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Scott Scheff

Publications and source records attributed to Scott Scheff.

15 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

m:N Working Group: Meeting Summary March 2024

From March 26th to 28th, 2024 the m:N UAS working group and its subgroups (Evaluation Methodologies, Exceptions/Interventions, and Initial Operating Capability for Airspace Integration) met at SAIC in Washington, D.C. for an in-person meeting. The subgroups meet virtually throughout the year, and twice a year participants from all the subgroups come together to further identify and discuss challenges and paths forward for incorporating UAS into the airspace. The m:N UAS working group is run by Jay Shively (Adaptive Aerospace) and Andy Thurling (DroneUp) and is comprised of members from government, industry, and academia in an effort to identify and reduce barriers to m:N operations. This includes identifying requirements, use cases, metrics, and the development of white papers to support organizations including the FAA, RTCA, and ASTM. A change from last year, the Large UAS and HAPS sub working groups have disbanded while the sUAS working group continues independently, currently working on a white paper titled Personnel Selection, Roles, and Training for sUAS. For 2024 the m:N sub working groups have been refocused to cover evaluation methodologies, interventions/exceptions, and initial operating capability for airspace integration; with the premise that the outcomes from these subgroups will be white papers. These white papers can inform one another to ultimately become a master whitepaper. Each subgroup lead is called out below: Evaluation Methodologies Subgroup Jay Shively, Adaptive Aerospace Interventions/Exceptions Subgroup Andy Thurling, DroneUp (Lead) Initial Operating Capability for Airspace Integration Subgroup Andy Lacher, NASA (Lead)

m:N operations↗
NASA NTRS2024

m:N Working Group Meeting Summary November 2023

From November 28th to 30th, 2023 the m:N UAS working group and its subgroups [small Unmanned Aircraft Systems (sUAS), Large UAS, High Altitude Platform Systems (HAPS), and Urban Air Mobility (UAM)] met at the NASA Langley Research Center in Hampton, VA for an in person meeting. The subgroups meet multiple times throughout the year, virtually. Twice a year however, participants from all the subgroups come together in person to further identify and discuss challenges, and path forward ideas for incorporating UAS into the airspace. The m:N UAS working group is run by Jay Shively (Adaptive Aerospace) and Andy Thurling (Thurling Aero Consulting) and is comprised of members from government, industry, and academia in an effort to identify and reduce barriers to m:N operations. This effort also includes identifying requirements, use cases, and metrics to support organizations and groups including the FAA, RTCA, and ASTM. Each subgroup is run by a government/industry team (see below). sUAS Subgroup Garrett Sadler (NASA) Scott Scheff (HF Designworks) Large UAS Subgroup Conrad Rory (NASA) Brandon Suarez (Reliable Robotics) HAPS Subgroup Andy Thurling (Thurling Aero Consulting) Jeff Homola (NASA) UAM Subgroup Mike Politowicz (NASA) Scott Scheff (HF Designworks), member-at-large

m:N operations↗
NASA NTRS2023

m:N Working Group Annual Status Report

This document serves as an annual report of m:N Unmanned Aircraft Systems (UAS) subgroup activities, addressed challenges, and roadmaps for the future. The subgroups consist of small Unmanned Aircraft Systems (sUAS), Large UAS, High Altitude Platform Systems (HAPS), and Urban Air Mobility (UAM). Also included in this report are participant lists for each subgroup (Appendix B) and future roadmap and outreach plans.The subgroups meet in a virtual format multiple times throughout the year. Twice a year, participants from all the subgroups come together as part of the m:N working group to brief each other in person on progress, challenges, and path forward ideas for successful incorporation of UAS into the airspace. Recent m:N in person meetings include: - November 29-30, 2022 at the NASA Ames Research Center in Mountain View, CA - May 9 & 11, 2023 at AUVSI’s Xponential conference in Denver, CO - The next in person working group meeting is planned for November 28-30, 2023 at NASA Langley in Hampton, Virginia The m:N UAS working group is run by Jay Shively (Adaptive Aerospace) and Andy Thurling (Thurling Aero Consulting) and is comprised of members from government, industry, and academia in an effort to identify and reduce barriers to m:N operations. This effort also includes identifying requirements, use cases, and metrics to support organizations and groups including the Federal Aviation Administration (FAA) and Radio Technical Commission for Aeronautics (RTCA’s) SC-228 Detect and Avoid committee.

