Optimizing Takeover Performance: Balancing Warning Information Amount for Urgent and Non-Urgent Autonomous Transitions

Abstract

Informative warnings can improve takeover performance in automated vehicles, but improper or excessive information may hinder it. This study investigates the optimal amount of information in urgent and non-urgent autonomous takeover transitions. Forty-five drivers were randomly assigned to groups receiving different amounts of the selected takeover warning information elements. Each group completed simulated takeover tasks in four scenarios with different urgency. Takeover performance, situation awareness, and stress levels were measured. The results indicate that, in urgent situations, single-element assistance delays takeover response, while three elements increase failure risk. However, dual-element assistance yields faster response, equivalent awareness, and minimal stress. In non-urgent situations, having three elements leads to the best awareness and lowest stress compared with having fewer elements. In conclusion, an appropriate and non-overwhelming level of information facilitates urgent takeover performance, whereas greater information is advantageous in non-urgent cases. These findings provide insights into designing appropriate warning amount assistants for automated driving takeover requests across varying time-pressure situations.