Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/119362
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Aeronautical and Aviation Engineering | en_US |
| dc.creator | Sun, Y | en_US |
| dc.creator | Li, D | en_US |
| dc.creator | Han, S | en_US |
| dc.creator | Lyu, M | en_US |
| dc.creator | Li, F | en_US |
| dc.date.accessioned | 2026-06-17T01:33:45Z | - |
| dc.date.available | 2026-06-17T01:33:45Z | - |
| dc.identifier.issn | 1071-5819 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/119362 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Academic Press | en_US |
| dc.subject | ARHUD | en_US |
| dc.subject | Blind spots | en_US |
| dc.subject | Cognitive model | en_US |
| dc.subject | Driving safety | en_US |
| dc.subject | Situation awareness | en_US |
| dc.title | ARHUD design for dynamic spatial information presentation to improve driver situation awareness of blind spots | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 211 | en_US |
| dc.identifier.doi | 10.1016/j.ijhcs.2026.103793 | en_US |
| dcterms.abstract | Blind 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.accessRights | embargoed access | en_US |
| dcterms.bibliographicCitation | International journal of human computer studies, Apr. 2026, v. 211, 103793 | en_US |
| dcterms.isPartOf | International journal of human computer studies | en_US |
| dcterms.issued | 2026-04 | - |
| dc.identifier.scopus | 2-s2.0-105034590538 | - |
| dc.identifier.eissn | 1095-9300 | en_US |
| dc.identifier.artn | 103793 | en_US |
| dc.description.validate | 202606 bchy | en_US |
| dc.description.oa | Not applicable | en_US |
| dc.identifier.SubFormID | G001859/2026-05 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | This study was supported by the Smart Traffic Fund (PSRI/43/2207/PR). | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.date.embargo | 2028-04-30 | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



