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The introduction of Advanced Driver Assistance Systems (ADAS) presents new human factors challenges. Research indicates that users often lack sufficient knowledge about these systems, which can impair hazard avoidance abilities. Improving users’ mental models and knowledge can foster safer interactions with vehicle automation. However, hazard avoidance for ADAS differs from traditional driving due to system-specific changes that influence how vehicles respond and control themselves and how drivers should monitor and respond. Failure to recognize these changes may have serious consequences. Error-based training approaches have been effective in improving drivers’ mental models and hazard avoidance. A new training program was developed utilizing Virtual Reality (VR) to enhance understanding of adaptive cruise control (ACC) and develop hazard avoidance skills. In a mixed-subject design, 36 participants were assigned to one of three groups: VR training, state diagram (SD) visualization, or basic text (BI) information. Mental models were assessed before and after training, and driving simulator data captured interactions with ACC and hazard avoidance. Findings showed that while the VR training influenced mental models and hazard avoidance, the effects were not statistically significant. Notably, VR training positively impacted participants’ glance behavior during edge case events—an intended training goal. Relationships between training and mental models emerged, although no significant correlations were found between mental models and hazard avoidance behaviors. These findings address a literature gap regarding hazard avoidance in vehicle automation and suggest that VR training could be expanded to include more ADAS features, fostering improved training in an increasingly automated driving landscape.
Pai et al. (Fri,) studied this question.