Effects of a color gradient and emoji in AR-HUD warning interfaces in autonomous vehicles on takeover performance and driver emotions

Abstract

Objective

This study examined the effects of color gradients and emojis in an augmented reality-head-up display (AR-HUD) warning interface on driver emotions and takeover performance.

Methods

A total of 48 participants were grouped into four different warning interfaces for a simulated self-driving takeover experiment. Two-way analysis of variance and the Kruskal–Wallis test was used to analyze takeover time, mood, task load, and system availability.

Results

Takeover efficiency and task load did not significantly differ among the interfaces, but the interfaces with a color gradient and emoji positively affected drivers’ emotions. Emojis also positively affected emotional valence, and the color gradient had a high emotional arousal effect. Both the color gradient and the emoji interfaces had an inhibitory effect on negative emotions. The emoji interface was easier to learn, reducing driver learning costs.

Conclusions

These findings offer valuable insights for designing safer and more user-friendly AR-HUD interfaces for self-driving cars.