A Novel Cooperation-Guided Warning of Invisible Danger from AR-HUD to Enhance Driver’s Perception

Abstract

Augmented Reality (AR) has the potential to help drivers become aware of invisible hazards through an Augmented Reality Head-Up Display (AR-HUD). However, this issue is still underexplored. To address it, a novel warning system for invisible dangers in AR-HUD user interfaces has been designed as a carrier for agents' cognitive information to enhance driver perception. This design was created by using a team cooperation perception model that combined the perception cycle of a human driver with a computational agent. Furthermore, user experiments were conducted to investigate the impact of this design on safe driving in two typical scenarios. The experimental results showed that this design can significantly improve drivers’ situation awareness and reaction time in both human-driving and auto-pilot modes, and enhance human drivers' trust in the auto-pilot system. The model and design can be generalized to more AR-HUD scenarios requiring human-machine perception and cognitive cooperation.

Keywords:

• Human-machine cooperation
• AR-HUD
• human-machine teaming
• human-vehicle cooperative interface
• autonomous driving

Disclosure statement

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

Notes

1 See https://unity.cn/.

2 See https://pingouin-stats.org/index.html.

3 See https://scipy.org/.

4 See https://plotnine.readthedocs.io/en/stable/.

Additional information

Funding

This research was supported by the National Social Science Fund of China (No.19FYSB040); CES-Kingfar Excellent Young Scholar Joint Research Funding (No. 202002JG26); Association of Fundamental Computing Education in Chinese Universities (2020-AFCEC-087); Association of Fundamental Computing Education in Chinese Universities (2020-AFCEC-088); the Fundamental Research Funds for the Central Universities.

Notes on contributors

Fang You

Fang You is a professor at College of Arts and Media, Tongji University. Her research interests include user experience design, traffic safety, interactive design and human factors.

Jun Zhang

Jun Zhang is a PhD candidate at College of Design and Innovation, Tongji University and School of Design, The Hong Kong Polytechnic University. His research interests include augmented reality, human-agent interaction, human factors and user experience.

Jie Zhang

Jie Zhang is a PhD candidate at School of Design, The Hong Kong Polytechnic University. His research interests include computer-aided design, ergonomics design, interactive design and human factors, and 3D head modeling and analysis.

Lian Shen

Lian Shen is postgraduate student at College of Arts and Media, Tongji University. Her research interests include user experience design, human-agent interaction and traffic safety.

Weixuan Fang

Weixuan Fang is postgraduate student at College of Arts and Media, Tongji University. Her research interests include user experience design, augmented reality and human-agent interaction.

Wei Cui

Wei Cui, is a postdoctoral researcher at the College of Design and Innovation, Tongji University, and Senior Researcher at the User Experience Laboratory, College of Arts and Media. Research interests include intelligent communication and interaction.

Jianmin Wang

Jianmin Wang is a professor at College of Arts and Media, Tongji University. His research interests include user experience design, traffic safety and interactive design.