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Jay Shively

Publications and source records attributed to Jay Shively.

17 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

AAM Human Factors Issues

This presentation provides an overview of Human Factors issue in AAM

unmanned aircraft systems↗
NASA NTRSDate not supplied

M:N Operations NASA/Uber Collaboration

In this presentation, current approaches to enable multiple-operator, multiple vehicle (M:N) operations are reviewed together with recent collaborative efforts between NASA and Uber. Topics include a review of human-automation teaming (HAT) concepts, including plays and working agreements, and a particular task-allocation method called Automation Level-based Task Allocation (ALTA). Following introductory material on HAT, an overview of a recent (July 2020) cognitive walkthrough study of M:N operations in the context of a food delivery via small-Unmanned Aircraft Systems application is provided. Initial results from this cognitive walkthrough detailing operator feedback on displays, operator and supervisor roles and responsibilities, and the overall concept of operation are reviewed. The presentation concludes with a description of a future, human-in-the-loop simulation experiment of M:N operations in a high-fidelity environment, which will examine the effects of high workload and assistive automation/tools on operator performance.

human-automation teaming↗
NASA NTRSDate not supplied

Human Autonomy Teaming - m:N Operations

The principles and reasons for employing Human Autonomy Teaming is discussed. Application of these techniques to multi-vehicle control is described. In several operational environments from small drone delivery to air taxi to autonomous cargo, many companies will need technologies that will allow for the operation of an unmanned aircraft (UAS or eVTOL) by a small crew of individuals that are located in a remote network operations center. That is, Multiple operators supervising an increasing Number of vehicles (M:N). This will require a new control/supervisory paradigm where the supervisors team with automation to achieve their joint tasks; Human Autonomy Teaming (HAT). This task will follow the HAT philosophy and tenants (e.g., trust, bi-directional communication, pilot directed interfaces). It will also develop and employ specific HAT tools (e.g., playbook, working agreements, predictive timeline displays, transparent interfaces to build trust).

multi-vehicle control↗
NASA NTRSDate not supplied

m:N Working Group

The principles and reasons for employing Human Autonomy Teaming is discussed. Application of these techniques to multi-vehicle control is described. In several operational environments from small drone delivery to air taxi to autonomous cargo, many companies will need technologies that will allow for the operation of an unmanned aircraft (UAS or eVTOL) by a small crew of individuals that are located in a remote network operations center. That is, Multiple operators supervising an increasing Number of vehicles (M:N). This will require a new control/supervisory paradigm where the supervisors team with automation to achieve their joint tasks; Human Autonomy Teaming (HAT). This task will follow the HAT philosophy and tenants (e.g., trust, bi-directional communication, pilot directed interfaces). It will also develop and employ specific HAT tools (e.g., playbook, working agreements, predictive timeline displays, transparent interfaces to build trust). This presentation discusses the background and progress of the m:N working group.

multi-vehicle control↗
NASA NTRSDate not supplied

m:N Handoff Study

Explore the source record for details and available documents.

m:N operations↗
NASA NTRSDate not supplied

Humans as Failsafe

Automation often relies on the human to "jump" into the loop and solve problems when the automation can’t due to conditions outside of which it was designed for or automaton failure. This talk proposes a methodology (Human Autonomy Assistant) to address that situation. Examples are provided from a wild fire context.

multi-vehicle control↗
NASA NTRSDate not supplied

HAT m:N Activity Overview

Since 2020, researchers from the Human Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center have conducted human-in-the-loop (HITL) simulation research to study a new control paradigm for operations involving multiple remotely piloted aircraft systems (RPAS). Colloquially referred to as "m:N," this paradigm is characterized by multiple operators collaboratively controlling multiple vehicles between them. The m:N name expresses a ratio whereby m is the number of operators and N is the number of vehicles shared between them. In this presentation, HAT Lab researchers provide a high-level overview of the m:N studies that have been performed to-date. These include a study of the m:N concept of operations (CONOPS) and the attending roles and responsibilities ("ConOps/R&R Sim"), a study focused on contingency management involving dynamic, inter-operator transfers of vehicles ("Handoff Sim"), and a study examining the effects of pilot-ATC communication systems on workload ("UAM Comms Sim"). A selection of key results are provided. The presentation concludes with a brief discussion of planned research into m:N operations.

m:N↗
NASA NTRSDate not supplied

Group 1: Evaluations Methodologies

m:N operations, multiple operators controlling mulitple vehicles, is a relatively new operating mode. As such, new evaluation methodologies are needed. In this presentation, neglect time and service time metrics are proposed as well as analysis candidates.

multiple↗
NASA NTRSDate not supplied

Meaningful Human Control of AI Based Systems

This presentation provides an overview of the concept of Meaningful Human Control (MHC) as it relates to artificially intelligent (AI) systems. The MHC concept originates in the context of autonomous weapons systems. In this presentation, the background and history of the MHC concept is provided and is followed by suggestions on how the concept can be extended to civil applications with AI.

meaningful human control↗