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

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.