A Study on Optimizing Digital Gauge Cluster Designs Based on Eye-Tracking Data

The rapid advancement of autonomous and electric vehicles has accelerated the adoption of digital technology in the automotive industry, leading to the digitalization of vehicle information display systems. The study investigated the effects of Dash type (Dual vs. Single) and Color (Black vs. White) on user information perception within digital gauge clusters. Eye-tracking technology was used to measure key metrics such as first fixation duration (TFF), fixation duration (FD), fixation count (FC), and revisit count (RC). A post-experiment questionnaire was also conducted to evaluate user preferences and overall performance. The results showed that a dual dash with a white color significantly improved user engagement and information processing efficiency compared to a single dash with a black color. ANOVA analysis revealed that both dash type and color had a significant independent effect on TFF, FD, FC, and RC. Particularly, the interaction effect in TFF and FD showed that the effect of dash type varied depending on the color. On the other hand, the interaction effects on FC and RC were insignificant, indicating that these factors acted independently. In conclusion, dash type and color influence users’ attention and information processing, and the interaction between initial attention and ease of understanding is crucial. This study is expected to contribute to improving user experience and driving safety by improving digital gauge cluster design.