Investigating the Influence of Takeover Request Warning Methods on Driver Tension in Level 3 Automated Driving

Recently, the widespread use of e-commerce and online services has significantly increased the demand for logistics. Simultaneously, a shortage of drivers, largely owing to a declining workforce, has emerged as a critical issue. In response, there has been growing interest in autonomous driving technologies as a means of alleviating the burden on drivers. Level 3 autonomous driving, also referred to as conditional automation, allows vehicles to operate autonomously under certain conditions. However, the driver must control the vehicle outside these conditions. When transitioning from autonomous to manual driving, a takeover request (TOR) warning is issued by the system to prompt the driver to regain control. Previous studies have indicated that adjusting the level of tension caused by a TOR warning can improve driving performance after the warning is issued. However, limited research has focused on the specific warnings used in level 3 autonomous driving, especially those issued when the driver is fully disengaged from the driving task. Additionally, repeated exposure to warnings may result in habituation and thereby reduce the warning effectiveness over time.