Effects of AR-HMD Interactive Interface Layout on Usability and Obstacle Avoidance in Subway Overhauls

Abstract

The maintenance and overhaul of rail transit vehicle frames are vital for ensuring the safe and reliable operation of equipment. AR-based maintenance has been proven to be cost-reducing and effective. Few studies explored the application of AR-based maintenance on subway overhaul. In this study, 74 participants were selected to conduct the underground maintenance AR recognition and obstacle avoidance experiment. And two-factor ANOVA, independent samples t-test, and non-parametric test were used for data statistics. The results show that a high-opacity AR interface has better recognition but affects obstacle avoidance. Facing different types of obstacles, AR interfaces with different layouts have significant differences in terms of recognizability and obstacle avoidance effects. Compared with the list layout, the matrix layout AR interface will make more effort for workers. The findings provide useful references for designing the visual information layout of AR interfaces and conducting usability testing of AR interfaces in complex scenarios such as underground maintenance. Highlights This study assessed the effects of the AR-HMD interface on workers’ recognition of and ability to safely avoid obstacles in a subway maintenance environment. A high-opacity AR interface leads to better recognition but affects obstacle avoidance. List AR interfaces lead to better recognition but increase the probability of obstacle avoidance failure by 50% under block obstacles. For linear obstacles, layout has no significant effect on recognition or obstacle avoidance. A matrix layout AR interface is more effortful than the list layout AR for the workers.