multi-vehicle↗
NASA NTRS2023

m:N Working Group Spring Meeting Summary

On May 9th and 11th, 2023, the NASA-led MultiVehicle (m:N) Working Group and its subgroups [small Unmanned Aircraft Systems (sUAS), Large UAS, High Altitude Pseudo Satellite (HAPS), and Urban Air Mobility (UAM)] met in Denver, CO at XPONENTIAL 2023, co-hosted by the Association for Uncrewed Vehicle Systems International (AUVSI) and Messe Düsseldorf North America (MDNA), for an in-person meeting. The subgroups meet multiple times throughout the year, virtually. Twice a year, however, participants from all the subgroups come together to brief each other on progress, challenges, and path forward ideas for incorporating UAS into the airspace. The m:N working group is co-chaired by Jay Shively (Adaptive Aerospace) and Andy Thurling (Thurling Aero Consulting) and is comprised of members from government, industry, and academia in an effort to identify and reduce barriers to m:N operations. This effort also includes identifying requirements, use cases, and metrics to support organizations and groups, including the FAA and RTCA’s SC-228 Detect and Avoid.

multi-vehicle↗
NASA NTRS2022

m:N Working Group

On November 29th and 30th, 2022, the m:N UAS working group and its subgroups [small Unmanned Aircraft Systems (sUAS), Large UAS, High Altitude Platform Systems (HAPS), and Urban Air Mobility (UAM)] met at the NASA Ames Research Center in Mountain View, CA for an in person meeting. The option to dial in remotely and use Conference.IO to engage with questions was offered as well. The subgroups meet multiple times throughout the year, virtually. Twice a year however, participants from all the subgroups come together to brief each other on progress, challenges, and path forward ideas for incorporating UAS into the airspace. The m:N UAS working group is run by Jay Shively (Adaptive Aerospace) and Andy Thurling (Thurling Aero Consulting) and is comprised of members from government, industry, and academia in an effort to identify and reduce barriers to m:N operations. This effort also includes identifying requirements, use cases, and metrics to support organizations and groups including the FAA and RTCA’s SC-228 Detect and Avoid. Each subgroup is run by a government/industry team.

multi-vehicle↗
NASA NTRS2021

State of the Industry: UAS Sensor Review

This report is a follow on from HF Designworks’ 2018 report on state of the present and state of the art sensor technologies as they related to Ground Based Detect and Avoid (GBDAA) systems for Unmanned Aircraft Systems (UAS). In this update, HF Designworks again looks to UAS test sites, manufacturers, vendors, and users to identify the latest sensor technologies covering not just GBDAA, but additional UAS sensor types; including airborne. For this latest report, the following sensor types were reviewed, as well as a few that don’t quite fit within the following categories: Electro-Optical / Infrared (EO/IR), LiDAR, RADAR, Radiofrequency (RF) scanner, Acoustic, and Other. From our interviews and research with various organizations and individuals, we found both interesting new technologies as well as improvements to many technologies first reviewed in 2018. Compared with our 2018 findings, many of the new technologies have helped produce sensors that are smaller, lighter, require less power, and have better range and resolution than those discussed in 2018. However, challenges still exist. There is no single currently available and FAA approved sensor suite that can adequately provide complete detect and avoid capabilities to meet the needs of UAS beyond visual line of sight (BVLOS) in the civilian airspace.

unmanned aircraft systems↗
NASA NTRSDate not supplied

HAT m:N Cognitive Task Analysis (CTA)

This Cognitive Task Analysis (CTA) study was designed to understand the capability of the m:N Tactical Operator (TO) interfaces developed by the Human-Autonomy Teaming Laboratory at NASA Ames to support operators responsible for simplified pilot operations of 100 independently operated small UAS (sUAS) in a constrained geographic area. The m:N sUAS TO interface includes a central Tactical Situation Display (TSD) digital map with moving icons reflecting the sUAS location and planned flight route. The interface also has two side panels. The left panel includes a tabular list of UAS assets and mission tasking, a list of recently viewed assets, and a list of events and alerts. The right panel includes a tabular list of UAS assets and their associated telemetry, text-based chat communication window, and a tabbed checklist window. This CTA was adapted from the incident-based applied cognitive task analysis (Militello & Hutton, 1998) and included demographics questions, scenario-based simulations, a task diagram and knowledge audit methods. In addition to examining the support provided by this m:N sUAS TO interface, this CTA study, conducted with aviation subject matter experts in analogous roles to the future tactical operator, was designed to illuminate and project likely cognitive requirements of the tactical operator. Interviewees participated in two scenario-based simulations using the m:N sUAS TO interfaces. In the first simulation, the interviewees supervised 12 sUAS operating in downtown San Diego, California transiting to and from a central sUAS Hive, restaurant locations, and customer drop off locations. Interviewees were asked to react to a UAS Volume Reservation (UVR) event with a two-phase impact on food delivery operations. In the second scenario, the interviewees supervised 100 sUAS operating in the same airspace and with the same mission. Interviewees used the interfaces to recognize and react to two sUAS air vehicle problems. After each scenario, we asked the interviewees a semi-structured list of questions to elicit their reflections about using the interfaces. Interviewees were confident in their ability to respond to two off-nominal situations in each simulation. Interviewees felt that, given high levels of automation on the sUAS, they would be able to manage the events without requiring additional support or handing off the sUAS to a colleague or supervisor in both the n=12 or n=100 sUAS settings. In the n=12 sUAS condition, interviewees used the center map to understand the asset location and progress along with mission tasking. An additional display window, Asset Telemetry, helped interviewees understand battery state and sUAS altitude. When the number of sUAS increased, interviewees altered their behavior. Rather than maintaining awareness of individual assets, interviewees appeared to become more reactive, managing exceptions. Interviewees reported that they spent less time looking at the nominal aircraft, and focused their attention primarily on the off-nominal aircraft. In addition, in the second simulation with n=100 sUAS, interviewees reported that they relied more on the side panels (Mission Timeline and Asset Telemetry) to gather information.

