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Feigh, Karen M.

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    Expectations and Needs for Interaction in Human Robot Interaction
    (Georgia Institute of Technology, 2023-11-29) Feigh, Karen M.
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    The Importance of Shared Mental Models and Collaborative Judgment in Human-AI Interaction
    (Georgia Institute of Technology, 2022-08-24) Feigh, Karen M.
    IRIM hosts each semester a symposium to feature presentations from faculty and presentations of research that has been funded by our IRIM seed grant program in the last year. The symposium is a chance for faculty to meet new PhD students on campus, as well as a chance to get a better idea of what IRIM colleagues are up to these days. The goal of the symposium is to spark new ideas, new collaborations, and even new friends!
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    Impact of Adverse Weather on Commercial Helicopter Pilot Decision-Making and Standard Operating Procedures
    (Georgia Institute of Technology, 2021-08) Speirs, Andrew H. ; Ramee, Coline ; Payan, Alexia P. ; Mavris, Dimitri N. ; Feigh, Karen M.
    Helicopter pilots face unique challenges with regard to adverse weather when compared to fixed-wing pilots. Rotorcraft typically operate at lower altitudes in off-field areas that are not always well covered by weather reporting stations. Although recent technological advances have increased the amount of weather data that pilots can access in the cockpit, weather remains a factor in 28% of fatal helicopter accidents. In this work, commercial helicopter pilots were surveyed and interviewed to better understand how they gather and process weather information, what the perceived limitations of current weather tools are, and how their decision-making process is affected by the information they gather and/or receive. Pilots were found to use a wide variety of weather sources for their initial go or no-go decision during the preflight phase, but use fewer weather sources in the cockpit while in-flight. Pilots highlighted the sparsity and sometimes inaccuracy of the weather information available to them in their prototypical operational domain. To compensate, they are forced to rely on local and experiential weather knowledge to supplement weather reports while still working to mitigate other external pressures. Based on the literature and on results from this work, recommendations are made to address the weather-related gaps faced by the rotorcraft community. This includes the installation of additional weather reporting stations outside of airports and densely populated areas, the further promotion of the HEMS tool to helicopter pilots in all industries, the development of weather tools capable of visualizing light precipitation such as fog, and the development of in-flight graphical displays that can help reduce the cognitive workload of interpreting weather information.
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    Helicopter Operations Weather Information Pilot Interviews
    (Georgia Institute of Technology, 2021-01-29) Speirs, Andrew ; Ramee, Coline ; Alexia, Payan ; Mavris, Dimitri N. ; Feigh, Karen M.
    Helicopter pilots face unique challenges with regard to adverse weather when compared to fixed-wing pilots. Rotorcraft typically operate at lower altitudes in off-field areas that are not always well covered by weather reporting stations. Although recent technological advances have increased the amount of weather data that pilots can access in the cockpit, weather remains a factor in 28% of fatal helicopter accidents. In this work, commercial helicopter pilots were interviewed to better understand how they gather and process weather information, what the perceived limitations of current weather tools are, and how their decision-making process is affected by the information they gather and/or receive.
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    Helicopter Operations Weather Information Survey Dataset
    (Georgia Institute of Technology, 2020-11-23) Payan, Alexia P. ; Ramee, Coline ; Speirs, Andrew ; Mavris, Dimitri N. ; Feigh, Karen M.
    To better understand the kind of weather information used by rotorcraft operators and get their opinion on the weather products that are available to them, the research team created an online survey. The survey consisted of three main sections: 1) Demographics, 2) Flight environment, and 3) Safety Operations. The information collected was used to analyze the number and types of weather information sources used by pilots in different phases of flight, identify differences between industries and study pilots training for adverse weather conditions. The data contained here is an anonymized version of answers to the survey.
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    Human Teacher’s Perception of Teaching Methods for Machine Learning Algorithms
    (Georgia Institute of Technology, 2019-02-06) Feigh, Karen M.
    A goal of interactive machine learning (IML) is to create robots or intelligent agents that can be easily taught how to perform tasks by individuals with no specialized training. To achieve that goal, researchers and designers must understand how certain design decisions impact the human’s experience of teaching the agent, such as influencing the agent’s perceived intelligence. We posit that the type of feedback a robot can learn from effects the perceived intelligence of the robot, similar to its physical appearance. This talk will discuss different methods of natural language instruction including critique and action advice. We conducted multiple human-in-the-loop experiments, in which people trained agents with different teaching methods but, unknown to each participant, the same underlying machine learning algorithm. The results show that the mechanism of teaching has an impact on a human teacher’s perception of the agent, including feelings of frustration, perceptions of intelligence, and performance, while only minimally impacting the agent’s performance.
