Optimizing the HMI Design for the Takeover Request in Conditional Automated Driving

In the era of the prevalence of artificial intelligence, automated driving technology, as a small branch, can effectively reduce the number of traffic accidents and create a safer road environment. However, before full automation is achieved, drivers still need to take over the vehicle in some sudden dangerous situations that the driving system cannot handle. Therefore, designing an efficient and user-friendly on-board human-machine interface (HMI) is crucial. This study compared three different visual signals (i. only takeover icon, ii. takeover icon and countdown, iii. takeover icon, countdown and specific danger type prompt as well as suggested measures) combined with two auditory signals (i. only prompt sound, ii. prompt sound and specific voice prompt) through questionnaires and face-to-face interviews. Each signal contains different levels of situational awareness information to test whether they can improve the takeover effect. The research results show that when the prompt signal contains more high-level situational awareness information about the environment, it can significantly help drivers to recover their perception and understanding of the surrounding environment faster after engaging in non-driving tasks. These findings provide insights for the design and implementation of on-board human-machine interfaces (HMIs), improving takeover performance and user experience.