human-autonomy teaming↗
NASA NTRSDate not supplied

Streamlining Tactical Operator Handoffs During Multi-Vehicle Applications

Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies overtime. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool make subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.

M:N operations↗
NASA NTRSDate not supplied

A Remote, Human-in-the-Loop Evaluation of a Multiple-Drone Delivery Operation

Over time, advances in unmanned aircraft systems (UAS) have enabled a shift in the operational paradigm from one operator managing one aircraft to that of multiple operators working together to manage multiple aircraft. This shift has highlighted the need for effective human-autonomy teaming methods to maintain manageable workload levels for operators as well as high standards of system performance and safety. This paper presents a study aimed at evaluating whether automation can help operators manage workload during small UAS (sUAS) package delivery scenarios featuring contingency situations. These contingency situations, resulting from unplanned UAS Volume Reservations (UVRs), required flight path reroutes for multiple aircraft simultaneously. The study manipulated the number of aircraft affected by the UVRs and the level of automation support. The presence of terrain conflicts was also controlled within each scenario. Due to the COVID-19 pandemic, subjects were not able to gain direct access to the Ground Control System (GCS). Therefore, the study was conducted using a subject-surrogate paradigm that required subjects to relay commands through a verbal protocol from remote locations outside of the lab to a researcher surrogate who had direct control of the GCS interfaces at the lab location. Results show that the automated support condition was associated with faster reroute response times, more efficient reroute maneuvers, and significantly lower levels of perceived workload than the manual reroute condition. However, the automation support level did not significantly impact pilots’ ability to avoid the UVR successfully; pilots were overwhelmingly capable of avoiding the UVR in all conditions. The presence of terrain conflicts primarily impacted pilot performance by leading to multiple uploads per vehicle, which was not typically required when pilots only needed to maneuver laterally. Although subjects did not have direct control over the GCS, subjective ratings indicate that the displays under test provided them with sufficient information to manage their aircraft and promptly respond to the unplanned UVRs. Overall, the objective and subjective data strongly suggest that the verbal protocol and subject-surrogate paradigm were effective methods for collecting data remotely amid the COVID-19 pandemic.

multi-UAS↗
NASA NTRSDate not supplied

m:N Handoff Study

Explore the source record for details and available documents.

m:N operations↗
NASA NTRSDate not supplied

A New Control Paradigm: Multiple Aircraft Controlled by Multiple Operators

Remotely piloted aircraft systems (RPAS) are becoming more and more prevalent in the aerospace operations. This is true in a number of diverse domains; urban air mobility, medical product delivery, infrastructure inspection, high altitude pseudo-satellites, search and rescue, auto cargo and several other applications. One aspect that all of these share in common is the need for scalability to be viable and continue to grow. The Association of Uncrewed Vehicle Systems International (AUVSI) develops an annual economic report. They project that in the first three years of integration more than 70,000 jobs will be created in the US alone, with an economic impact of more than $13.6 billion. This benefit will grow through 2025 when we foresee more than 100,000 jobs created and economic impact of $82 billion. For many of these domains to reach these levels and have the scalability needed, they will require a remote pilot to control multiple aircraft (1:N) or the extension of that, multiple pilots controlling multiple aircraft (m:N). This is a new control paradigm that raises multiple issues in various areas. The issues include regulatory, technical, safety, community acceptance and Human Factors. Human factors issues include displays, pilot workload, pilot situation awareness just to name a few. This panel brings together researchers, developers and operators that have been working in the area of m:N. They will discuss the need, the issues and some potential solutions.

multi-vehicle control↗
NASA NTRSDate not supplied

Streamlining Tactical Operator Handoffs During Multi-Vehicle Operations

Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies over time. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool made subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.

m:N operations↗