air traffic control systems to ensure the ability of the system to gracefully degrade, as well as risk assessment and system validation processes.

Graceful Degradation↗

NASA NTRS2017

Towards Designing Graceful Degradation into Trajectory Based Operations: A Human-Machine System Integration Approach

One of the most fundamental changes to the air traffic management system in NextGen is the concept of trajectory based operations (TBO). With the introduction of such change, system safety and resilience is a critical concern, in particular, the ability of systems to gracefully degrade. In order to design graceful degradation into a TBO envrionment, knowledge of the potential causes of degradation, and appropriate solutions, is required. In addition, previous research has predominantly explored the technological contribution to graceful degradation, frequently neglecting to consider the role of the human operator, specifically, air traffic controllers (ATCOs). This is out of step with real-world operations, and potentially limits an ecologically valid understanding of achieving graceful degradation in an air traffic control (ATC) environment. The following literature review aims to identify and summarize the literature to date on the potential causes of degradation in ATC and the solutions that may be applied within a TBO context, with a specific focus on the contribution of the air traffic controller. A framework of graceful degradation, developed from the literature, is presented. It is argued that in order to achieve graceful degradation within TBO, a human-system integration approach must be applied.

trajectory based operations↗

NASA NTRSDate not supplied

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility, Air Traffic Control, Workload↗

NASA NTRSDate not supplied

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility↗

NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and F1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

LSTM↗

NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and 𝐹1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

ATC↗

NASA NTRSDate not supplied

Towards Understanding Data Requirements for Developing Automatic Speech Recognition Systems for Air Traffic Control

In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. Given the many applications focusing on transcribing air traffic control and management communication, this paper explores the training of OpenAI's Whisper model across multiple existing public and private air traffic control voice datasets in an effort to improve robustness. Combining roughly 60+ hours of various air traffic datasets, our goal is to train a unified Whisper model and expect an average word error rate reduction across testing datasets. Furthermore, this work aims to understand the data quantity requirements for achieving state-of-the art results by comprehensively training Whisper on varying dataset sizes. This work has the potential to improve automatic speech recognition performance across the domain, improve understanding of the quantity of data required by an aviation speech recognition system, and lastly provide metrics to compare and improve upon in future research.

ATC↗