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Comparing route learning in drivers using conventional navigation assistance devices and a hypothetical augmented reality system

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Date Issued:
2020
Abstract:
Current trends point towards the development and implementation of augmented reality (AR) navigation assistance systems for drivers. Previous research has found augmented reality can benefit driving performance, but the impact of AR on route learning (spatial knowledge acquisition) has received less attention. The current study used simulated driving scenarios to determine how the type of navigation aid device used (i.e., paper map, electronic map, and AR system) affected driving performance and route learning. Route learning was examined at landmark, route, and survey levels. The hypotheses tested were that AR would improve driving performance, but diminish route learning compared to paper map use; that AR would outperform electronic map use in both driving performance and route learning; and that experts and novices would be affected differently. Paper map use resulted in poorer driving performance and greater route learning, but map recognition may be a confounding factor in higher level spatial knowledge acquisition with paper map use. Driving performance and route learning were similar for drivers using the electronic map and AR, but there were differences that suggest drivers have reduced uncertainty and hesitation while using AR to navigate in unfamiliar areas. Differences between expert and novice drivers were not found.
Title: Comparing route learning in drivers using conventional navigation assistance devices and a hypothetical augmented reality system.
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Name(s): Yount, Zachary Franklin, author.
Type of Resource: text
Genre: Bibliography
Text-txt
Academic Theses.
Academic Theses.
Electronic Thesis Or Dissertation.
Issuance: monographic
Date Issued: 2020
Date Issued: 2020
Other Date: 2020.
Publisher: University of West Florida,
Place of Publication: Pensacola, Florida :
Physical Form: electronic resource
Extent: 1 online resource (viii, 38 leaves : illustrations, charts)
Language(s): eng
Abstract: Current trends point towards the development and implementation of augmented reality (AR) navigation assistance systems for drivers. Previous research has found augmented reality can benefit driving performance, but the impact of AR on route learning (spatial knowledge acquisition) has received less attention. The current study used simulated driving scenarios to determine how the type of navigation aid device used (i.e., paper map, electronic map, and AR system) affected driving performance and route learning. Route learning was examined at landmark, route, and survey levels. The hypotheses tested were that AR would improve driving performance, but diminish route learning compared to paper map use; that AR would outperform electronic map use in both driving performance and route learning; and that experts and novices would be affected differently. Paper map use resulted in poorer driving performance and greater route learning, but map recognition may be a confounding factor in higher level spatial knowledge acquisition with paper map use. Driving performance and route learning were similar for drivers using the electronic map and AR, but there were differences that suggest drivers have reduced uncertainty and hesitation while using AR to navigate in unfamiliar areas. Differences between expert and novice drivers were not found.
Identifier: 1222213022 (oclc), WFE0000736 (IID)
Note(s): by Zachary Franklin Yount.
Usha Kundu, M.D. College of Health
Thesis (M.A.) University of West Florida 2020
Includes bibliographical references.
Also available in print.
Subject(s): University of West Florida
University of West Florida.
Library Classification: LD1807.F62k 2020 Y686
Persistent Link to This Record: http://purl.flvc.org/uwf/fd/WFE0000736
Use and Reproduction: http://rightsstatements.org/vocab/InC-EDU/1.0/
Host Institution: UWF
Other Format: Comparing route learning in drivers using conventional navigation assistance devices and a hypothetical augmented reality system. (Print version:)
(OCoLC)1222213033

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