Impact of highlighting strategies in AR-HUD and digital interfaces across scenario complexity
Driver situation awareness, visual attention, and workload
Bibliographic Data
| ID | 21452886 |
|---|---|
| Authors | Jue Li (0000-0001-6546-5683, Tongji University), YaFan Li (Nanjing Forestry University), 丽亚 范 (Nanjing Forestry University), Xuguang Wang (0000-0001-9181-6045, Tongji University), Long Liu (0000-0002-1520-8504, Tongji University, corresponding author) |
| Year | 2026 |
| Pages | 1-15 |
| Publication date | 2026-06-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Behaviour and Information Technology (JOURNAL) |
| Journal identifiers | ISSN: 0144-929X • E-ISSN: 1362-3001 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/0144929x.2026.2670379 |
| OpenAlex | W7163200871 |
| Language | EN |
| References cited | 62 |
The application of Augmented Reality Head-Up Display (AR-HUDs) in Automated Driving Systems (ADS) shows promise over traditional digital interfaces, but AR elements can potentially distract drivers. This study investigated whether AR-HUDs offer advantages in Situation Awareness (SA), visual attention, and workload compared to digital interfaces across different driving scenarios and interface design strategies. We simulated three levels of driving scenario complexity and implemented two highlighting strategies (CH: collision highlighting; PH: proximity highlighting) in both AR-HUD and digital interface conditions. 35 participants completed the simulated driving experiment while their visual attention, pupil diameter, subjective SA and workload were measured. Results showed that AR-HUDs significantly improved drivers’ SA and reduced workload compared to digital interfaces, particularly in complex scenarios. CH strategy more effectively directed attention to hazards; under AR-HUD conditions, CH led to smaller pupil diameter and lower workload. These findings highlighting AR-HUDs’ advantage in enhancing SA, especially when hazards information is presented intuitively. This study provides empirical evidence and practical recommendations for AR-HUD design in ADS, contributing to optimised driving safety, and improved user experience
Component (thermodynamics) · Key (lock) · User interface · Visualization · Work (physics) · Workload · Human-Automation Interaction and Safety · Spatial Cognition and Navigation · Virtual Reality Applications and Impacts
| Citation velocity | historical |
|---|---|
| Highly cited | No |