Physiological Assessment of Driver Trust in Automated Vehicles under Distinct Driving Styles

Abstract

With the rapid advancement of automated vehicle (AV) technology, drivers’ willingness to rely on AV systems has become a decisive factor in their broader deployment. Among the many psychological determinants, drivers’ trust has been consistently identified as a key condition influencing the acceptance and appropriate use of AVs. Consequently, understanding how trust evolves during real-time interaction with an AV is increasingly critical for determining whether drivers can engage with the system safely and effectively. Current research on trust assessment often relies on subjective measures, yielding limited temporal resolution and vulnerability to subjective bias. This study proposes a multimodal, event-driven experimental framework to investigate how different AV driving styles affect driver trust through objective physiological signals. First, a driving simulation experiment was designed with three distinct driving styles: a) a baseline scenario featuring smooth, normative driving to establish physiological reference physiological states; b) a hesitant scenario characterised by cautious and delayed decision-making; and c) an aggression condition characterised by late braking and assertive, high-speed cornering. Each participant experienced all conditions in counterbalanced order. Second, participants’ physiological responses were recorded using a synchronised multi-sensor setup, including electroencephalography (EEG) and eye-tracking. Subjective trust ratings were collected after each scenario to serve as the ground truth for trust evaluation. Finally, the collected signals were integrated to analyse the correlation between trust level and physiological features. The results suggest that aggressive and hesitant driving styles elicit distinguishable subjective, neural, and attentional responses, indicating different pathways of distrust. These findings provide preliminary evidence supporting the feasibility of physiology-based approaches for assessing driver trust in automated driving.

Keywords: Automated Vehicle, Driver’s Trust, Driving Styles, Physiological Signals, Driving Simulation

DOI: 10.54941/ahfe1007863