Takeover and non-driving related task performance in conditional automated driving: EEG and behavior Parameters interaction

In this study, a conditional automated driving scenario is simulated using virtual reality (VR) technology to explore whether office works presented through augmented reality (AR) affect task and takeover performance, and the neural mechanism was revealed. Sixty-four participants were recruited and their electroencephalography (EEG) was used to measure the brain activities. The results indicated that non-driving-related tasks (NDRTs) requiring higher internal attention focus resulted in poorer task and takeover performance. The alpha power decline magnitude in the parietotemporal (PT) was positively correlated with the takeover time; and the greater the alpha power decline in the right centroparietal (CP) hemisphere, the worse is the participants' memory quality for NDRTs. The ventral attention network (VAN) and right parietal cortex, which are active during working memory, are more likely to explain these findings. The results can provide suggestions for the design of AR-ADS and help improve the safety in L3 driving automation systems.