Engineering topics

Sadler, Garrett

Publications and source records attributed to Sadler, Garrett.

11 records

NASA NTRS2019

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: ACAS-Xu Run 5 Human-In-The-Loop Sim SC-147 Results Outbrief

This presentation provides an overview of a recently completed human-in-the-loop simulation, conducted as part of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. This study examined how to present resolution advisories (RAs) issued by Airborne Collision Avoidance System (ACAS) Xu, which can be in the vertical dimension, the horizontal dimension, or both (i.e., "blended"). The study varied the location of the ACAS Xu traffic information - it was either presented within an 'integrated' display or a 'standalone' display, where the traffic information was separated from the vehicle control interfaces and navigational information. Results revealed generally positive feedback on the visual and aural presentation of RAs, with special considerations and performance implications noted throughout.

Monk, Kevin J.↗

NASA NTRS2019

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: ACAS Xu Engineering Analysis Results

This presentation provides an overview of the results from a two-part engineering analysis conducted as part of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. Part one of this analysis examined how to present resolution advisories (RAs) issued by Airborne Collision Avoidance System (ACAS) Xu, which can be in the vertical dimension, the horizontal dimension, or both (i.e., "blended"). The study varied the appearance of the alerting and the verbiage used in the aural alerts. Results revealed high acceptability ratings for the appearance of the RA guidance. Part two of the analysis assessed pilot acceptability of varying levels of automation in the collision avoidance (CA) task. Pilots experienced conditions in which ACAS Xu RAs were executed either manually or automatically (i.e., auto-Collision Avoidance). In some conditions the return to a previously filed course was also executed automatically (auto-Return to Course). Results indicated that improvements are needed to how the state of the automation is presented. Implications of these findings are also discussed.

Detect and Avoid↗

NASA NTRS2019

Automatic Execution of Collision Avoidance and Return to Course Analysis (D.6.20) Experiment Review

This presentation details the experimental design for an upcoming engineering analysis of a mock version of the Airborne Collision Avoidance System (ACAS), specifically the 'Xu' variant, which is designed for unmanned aircraft platforms. As a component of the Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS) project, this engineering analysis intends to study aspects of ACAS Xu in two parts. In the first phase of the study, the display and alerting guidance for collision avoidance (CA) resolution advisories (RA) shown to pilots at a ground control station will be manipulated, varying in level of RA transparency and presentation of safe maneuver parameters. The second phase of the engineering analysis will examine pilots' response to increasing levels of automation in the tasks of collision avoidance and return-to-course (RTC).

Sadler, Garrett↗

NASA NTRS2018

Multi-UAS HITL: Primary Results & Automation Workshop Summaries

This presentation covers the primary results from a recently completed human-in-the-loop (HITL) simulation conducted as part of the UAS (Unmanned Aircraft System) integration into the NAS (National Airspace System) project. The HITL examined the impact of multiple (simultaneous) UAS control while performing a demanding mission task and managing scripted conflicts. The scripted conflicts were designed to trigger the detect-and-avoid (DAA) system. This was the first time the DAA system as designed as part of the UAS-NAS project has been applied to multi-UAS control. The second part of the presentation briefly summarizes the takeaways from two workshops held on human-automation interaction considerations for UAS integration. NASA co-hosted and participated in both workshops.

unmanned aircraft systems↗

NASA NTRS2017

Application of Human-Autonomy Teaming to an Advanced Ground Station for Reduced Crew Operations

Within human factors there is burgeoning interest in the "human-autonomy teaming" (HAT) concept as a way to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous systems as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as "plays." It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations, healthcare and medicine, autonomous vehicles, photography, and aviation. The current paper presents one such effort to apply HAT. It details the design of a HAT agent, developed by Human Automation Teaming Solutions, Inc., to facilitate teamwork between the automation and the human operator of an advanced ground dispatch station. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO); consequently, we have named the agent R-HATS. Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by R-HATS, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, R-HATS determines what tasks need to be completed and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. R-HATS has been designed to both support end users and researchers in RCO and HAT. Additionally, R-HATS and its underlying architecture were developed with generalizability in mind as a modular software applicable outside of RCO/aviation domains. This paper will also discuss future further development and testing of RHATS.

automation↗

NASA NTRS2017

Beyond Point Design: General Pattern to Specific Implementations

We have previously laid out a general framework for Human-Autonomy Teaming (HAT) and described how we applied this framework to a specific aeronautic task. In this presentation we demonstrate the applicability of these same principles to two familiar areas, photography and driving directions, focusing on bi-directional communication. We argue that good HAT requires communication of situation variables including operator goals and preferences and threats to meeting them, options including rationale, projected outcomes and confidence, and delegation.

human factors↗

NASA NTRS2017

Beyond Point Design: General Pattern to Specific Implementations

Elsewhere we have discussed a number of problems typical of highly automated systems and proposed tenets for addressing these problems based on Human-Autonomy Teaming (HAT)[1]. We have examined these principles in the context of aviation [2,3]. Here we discuss the generality of these tenets by examining how they might be applied to 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. We then illustrate how the generalities found across aviation, photography and navigation can be captured in a design pattern.

Lachter, Joel Benjamin↗

NASA NTRS2016

Effects of Transparency on Pilot Trust and Agreement in the Autonomous Constrained Flight Planner

We performed a human-in-the-loop study to explore the role of transparency in engendering trust and reliance within highly automated systems. Specifically, we examined how transparency impacts trust in and reliance upon the Autonomous Constrained Flight Planner (ACFP), a critical automated system being developed as part of NASA's Reduced Crew Operations (RCO) Concept. The ACFP is designed to provide an enhanced ground operator, termed a super dispatcher, with recommended diversions for aircraft when their primary destinations are unavailable. In the current study, 12 commercial transport rated pilots who played the role of super dispatchers were given six time-pressured all land scenarios where they needed to use the ACFP to determine diversions for multiple aircraft. Two factors were manipulated. The primary factor was level of transparency. In low transparency scenarios the pilots were given a recommended airport and runway, plus basic information about the weather conditions, the aircraft types, and the airport and runway characteristics at that and other airports. In moderate transparency scenarios the pilots were also given a risk evaluation for the recommended airport, and for the other airports if they requested it. In the high transparency scenario additional information including the reasoning for the risk evaluations was made available to the pilots. The secondary factor was level of risk, either high or low. For high-risk aircraft, all potential diversions were rated as highly risky, with the ACFP giving the best option for a bad situation. For low-risk aircraft the ACFP found only low-risk options for the pilot. Both subjective and objective measures were collected, including rated trust, whether the pilots checked the validity of the automation recommendation, and whether the pilots eventually flew to the recommended diversion airport. Key results show that: 1) Pilots trust increased with higher levels of transparency, 2) Pilots were more likely to verify ACFPs recommendations with low levels of transparency and when risk was high, 3) Pilots were more likely to explore other options from the ACFP in low transparency conditions and when risk was high, and 4) Pilots decision to accept or reject ACFPs recommendations increased as a function of the transparency in the explanation. The finding that higher levels of transparency was coupled with higher levels of trust, a lower need to verify other options, and higher levels of agreement with ACFP recommendations, confirms the importance of transparency in aiding reliance on automated recommendations. Additional analyses of qualitative data gathered from subjects through surveys and during debriefing interviews also provided the basis for new design recommendations for the ACFP.

trust↗

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

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 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↗