Shu Wang
Augmented reality prototype HUD for passenger infotainment in a vehicular environment
Wang, Shu; Charissis, Vassilis; Harrison, David K.
Abstract
The paper presents a prototype Head Up Display interface which acts as an interactive infotainment system for rear seat younger passengers, aiming to minimize driver distraction. The interface employs an Augmented Reality medium that utilizes the external scenery as a background for two platform games explicitly designed for this system. Additionally, the system provides AR embedded information on major en route landmarks, navigational data, and local news amongst other infotainment options. The proposed design is applied in the peripheral windscreens with the use of a novel Head-Up Display system. The system evaluation by twenty users offered promising results discussed in the paper.
Citation
Wang, S., Charissis, V., & Harrison, D. K. (2017). Augmented reality prototype HUD for passenger infotainment in a vehicular environment. Advances in Science, Technology and Engineering Systems Journal, 2(3), 634-641. https://doi.org/10.25046/aj020381
Journal Article Type | Article |
---|---|
Acceptance Date | May 15, 2017 |
Online Publication Date | Jun 4, 2017 |
Publication Date | Jun 4, 2017 |
Deposit Date | Apr 18, 2023 |
Publicly Available Date | Jun 27, 2023 |
Journal | Advances in Science, Technology and Engineering Systems |
Peer Reviewed | Peer Reviewed |
Volume | 2 |
Issue | 3 |
Pages | 634-641 |
DOI | https://doi.org/10.25046/aj020381 |
Keywords | head up display; augmented reality; infotainment systems; driving simulator; driving patterns; driving scenarios; children; driver distraction; educational games; games |
Files
Augmented reality prototype HUD for passenger infotainment in a vehicular environment
(1.4 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by-sa/4.0
You might also like
Use and operational safety
(2023)
Book Chapter
A stacking ensemble of deep learning models for IoT intrusion detection
(2023)
Journal Article
Federated Learning for IoT Intrusion Detection
(2023)
Journal Article
A Stacking Ensemble of Deep Learning Models for IoT Network Intrusion Detection
(2023)
Preprint / Working Paper
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search