Soper, Jonathan (2022) An investigation of the influence of a decision support system on simulated ice management performance. Masters thesis, Memorial University of Newfoundland.
[English]
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Abstract
As automation becomes increasingly widespread in the marine industry, it is important that the efficacy of automated systems be appropriately gauged and measured. In this research, an experimental method was applied to test a decision support system (DSS) using inexperienced participants. These participants are provided with basic habituation but otherwise must depend on the DSS to provide strategic advice. They are then tasked with using their vessel to clear pack ice from the lifeboat launch zone of an offshore structure, using the DSS for strategic assistance. The experimental simulator has been used in other studies to gauge the effects of experience and training on ice management performance, which allows for a comprehensive comparison to be made across several different groups. The DSS contains expert knowledge and acts as a digital coach for the inexperienced participants in this study. It provides advice through video replays and text-based advice that was customized to their current approach when assistance is requested. The participants tended to adopt the expert strategies suggested by the DSS, but failed to deliver statistically significant improvements. This can be in part attributed to their lack of ship handling experience. Qualitative analysis from exit interviews also provided a good basis to guide improvements to the DSS. Ultimately, the experiment provides insights into the strengths and weaknesses of this DSS and describes an effective experimental method for evaluating this technology.
Item Type: | Thesis (Masters) |
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URI: | http://research.library.mun.ca/id/eprint/15673 |
Item ID: | 15673 |
Additional Information: | Includes bibliographical references (pages 92-94) |
Keywords: | ice management, marine navigation, human factors, decision support system, marine simulation, design of experiments |
Department(s): | Engineering and Applied Science, Faculty of |
Date: | October 2022 |
Date Type: | Submission |
Digital Object Identifier (DOI): | https://doi.org/10.48336/TP8C-B103 |
Library of Congress Subject Heading: | Decision support systems; Ice navigation--Simulation methods; Marine engineering--Human factors |
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