Inattentional Blindness in Augmented Reality Head-Up Display-Assisted Driving

ABSTRACT

Augmented reality head-up display (AR HUD) is a new technology in assisted driving, which can add extra information to the driving environment in real-time to help the driver better perceive road situation. AR HUD can enhance driving safety but may also encourage inattentional blindness. Hence, this study aims to examine whether AR HUD-induces inattentional blindness and determine whether workload intensifies their relationship. In experiment 1, 60 participants were randomly assigned to three groups and watched three types of augmented reality (AR)-augmented driving videos, respectively. They were instructed to respond to any critical events, but only their responses to road-crossing pedestrians were recorded. Results show that AR HUD reduces inattentional blindness when pedestrians are augmented but encourages inattentional blindness when pedestrians are not augmented. In experiment 2, 20 participants viewed AR-augmented driving videos of high and low workloads. Pedestrians were not augmented in all videos. Result reveals that a high workload induces more inattentional blindness than low workload. The finding confirms that AR HUD induces inattentional blindness, and a high workload will intensify this relationship. The future design of the AR HUD assisted-driving system should consider the risk of inattentional blindness and come up with corresponding countermeasures.

Disclosure of potential conflict of interest

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

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant [31900768]; Youth Innovation Special Project of Basic Scientific Research Foundation of Zhejiang Sci-Tech University under Grant [2020Q046]; Science and technology innovation activity plan of college students in Zhejiang Xinmiao Talents Program under Grant [2019R46035]; National College Student Innovation and Entrepreneurship Training Program of Zhejiang Sci-Tech University under Grant [201910338003].

Notes on contributors

Yuwei Wang

Yuwei Wang is a graduate student at the Department of Psychology, Zhejiang Sci-Tech University. Her research interests include traffic safety, user experience design, human–computer interaction.

Yimin Wu

Yimin Wu is an undergraduate student at the Department of Psychology, Zhejiang Sci-Tech University. His research interests include user experience and human–computer interaction.

Cheng Chen

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

Bohan Wu

Bohan Wu is a graduate student at the Department of Psychology, Zhejiang Sci-Tech University. His research interests include user experience design and ergonomics.

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.

Duming Wang

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

Hongting Li

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

Zhen Yang

ZhenYang 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 neuroergonomics.