Automated vehicles with conditional driving automation (SAE level 3 (SAE, 2018)) will request the human driver to intervene when reaching its system boundaries by issuing a take-over request (TOR). This study is investigating whether a speech-based auditory take-over request is influencing the time it takes from automated to manual driving, taking into account the personality trait of the human driver based on theory of Goldberg (1992). The audible warning is based on a woman's voice, varying in three levels of urgency, speech-rate and syntax, and incorporate a lateral deviation measurement by varying the lane width. Due to the COVID-19 pandemic, the experiment was changed to a N=1-study, meaning that only one participant, namely the lead researcher, partook in his own experiment. The driving experiment consisted of 81 runs, each having a TOR after approximately 8 minutes of automated driving. When the automated vehicle is in control, the human driver is asked to do a secondary task, namely the challenging game Tetris on a tablet to get distracted from the situation on the road. It was found that an increase in urgency (take-over type) means a decrease in take-over time (TOT). No significant differences were found for the speech-rate in relation to the TOT, whereas for the syntax, only the STR and UTR had significant differences. Lateral deviation was found to increase when urgency increases, which means that accuracy decreases with higher urgency. Overall, a final design is given based on the results of the N=1-study which could be used for a larger experiment including the personality trait.