Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/119362
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dc.contributorDepartment of Aeronautical and Aviation Engineeringen_US
dc.creatorSun, Yen_US
dc.creatorLi, Den_US
dc.creatorHan, Sen_US
dc.creatorLyu, Men_US
dc.creatorLi, Fen_US
dc.date.accessioned2026-06-17T01:33:45Z-
dc.date.available2026-06-17T01:33:45Z-
dc.identifier.issn1071-5819en_US
dc.identifier.urihttp://hdl.handle.net/10397/119362-
dc.language.isoenen_US
dc.publisherAcademic Pressen_US
dc.subjectARHUDen_US
dc.subjectBlind spotsen_US
dc.subjectCognitive modelen_US
dc.subjectDriving safetyen_US
dc.subjectSituation awarenessen_US
dc.titleARHUD design for dynamic spatial information presentation to improve driver situation awareness of blind spotsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume211en_US
dc.identifier.doi10.1016/j.ijhcs.2026.103793en_US
dcterms.abstractBlind spots remain a major contributor to traffic accidents by undermining drivers’ situation awareness (SA). Although modern vehicles are equipped with sensors that detect obstacles in the blind spots, communicating this information effectively remains a challenge due to the mismatch between the system displays and the spatial perception of drivers. To address this issue, we propose a novel augmented reality head-up display (ARHUD). Based on mental folding theory, our design treats the front windshield as a spatial projection of the vehicle’s surroundings, mapping blind spot hazards to its peripheral edges. A color-coded distance scheme further supports rapid hazard recognition and risk assessment. A multi-scenario driving simulation experiment (N = 60) was conducted with four information presentation modalities (the proposed ARHUD, a prior ARHUD design, in-vehicle display, and auditory alerts) across urban and highway environments. Results show that our ARHUD significantly improves hazard detection, attention allocation, and cognitive efficiency. These findings enhance the design of blind spot visualizations and promote safer, more intuitive ARHUD systems for intelligent vehicles.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationInternational journal of human computer studies, Apr. 2026, v. 211, 103793en_US
dcterms.isPartOfInternational journal of human computer studiesen_US
dcterms.issued2026-04-
dc.identifier.scopus2-s2.0-105034590538-
dc.identifier.eissn1095-9300en_US
dc.identifier.artn103793en_US
dc.description.validate202606 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG001859/2026-05-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis study was supported by the Smart Traffic Fund (PSRI/43/2207/PR).en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2028-04-30en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Status embargoed access
Embargo End Date 2028-04-30
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