Evaluating the Effectiveness of Contact-Analog and Bounding Box Prototypes in Augmented Reality Head-Up Display Warning for Chinese Novice Drivers Under Various Collision Types and Traffic Density

Abstract

Augmented Reality Head-Up Display (AR-HUD) is a promising solution to the current warning system distraction problem. However, how to effectively convey warnings through AR graphics is still unclear. This study examines the effectiveness of the contact-analog graphic compared to the bounding box graphic in various collision types and traffic densities. Forty-eight participants watched AR-augmented driving videos and were instructed to respond to critical events. Reaction time, response rate, and subjective evaluations were compared for rear-end and pedestrian collisions in different traffic densities under different warnings. Both bounding box and contact-analog warnings improved driving performance compared to the non-warning group. The contact-analog warning performed better for rear-end collisions, while the bounding box warning had a lower reaction time for pedestrian collisions, regardless of traffic density.

Keywords:

• AR-HUD
• bounding box warnings
• contact-analog warnings
• world-fixed graphics
• conformal graphics
• collision type
• traffic density

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China under Grants (72371228, T2192930, T2192931, and 31900768).

Notes on contributors

Wanting Chen

Wanting Chen is a graduate student at the Department of Psychology, Zhejiang Sci-Tech University. Her research interests include traffic safety, augmented reality, and human–computer interaction.

Liuqiucheng Niu

Liuqiucheng Niu is a graduate student at the Department of Psychology, Zhejiang Sci-Tech University. Her research interests include user experience and human–computer interaction.

Shan Liu

Shan Liu is a graduate student at the Department of Psychology, Zhejiang Sci-Tech University. Her research interests include ergonomics and human–computer interaction.

Shu Ma

Shu Ma is a PhD researcher at the Department of Psychology, Zhejiang Sci-Tech University. Her research interests include human–computer interaction, traffic safety, and automated driving.

Hongting Li

Hongting Li is a professor at the Department of Psychology, Zhejiang University of Technology. His research interests include human–computer interaction, ergonomics, user experience, augmented reality, and virtual reality.

Zhen Yang

Zhen Yang is an assistant professor at the Department of Psychology, Zhejiang Sci-Tech University. His research interests include human–computer interaction, human factors, user experience, cognitive science, and neuroeconomics.