Examining driving behaviors and trust in an in-vehicle warning system under uncertainty: A roundabout study

Advanced driver assistance systems (ADASs) can greatly enhance road safety by providing real-time warnings to drivers in imminent crash situations. However, the provided warning time may deviate from its designed time. There is limited research on how warning uncertainties influence drivers’ behavior, safety performance, and trust. This study conducted a driving simulator study to examine how uncertainties in warnings impact driving behaviors and trust using a roundabout driving scenario. Two warning error distributions were constructed to represent low and high warning uncertainty levels. Thirty-six participants were recruited and randomly divided into two groups under the two uncertainty levels in a driving simulator experiment. The between-group analysis shows that the lower warning uncertainty level group results in higher trust and that trust increases (or decreases) over time under low (or high) uncertainty levels. The within-group analysis shows that higher warning errors downgrade drivers’ trust and safety performance when the errors are high. Finally, a personalized trust prediction model was developed using demographic and vehicle movement data, and the XGBoost model achieved the best performance with 86.42% accuracy.