Impacts of Automated Valet Parking Systems on Driver Workload and Trust

In the realm of automated driving, automated valet parking (AVP) systems represent a significant leap towards enhancing urban mobility and safety. While existing research has explored various aspects of AVP systems, there is a notable gap in the literature specifically addressing AVP systems in relation to their impact on driver workload and trust. This study evaluates a Level 2 AVP system implemented in a vehicle, focusing on its impact on driver workload and trust. We utilized eye-tracking, physiological monitoring, and self-reported surveys to capture driver responses during AVP operation compared to manual parking. Results indicated a trend towards reduced workload during AVP use, as suggested by eye-tracking data, and a decrease in physiological markers of stress, although these differences were not statistically significant. Driver trust in the AVP system significantly increased after hands-on experience. However, an increase in mobile device usage signaled potential issues of overreliance on automation. The findings underscore the importance of integrating human factors into AVP system design to balance workload reduction with the prevention of overreliance, ultimately enhancing driver engagement and calibrating trust.