Abstract
Level 2 automated vehicles (AVs) have been commercially available for years, yet the extent to which drivers are cognizant of their capabilities and limitations remains largely unknown. This study aimed to assess the public’s mental model of Level 2 AVs and investigate the relationships between mental model, trust, and reliance. Moreover, it sought to explore driver heterogeneity through cluster analysis to identify typical driver classes. Employing Tesla Autopilot as a representative Level 2 automation system, we designed a questionnaire measuring mental model from three dimensions: functional condition, sensorimotor preparation, and automation monitoring. This questionnaire was administered to both Tesla Autopilot owners (N = 357) and non-owners (N = 357). The results showed that, on average, drivers possessed an inadequate mental model regarding Level 2 AVs, and those with a relatively better mental model exhibited lower levels of trust and reliance. Owning a Level 2 AV did not result in a better understanding of the system, but it led to a higher trust level. Moreover, the results suggested that drivers’ trust and reliance in AVs tended to increase within the initial 6 months of usage and then kept stabilized after that. Through cluster analysis, we identified three distinct driver classes that exhibited significant differences in their mental model levels and attitudes towards AVs: Class 1 (blurred positive), Class 2 (sober neutral), and Class 3 (cautiously positive). This further validates the presence of heterogeneity among drivers. The insights gained from this study can serve as a valuable resource for supporting and guiding the development and implementation of training programs aimed at enhancing drivers’ comprehension of Level 2 AVs.
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More From: International Journal of Human–Computer Interaction
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