Current automated vehicles depend on takeover requests to notify drivers when system limitations occur, and informative takeover requests that communicate contextual environmental information, such as potential road hazards, have been found effective in controlled driving experiments. However, the robustness of informative takeover requests across diverse traffic scenarios and various driver mental states remains unclear. Therefore, this study investigated how mental states (anger, sadness, happiness, mind-wandering, external distraction, fatigue), scenarios (lane changing and lane keeping), and modalities (visual and tactile signals) affect takeover performance through reaction time, decision-making time, and decision-making accuracy while adopting informative takeover requests. The results showed lower decision-making accuracy in lane-keeping than in lane-changing scenarios, with tactile signals providing marginally greater accuracy than visual signals. No main effects of mental states were found on takeover performance. Overall, the findings may inform the development of advanced human-machine interfaces across different mental states in automated systems.
Lo et al. (Wed,) studied this question.
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