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    Evaluation of the Usability and Learnability of Vehicle Sketch Pad in Academia
    (Georgia Institute of Technology, 2016-06-02) MacLeod, Stephanie F. ; Feigh, Karen M.
    This paper describes an evaluation of the usability and learnability of Vehicle Sketch Pad (VSP) within the academic aerospace engineering field. In addition, this paper provides suggestions on how Vehicle Sketch Pad should develop to better provide a desirable graphical user interface (GUI). Aerospace Engineering graduate students were asked to perform specific tasks within Vehicle Sketch Pad, and their performance, efficiency, and workload while completing these tasks were measured. The same students were asked to perform similar tasks within a more traditional computer aided design (CAD) tool, AutoDesk Inventor. At this time, how the user interfaced with the Inventor GUI and what features within the interface they liked and did not like were measured. Analysis of the results of this experiment showed that all three experience-based noise variables, undergraduate major, prior courses taken, and prior VSP experience, do impact the user’s performance, efficiency, and workload while completing a task in VSP. For example, those with a more in-depth Aerospace-related background perceived less workload than those with alternative backgrounds. Additionally, the VSP GUI proved to have a statistically significant impact on the user’s performance, efficiency, and workload. For example, those who experienced confusion due to the workspace layout expressed they felt utilizing VSP was a very mentally demanding task. As a result this analysis, a roadmap for VSP development opportunities was created. This roadmap included users’ opinions and the researcher’s observances of gaps within the VSP GUI in addition to suggestions based on the Inventor GUI.
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    Single-operator Multi-vehicle Human-Automation Interface Study dataset
    (Georgia Institute of Technology, 2015-05) Feigh, Karen M. ; Johnson, Eric N. ; Christmann, Hans Claus
    With the achievement of autonomous flight for small unmanned aircraft, currently ongoing research is expanding the capabilities of systems utilizing such vehicles for various tasks. This allows shifting the research focus from the individual systems to task execution benefits resulting from interaction and collaboration of several aircraft. Given that some available high-fidelity simulations do not yet support multi-vehicle scenarios, a multi-vehicle framework has been introduced which allows several individual single-vehicle systems to be combined into a larger multi-vehicle scenario with little to no special requirements towards the single-vehicle systems. The created multi-vehicle system offers real-time software-in-the-loop simulations of vehicle teams across multiple hosts and enables a single operator to command and control a several unmanned aircraft beyond line-of-sight in geometrically correct two-dimensional cluttered environments through a multi-hop network of data relaying intermediaries. The related dissertation by Christmann presents the main aspects of the developed system: the underlying software framework and application programming interface, the utilized inter- and intrasystem communication architecture, the graphical user interface, and implemented algorithms and operator aid heuristics to support the management and placement of the vehicles.The effectiveness of the aid heuristics is validated through a human subject study which showed that the provided operator support systems significantly improve the operators' performance in a simulated first responder scenario. This dataset contains the collected data of that human subject study.
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    Decision Making with Incomplete Information Dataset
    (Georgia Institute of Technology, 2014-07-09) Feigh, Karen M. ; Canellas, Marc ; Chua, Zarrin K.
    Decision makers are often required to make decisions with incomplete information. In order to design decision support systems (DSSs) utilizing restrictiveness and guidance to assist decision makers in these situations, it is essential to understand how certain decision making strategies are affected by incomplete information. This paper presents the results of a simulation measuring the accuracy and effort of take-the-best (TTB) and Tallying alongside two normative-rational decision making strategies, weighted-additive (WADD) and equal-weighting (EW) in scenarios with varying levels of total information, information imbalance, dispersion, and dominance. The results show there is significant variability in the effort requirements of heuristic strategies which may diminish the arguments for effort-accuracy trade-offs. Additionally, heuristic strategies were shown to be closest in accuracy to normative-rational strategies when context features matched dynamic decision settings. Ultimately, methods for restrictiveness and guidance based on trade-offs between total information and information imbalance were shown to enable reductions in total information that actually increased the accuracy of heuristics.
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    Neural Networks for Assessment of Flight Deck Human-Automation Interaction Dataset
    (Georgia Institute of Technology, 2013-08-22) Feigh, Karen M. ; Sullivan, Katlyn B. ; Mappus, Rudolph Louis, IV ; Durso, Frank ; Fischer, Ute ; Pop, Vlad ; Mosier, Kathleen T. ; Morrow, Daniel G.