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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Application of Human-Autonomy Teaming (HAT) Patterns to Reduce Crew Operations (RCO)

Unmanned aerial systems, advanced cockpits, and air traffic management are all seeing dramatic increases in automation. However, while automation may take on some tasks previously performed by humans, humans will still be required to remain in the system for the foreseeable future. The collaboration between humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. This paper applies a methodology for identifying HAT patterns to an advanced cockpit project.

design patterns↗
NASA NTRS2016

Application of Human-Autonomy Teaming (HAT) Patterns to Reduce Crew Operations (RCO)

Unmanned aerial systems, robotics, advanced cockpits, and air traffic management are all examples of domains that are seeing dramatic increases in automation. While automation may take on some tasks previously performed by humans, humans will still be required, for the foreseeable future, to remain in the system. The collaboration with humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. This paper applies a methodology for identifying HAT patterns to an advanced cockpit project.

design patterns↗
NASA NTRS2016

Application of Human-Autonomy Teaming (HAT) Patterns to Reduced Crew Operations (RCO)

As part of the Air Force - NASA Bi-Annual Research Council Meeting, slides will be presented on recent Reduced Crew Operations (RCO) work. Unmanned aerial systems, robotics, advanced cockpits, and air traffic management are all examples of domains that are seeing dramatic increases in automation. While automation may take on some tasks previously performed by humans, humans will still be required, for the foreseeable future, to remain in the system. The collaboration with humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. A methodology for identifying HAT patterns to an advanced cockpit project is discussed.

Human-Autonomy Teaming (HAT)↗
NASA NTRS2016

Demonstration of Human-Autonomy Teaming Principles

Known problems with automation include lack of mode awareness, automation brittleness, and risk of miscalibrated trust. Human-Autonomy Teaming (HAT) is essential for improving these problems. We have identified some critical components of HAT and ran a part-task study to introduce these components to a ground station that supports flight following of multiple aircraft. Our goal was to demonstrate, evaluate, and refine HAT principles. This presentation provides a brief summary of the study and initial findings.

transparency↗
NASA NTRS2017

Developing a General Framework for Human Autonomy Teaming

Automation has entered nearly every aspect of our lives, but it often remains hard to understand. Why is this? Automation is often brittle, requiring constant human oversight to assure it operates as intended. This oversight has become harder as automation has become more complicated. To resolve this problem, Human-Autonomy Teaming (HAT) has been proposed. HAT looks to make automation act as more of a teammate, by having it communicate with human operators in a more human, goal-directed, manner which provides transparency into the reasoning behind automated recommendations and actions. This, in turn, permits more trust in the automation when it is appropriate, and less when it is not, allowing a more targeted supervision of automated functions. This paper proposes a framework for HAT, incorporating two key tenets: bi-directional communication, and operator directed authority. We have successfully applied these tenets to integrating the autonomous constrained flight planner (an aide for planning diverts) into a dispatch station. We propose the development of general design patterns that may allow these results to be generalized to domains such as photography and automotive navigation. While these domains are very different, we find application of our HAT tenets provides a number of opportunities for improving interaction between human operators and automation.

human factors↗
NASA NTRS2017

A Human-Autonomy Teaming Approach for a Flight-Following Task

Managing aircraft is becoming more complex with increasingly sophisticated automation responsible for more flight tasks. With this increased complexity, it is becoming more difficult for operators to understand what the automation is doing and why. Human involvement with increasingly autonomous systems must adjust to allow for a more dynamic relationship involving cooperation and teamwork. As part of an ongoing project to develop a framework for human-autonomy teaming (HAT) in aviation, a part-task study was conducted to demonstrate, evaluate and refine proposed critical aspects of HAT. These features were built into an automated recommender system on a ground station available from previous studies. Participants performed a flight-following task once with the original ground station (i.e., No HAT condition) and once with the HAT features enabled (i.e., HAT condition). Behavioral and subjective measures were collected; subjective measures are presented here. Overall, participants preferred the ground station with HAT features enabled compared to the station without the HAT features. Participants reported that the HAT displays and automation were preferred for keeping up with operationally important issues. Additionally, participants reported that the HAT displays and automation provided enough situation awareness to complete the task and reduced workload relative to the No HAT baseline.

