Exploring the trust and behavior of experienced advanced driver assistance system drivers: An on-road study

Trust in automation is crucial for the optimal utilization of advanced driver assistance systems (ADAS). While previous studies have examined trust in automated driving (TiAD) and its impact on behavior, there remains a need to explore how experienced drivers interact with partially automated systems in real-world contexts. This study investigates the trust and behavior of 34 experienced ADAS drivers, divided into trustful and distrustful groups, during on-road driving encompassing six typical scenarios. This study evaluates the initial and final TiAD, situational trust across six driving scenarios; and behaviors, including hands-off the steering wheel, engagement in non-driving-related activities (NDRAs), and visual behavior. Results reveal no significant change in TiAD between pre- and post-driving evaluations, but there are significant differences in TiAD and situational trust across six scenarios between the trustful and distrustful groups. Regarding behavior, trustful drivers exhibit more hands-off events and delay responses to warnings. Both groups engage in risky NDRAs with different patterns, while trustful drivers showing a higher tendency for high-risk NDRAs. Visual behavior analysis shows that trustful drivers spend less time monitoring the driving environment, particularly in complex scenarios such as lane addition/reduction, but more time focusing on the human-machine interface (HMI) overall compared to distrustful drivers. The study also explores the impact of ADAS type and mileage, showing that drivers with advanced functionality exhibit higher trust and reduced monitoring, while mileage influence trust with a turning point at around 3,000 km. With these findings, this study highlights safety risks and proposes strategies to address them. This study is expected to provide insights into trust research and ADAS optimization, enhancing driving safety and user experience.