The Effect of AR-HUD Takeover Assistance Types on Driver Situation Awareness in Highly Automated Driving: A 360-Degree Panorama Experiment

AbstractHuman-machine co-driving presents a significant hurdle in automated driving system. The takeover process in automated driving system involves complex human factors, failure to takeover the vehicle and control driving behavior during the takeover process may lead to severe traffic safety hazards. An augmented reality head-up display (AR-HUD) takeover assistance information can provide real-time assistance information to the driving environment, enhancing drivers’ situation awareness (SA) and takeover decisions in highly automated driving system. This study investigated the impact of different AR-HUD types of takeover assistance information display. Three AR-HUD types, corresponding to the three pre-takeover behavioral processes (perception, understanding, and prediction), were evaluated: PSR (assistance in perceiving the source of risk), AS (assistance in analyzing situations), and MD (assistance in making decisions). The baseline (without assistance information) was used as the control group. In a driving simulation experiment using 360° panoramic video, seventy-nine participants performed SA assessment and visual tracking tasks. Questionnaire and eye-tracking data indicated that the type of AR-HUD displayed positively influenced drivers’ SA and takeover decisions, with AS being the most effective in enhancing SA and improving takeover performance. Additionally, this study compared the differences between the three types of AR-HUD and the baseline under two takeover request lead times (TORlt) of 5 seconds and 7 seconds. It was found that drivers’ SA was lower when TORlt was shorter (with the corresponding AR-HUD display also being shorter). This study provides insight concerning the impact of various types of AR-HUD takeover assistance information display and TORlt on driving safety. The findings support the further optimization of AR-HUD takeover assistance information design.Keywords: Automated drivingsituation awarenesstakeover decisionAR-HUD takeover assistance informationeye-tracking Disclosure statementThe authors declared that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Additional informationFundingThis work was supported by Humanities and Social Science Foundation, the Ministry of Education of China under Grant number 22YJA760001, Social Science Foundation of Fujian province under Grant number FJ2021B178.Notes on contributorsZhendong WuZhendong Wu is an Associate Professor in the Department of Industrial Design at College of Mechanical Engineering and Automation within Huaqiao University. His current research interests encompass human-computer interaction, virtual reality, 3D animation, and digital heritage preservation.Lintao ZhaoLintao Zhao obtained his master’s degree from the Department of Industrial Design at College of Mechanical Engineering and Automation within Huaqiao University. His current research interests encompass user experience measurement using virtual reality, human-computer interaction, and halo environment usability design.Guocui LiuGuocui Liu is a junior undergraduate student in the Department of Industrial Design at College of Mechanical Engineering and Automation within Huaqiao University. Her current research interests include human-computer interaction and virtual interaction.Jingchun ChaiJingchun Chai is a master’s student in the Department of Industrial Design at the College of Mechanical Engineering and Automation within Huaqiao University. His current research interests encompass spatial aesthetics, information visualization, and animation design.Jierui HuangJierui Huang is a junior undergraduate student in the Department of Industrial Design at College of Mechanical Engineering and Automation within Huaqiao University. His current research interests encompass user experience measurement using virtual reality and innovative design methodologies for augmented reality.Xiaoqun AiXiaoqun Ai serves as a professor in the Department of Industrial Design at Huaqiao University and is also a Ph.D. candidate at the Central Academy of Fine Arts in China. Her research focuses on spatial experience and light art design, pioneering methodologies in design.