ACFP↗
NASA NTRS2018

Contingency Management with Human Autonomy Teaming

Automation is playing an increasingly important role in many operations. It is often cheaper faster and more precise than human operators. However, automation is not perfect. There are many situations in which a human operator must step in. We refer to these instances as contingencies and the act of stepping in contingency management. Here we propose coupling Human Autonomy Teaming (HAT) with contingency management. We describe two aspects to HAT, bi-directional communication, and working agreements (or plays). Bi-directional communication like Crew Resource Management in traditional aviation, allows all parties to contribute to a decision. Working agreements specify roles and responsibilities. Importantly working agreements allow for the possibility of roles and responsibilities changing depending on environmental factors (e.g., situations the automation was not designed for, workload, risk, or trust). This allows for the automation to "automatically" become more autonomous as it becomes more trusted and/or it is updated to deal with a more complete set of possible situations. We present a concrete example using a prototype contingency management station one might find in a future airline operations center. Automation proposes reroutes for aircraft that encounter bad weather or are forced to divert for environmental or systems reasons. If specific conditions are met, these recommendations may be autonomously datalinked to the affected aircraft.

dispatch↗
NASA NTRSDate not supplied

ETM Research Transition Team

An overview of Upper Class E Traffic Management (ETM) Research Transition Team (RTT)

Upper Class E Traffic Management↗
NASA NTRS2021

m:N and Human Autonomy Teaming Concepts for High Density Vertiport Operations

This report focuses on the role of the Fleet Manager (FM) and, in particular, the ways in which automation could support their position as they manage multiple aircraft and operators in a highly dynamic, advanced air mobility (e.g., air taxi) environment, specifically "high-density vertiport" (HDV) regions. Similar to terminal area operations for traditional aviation, operations involving HDVs will need to be highly structured while also remaining resilient to the various contingencies that can happen in that environment. The role of the FM is consistent with an “m:N” architecture, where “m” number of operators cooperatively manage “N” number of vehicles (where “N” is always larger than “m”). In such a paradigm it is critical to provide the operator with the tools and information necessary to manage their fleet safely and navigate the known pitfalls with highly automated, complex systems (e.g., brittleness, insufficient situation awareness, skill degradation). As the field of m:N has expanded as an area of study, a set of higher-level automation concepts have emerged—namely “plays,” “working agreements,” and “human-autonomy teaming” (HAT)—that could support operators in this new role.

human autonomy teaming↗
NASA NTRSDate not supplied

Foundational Human-Autonomy Teaming Research and Development in Scalable Remotely Operated Advanced Air Mobility Operations: Research Model and Initial Work

To achieve the scalability envisioned for many Advanced Air Mobility (AAM) applications, uncrewed aerial system (UAS) concepts are being pursued with the goal of enabling fewer human operators to manage more increasingly autonomous vehicles. NASA’s Transformational Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) subproject has identified human-autonomy teaming (HAT) as a critical area of research required to support these operations. Under T3-RAM, the HAT Foundational Research Activity has been tasked with providing basic research to identify HAT and human-automation interaction (HAI) principles that can be used to achieve scalable multi-vehicle UAS operations. This paper first outlines a research model to produce ecologically relevant basic research, then contextualizes completed and planned research and development activities within this model. Proposed research threads are presented, along with their practical and theoretical implications.

