Differences in drivers’ dependence on AR warning information in urban driving environments: the role of driving experience - Huo, Faren; Alla, Rubanka (Frontiers in Virtual Reality, 2025)
Augmented Reality Head-Up Displays (AR HUDs) have been shown to enhance drivers’ performance and road safety. However, with the growing attention to trust in automated driving systems, excessive reliance on automation may lead to complacency and dependency. This study therefore aimed to examine how drivers with different levels of experience depend on AR warning messages under varying environmental conditions (daytime vs. nighttime urban driving) and to propose strategies for optimizing AR warning interaction design. A before-and-after comparative experimental design was employed. Participants completed driving tasks involving a typical urban hazard—pedestrians suddenly running into the road—under two conditions: (1) without AR warning messages and (2) with an induced random AR warning failure in an AR message environment. The perceived time-to-pedestrian values were analyzed to quantify driving dependence. Participants were divided into experienced and novice driver groups, and the effects of driving experience and lighting condition were examined. Objectively, both experienced and novice drivers’ dependence on AR warning messages was primarily influenced by the driving environment. Under high-load conditions such as nighttime driving, both groups maintained higher attention and exhibited minimal dependence on AR warnings. Under lower-load daytime conditions, dependence varied by driving experience: experienced drivers remained self-reliant due to ingrained driving habits and situational awareness, while novice drivers displayed increased relaxation and dependence on AR cues. Subjectively, drivers’ perceived dependence and anticipation of AR warnings correlated more strongly with the perceived intrusiveness of the AR system than with its effectiveness. These findings suggest that dependence on AR HUD warning messages is a complex interaction between environmental load, user experience, and perceived system intrusiveness. To mitigate automation complacency, future AR HUD design should tailor warning strategies according to user experience levels and driving context. The study provides practical insights for optimizing AR interaction design and highlights directions for future research to address additional urban driving risks.