United States Department of Transportation
i
The Impact of Driver’s Mental Models of Advanced Vehicle Technologies on Safety and Performance [supporting datasets]
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2020-05-01
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[PDF-140.76 KB]
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Abstract:Advanced driver assistance systems (ADAS) are rapidly being introduced across automobile manufacturer lineups. These technologies have the potential to improve safety, but they also change the driver-vehicle relationship—as well as their respective roles and responsibilities. To maximize safety, it is important to understand how drivers’ knowledge and understanding of these technologies—referred to as drivers’ mental models—impact performance and safety. This study evaluated the impact of the degree of accuracy (or quality) of drivers’ mental models of adaptive cruise control (ACC) on performance using a high-fidelity driving simulator. Participants with varying degrees of ACC experience were recruited and trained such that they had either a strong or weak mental model. Participants then completed a study where they interacted with the ACC system and encountered several edge-case events. In general, participants with strong mental models were faster than those with weak mental models to respond in edge-case situations— defined as cases where the ACC did not detect an approaching object, such as a slow moving motorcycle. The performance deficits observed for drivers with weak mental models appear to reflect uncertainty surrounding how ACC will behave in edge cases. These results raise several important questions surrounding driver introductions to ADAS and the need for training.
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