The Interplay Between Driver Dynamic Trust and Their Self-Confidence in Monitoring Automation

Abstract

As vehicles become increasingly automated, understanding how drivers trust these systems is crucial for both safety and effective use. Our research explores how drivers’ moment-to-moment trust in vehicle automation relates to their self-confidence in detecting system errors. Using simulated driving scenarios, we observed how drivers monitored automated systems under varying traffic conditions and automation performance. Our preliminary findings highlight that while higher traffic demands and automation errors negatively impact drivers’ ability to detect system errors, their trust aligns more closely with their selfconfidence in judging automation performance than with their perceptual sensitivity or decision criteria. This study provides insights into the psychological processes influencing driver interactions with automation and emphasizes the unique role of self-confidence in effective monitoring. Understanding these dynamics can support the design of automated systems that promote safer driving behaviors.