Human-Autonomy Teaming↗
NASA NTRSDate not supplied

MPATH (Measuring Performance for Autonomy Teaming with Humans) Ground Control Station: Design Approach and Initial Usability Results

Envisioned future Advanced Air Mobility (AAM) operations will require a transition of aircraft command and control from onboard pilots to remote operators. The National Aeronautics and Space Administration (NASA) has developed a research ground control station (GCS) software called MPATH (Measuring Performance for Autonomy Teaming with Humans) to study the human factors of remote operators in a representative AAM environment, where small uncrewed aerial systems (sUAS; simulated or real) act as surrogates for larger AAM aircraft. A primary focus of the research being conducted with the MPATH GCS is scalability (i.e., one human managing multiple vehicles). MPATH has demonstrated to be a useful capability for human factors research and remote operations. Two initial usability studies and a multi-vehicle control assessment were recently conducted, and usability data and operator feedback were collected. Generally, participants rated MPATH high on usability and interface quality, whereas information quality was rated slightly lower. These results were supported by specific feedback. Several generalized GCS design recommendations are proposed based on the results and feedback from these flight activities. Future updates to MPATH will incorporate the proposed recommendations. In practice, these recommendations could be used by any GCS software designer or developer to promote usability and safety.

Advanced Air Mobility↗
NASA NTRSDate not supplied

Human-Autonomy Teaming Assistant to Support Small Uncrewed Aircraft Systems for Wildland Firefighting Operations

An exploratory human-in-the-loop simulation was conducted to investigate and characterize a Human-Autonomy Teaming (HAT) Assistant to support a remote operator of multiple small Uncrewed Aircraft Systems (sUAS) using a ground control station (GCS) in the context of a wildland fire surveillance mission. Operator performance using the GCS with the HAT Assistant (Assisted Mode) was compared to operator performance using the GCS without the HAT Assistant (Unassisted Mode) during two types of contingency-event scenarios (Low and High Complexity). In the Assisted Mode, the HAT Assistant provided updates to the level of risk to the mission along with recommendations for risk mitigation, which were not provided in the Unassisted Mode. No significant differences in objective performance and subjective ratings of workload, situation awareness, and trust in automation between the Assisted and Unassisted Modes were detected, however there were indications that participants preferred the Assisted GCS over the Unassisted GCS and directions for further development were explored. Additional work is necessary to further refine the HAT Assistant and better characterize its effects on remote operator performance while managing multiple sUAS assets. Future work is recommended to optimize the implementation of an assistant to support operator performance during different missions and across vehicle classes.

Human-Autonomy Teaming↗
NASA NTRSDate not supplied

Human-Autonomy Teaming Assistant to Support Small Uncrewed Aircraft Systems for Wildland Firefighting Operations

An exploratory human-in-the-loop simulation was conducted to investigate and characterize a Human-Autonomy Teaming (HAT) Assistant to support a remote operator of multiple small Uncrewed Aircraft Systems (sUAS) using a ground control station (GCS) in the context of a wildland fire surveillance mission. Operator performance using the GCS with the HAT Assistant (Assisted Mode) was compared to operator performance using the GCS without the HAT Assistant (Unassisted Mode) during two types of contingency-event scenarios (Low and High Complexity). In the Assisted Mode, the HAT Assistant provided updates to the level of risk to the mission along with recommendations for risk mitigation, which were not provided in the Unassisted Mode. No significant differences in objective performance and subjective ratings of workload, situation awareness, and trust in automation between the Assisted and Unassisted Modes were detected, however there were indications that participants preferred the Assisted GCS over the Unassisted GCS and directions for further development were explored. Additional work is necessary to further refine the HAT Assistant and better characterize its effects on remote operator performance while managing multiple sUAS assets. Future work is recommended to optimize the implementation of an assistant to support operator performance during different missions and across vehicle classes

Human-Autonomy Teaming↗
DOE OSTI2017

Deploying Electric Vehicles and Electric Vehicle Supply Equipment: Tiger Teams Offer Project Assistance for Federal Fleets

To assist federal agencies with the transition to plug-in electric vehicles (PEVs), including battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), FEMP offers technical guidance on electric vehicle supply equipment (EVSE) installations and site-specific planning through partnerships with the National Renewable Energy Laboratory’s EVSE Tiger Teams.

electric vehicle↗
DOE OSTI2023

Resource Team Annual Report FY23

This report outlines the accomplishment of the Resource Team program in FY23, and discusses closeout of the program following this FY

99 GENERAL AND MISCELLANEOUS↗