This paper investigates the effects of age, gender, and situational factors on take-over performance in automated driving. The existing automated driving systems still consider a driver as a fallback-ready user who is receptive to take-over requests. Thus, we need to understand the impact of situations and human factors on take-over performance. 34 drivers drove on a simulated track, consisting of one baseline and four event scenarios. The data, including the brake reaction time and the standard deviation of lane position, and physiological data, including the heart rate and skin conductance, were collected. The analysis was performed using repeated-measures ANOVA. The results showed that there were significant age, gender, and situational differences in the takeover performance and mental workload. Findings from this study indicated that older drivers may face risks due to their degraded driving performance, and female drivers may have a negative experience on automated driving.
