The impact of different AR-HUD virtual warning interfaces on the takeover performance and visual characteristics of autonomous vehicles

平视显示器 接口(物质) 增强现实 超车 计算机科学 挡风玻璃 模拟 影子(心理学) 工程类 计算机视觉 运输工程 气泡 心理学 最大气泡压力法 并行计算 航空航天工程 心理治疗师
作者
Chunhui Jing,Chenguang Shang,Dongyu Yu,Yaodong Chen,Jinyi Zhi
出处
期刊:Traffic Injury Prevention [Taylor & Francis]
卷期号:23 (5): 277-282 被引量:21
标识
DOI:10.1080/15389588.2022.2055752
摘要

Objective The objective of this study was to determine the different effects of the arrow-pointing augmented reality head-up display (AR-HUD) interface, virtual shadow AR-HUD interface, and non-AR-HUD interface on autonomous vehicle takeover efficiency and driver eye movement characteristics in different driving scenarios.Methods Thirty-six participants were selected to carry out a simulated driving experiment, and the eye movement index and takeover time were analyzed.Results The arrow pointing AR-HUD interface and the virtual shadow AR-HUD interface could effectively reduce the driver's visual distraction, improve the efficiency of obtaining visual information, reduce the number of times the driver's eyes leave the road, and improve the efficiency of the takeover compared with the non-AR-HUD interface, but there was no significant difference in eye movement indexes between the arrow pointing AR-HUD interface and the more eye-catching virtual shadow AR-HUD interface. When specific scenarios were considered, it was found that in the scenario of emergency braking of the vehicle in front, the arrow pointing AR-HUD interface and the virtual shadow AR-HUD interface had more advantages in takeover efficiency than the non-AR-HUD interface. However, in the scenarios of a rear vehicle overtaking the vehicle ahead and non-motor vehicles running red lights, there was no significant difference in takeover efficiency. For the non-motor vehicle invading the line, emergency U-turn of the vehicle in front, and pedestrian crossing scenarios, the virtual shadow AR-HUD interface had the highest takeover efficiency.Conclusions These research results can help improve the active safety of autonomous vehicle AR-HUD interfaces.
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