Some Characteristics of Mental Models of Advanced Driver Assistance Systems: A Semi-structured Interviews Approach

Abstract

People construct mental models—internal cognitive representations—when they interact with dynamic systems. The introduction of automation in vehicles has raised concerns about potential negative consequences of inaccurate mental models, yet characteristics of mental models remain difficult to identify. A descriptive study used semi-structured interviews to explore mental models of advanced driver assistance systems (adaptive cruise control, lane keeping assist, and Level 2 systems). Results exposed shortcomings in drivers’ understandings of the hardware, software, and limitations of these systems and also suggested that mental models will affect behavior while using automation. Further, we found that mental models can be influenced by interface feedback (or lack thereof) and limitations experienced. Some drivers attributed purposeful design to aspects of the systems that likely were chosen idiosyncratically or arbitrarily. Our findings offered potentially useful avenues for future research on mental models of automation and corroborated concerns that inaccurate mental models may be common.

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