Citation

Gaspar JG, Carney C, Shull E, Horrey WJ. Transp. Res. F Traffic Psychol. Behav. 2021; 81: 622-638.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trf.2021.07.012

PMID

unavailable

Abstract

Driver support features (DSF) 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 simulator study examined how drivers with different mental models of adaptive cruise control performed in edge cases. The study compared the responses of groups of drivers, with strong and weak mental models of ACC, established through a combination of screening, training, and exposure, in edge case situations in a high-fidelity driving simulator. 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.

Language: en

Keywords

Automation; Driver support features; Driving simulation; Mental models