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An Empirical Investigation on the Visual Imagery of Augmented Reality User Interfaces for Smart Electric Vehicles Based on Kansei Engineering and FAHP-GRA
by
Zheng, Meng-Cong
, Lin, Jin-Long
in
Accuracy
/ Analytic hierarchy process
/ Augmented reality
/ augmented reality dashboard
/ Automotive engineering
/ Content analysis
/ Dashboards
/ Design
/ Electric vehicles
/ Emotions
/ Factor analysis
/ Factorial experiments
/ fuzzy analytic hierarchy process-grey relational analysis
/ Fuzzy systems
/ human-machine interface
/ Imagery
/ Kansei engineering
/ Methods
/ multi-criteria decision-making
/ Multiple criteria decision making
/ Performance evaluation
/ Product development
/ Real time
/ Semantics
/ Systems theory
/ User experience
/ User interface
/ User interfaces
/ User satisfaction
/ Vehicle safety
/ Visual effects
2024
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An Empirical Investigation on the Visual Imagery of Augmented Reality User Interfaces for Smart Electric Vehicles Based on Kansei Engineering and FAHP-GRA
by
Zheng, Meng-Cong
, Lin, Jin-Long
in
Accuracy
/ Analytic hierarchy process
/ Augmented reality
/ augmented reality dashboard
/ Automotive engineering
/ Content analysis
/ Dashboards
/ Design
/ Electric vehicles
/ Emotions
/ Factor analysis
/ Factorial experiments
/ fuzzy analytic hierarchy process-grey relational analysis
/ Fuzzy systems
/ human-machine interface
/ Imagery
/ Kansei engineering
/ Methods
/ multi-criteria decision-making
/ Multiple criteria decision making
/ Performance evaluation
/ Product development
/ Real time
/ Semantics
/ Systems theory
/ User experience
/ User interface
/ User interfaces
/ User satisfaction
/ Vehicle safety
/ Visual effects
2024
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Do you wish to request the book?
An Empirical Investigation on the Visual Imagery of Augmented Reality User Interfaces for Smart Electric Vehicles Based on Kansei Engineering and FAHP-GRA
by
Zheng, Meng-Cong
, Lin, Jin-Long
in
Accuracy
/ Analytic hierarchy process
/ Augmented reality
/ augmented reality dashboard
/ Automotive engineering
/ Content analysis
/ Dashboards
/ Design
/ Electric vehicles
/ Emotions
/ Factor analysis
/ Factorial experiments
/ fuzzy analytic hierarchy process-grey relational analysis
/ Fuzzy systems
/ human-machine interface
/ Imagery
/ Kansei engineering
/ Methods
/ multi-criteria decision-making
/ Multiple criteria decision making
/ Performance evaluation
/ Product development
/ Real time
/ Semantics
/ Systems theory
/ User experience
/ User interface
/ User interfaces
/ User satisfaction
/ Vehicle safety
/ Visual effects
2024
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An Empirical Investigation on the Visual Imagery of Augmented Reality User Interfaces for Smart Electric Vehicles Based on Kansei Engineering and FAHP-GRA
Journal Article
An Empirical Investigation on the Visual Imagery of Augmented Reality User Interfaces for Smart Electric Vehicles Based on Kansei Engineering and FAHP-GRA
2024
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Overview
Smart electric vehicles (SEVs) hold significant potential in alleviating the energy crisis and environmental pollution. The augmented reality (AR) dashboard, a key feature of SEVs, is attracting considerable attention due to its ability to enhance driving safety and user experience through real-time, intuitive driving information. This study innovatively integrates Kansei engineering, factor analysis, fuzzy systems theory, analytic hierarchy process, grey relational analysis, and factorial experimentation to evaluate AR dashboards’ visual imagery and subjective preferences. The findings reveal that designs featuring blue planar and unconventional-shaped dials exhibit the best performance in terms of visual imagery. Subsequent factorial experiments confirmed these results, showing that drivers most favor blue-dominant designs. Furthermore, in unconventional-shaped dial designs, the visual effect of vertical 3D is more popular with drivers than horizontal 3D, while the opposite is true in round dials. This study provides a scientific evaluation method for assessing the emotional experience of AR dashboard interfaces. Additionally, these findings will help reduce the subjectivity in interface design and enhance the overall competitiveness of SEV vehicles.
Publisher
MDPI AG
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