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Daniel Guggenheim School of Aerospace Engineering

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Now showing 1 - 3 of 3
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    Cognitive Process Model, Validation Data, Initial Modeling Results
    (Georgia Institute of Technology, 2013-07-30) Chua, Zarrin K.
    These are the model files for the cognitive process model (moderate, Apollo-like function allocations) and four landing areas on the South Pole of the moon. With this data set, the user should be able to visualize the chosen landing sites for each user in the August 2012 human in the loop experiment conducted with the NASA astronaut office, validation of the cognitive model, and a set of randomly generated data points used for initial results.
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    System design considerations for human-automation function allocation during lunar landing
    (Georgia Institute of Technology, 2013-07-08) Chua, Zarrin K.
    A desire to advance humanity's presence in space prompts the need for improved technology to send crew to places such as the Moon, Mars, and nearby asteroids. Safely placing a crewed vehicle on and in any landing condition requires a design decision regarding the distribution of responsibilities between the crew and automation. In this thesis, a cognitive process model is used to determine the necessary automated functionality to support astronaut decision making. Current literature lacks sufficient detailed knowledge regarding astronaut decision making during this task and observations of astronauts landing on the Moon are not readily available. Therefore, a series of human-in-the-loop experiments, one of which was conducted with the NASA Astronaut Office at Johnson Space Center, have been conducted to examine the changes in performance due to differing function allocations, trajectory profiles, and scenario operations. The data collected in the human-in-the-loop study has provided empirical data that has informed the cognitive process model, the requirements analysis, and provided insight regarding cockpit display usage and information needs. The proposed system requirements include design guidance for assisting astronauts during both nominal and off-nominal landing scenarios.
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    Analysis of Human-System Interaction For Landing Point Redesignation
    (Georgia Institute of Technology, 2009-05-26) Chua, Zarrin K.
    Despite two decades of manned spaceflight development, the recent thrust for increased human exploration places significant demands on current technology. More information is needed in understanding how human control affects mission performance and most importantly, how to design support systems that aid in human-system collaboration. This information on the general human-system relationship is difficult to ascertain due to the limitations of human performance modeling and the breadth of human actions in a particular situation. However, cognitive performance can be modeled in limited, well-defined scenarios of human control and the resulting analysis on these models can provide preliminary information with regard to the human-system relationship. This investigation examines the critical case of lunar Landing Point Redesignation (LPR) as a case study to further knowledge of the human-system relationship and to improve the design of support systems to assist astronauts during this task. To achieve these objectives, both theoretical and experimental practices are used to develop a task execution time model and subsequently inform this model with observations of simulated astronaut behavior. The experimental results have established several major conclusions. First, the method of LPR task execution is not necessarily linear, with tasks performed in parallel or neglected entirely. Second, the time to complete the LPR task and the overall accuracy of the landing site is generally robust to environmental and scenario factors such as number of points of interest, number of identifiable terrain markers, and terrain expectancy. Lastly, the examination of the overall tradespace between the three main criteria of fuel consumption, proximity to points of interest, and safety when comparing human and analogous automated behavior illustrates that humans outperform automation in missions where safety and nearness to points of interest are the main objectives, but perform poorly when fuel is the most critical measure of performance. Improvements to the fidelity of the model can be made by transgressing from a deterministic to probablistic model and incorporating such a model into a six degree-of-freedom trajectory simulator. This paper briefly summarizes recent technological developments for manned spaceflight, reviews previous and current efforts in implementing LPR, examines the experimental setup necessary to test the LPR task modeling, discusses the significance of findings from the experiment, and also comments on the extensibility of the LPR task and experiment results to human Mars spaceflight.