A model-driven tool for getting insights into car drivers’ monitoring behavior

The Human Efficiency Evaluator (HEE) is a model-based tool that predicts car drivers' visual attention based on a variant of the SEEV model. Different to prior research that required individual human factor (HF) expertise to generate valid attention predictions, the HEE enables to collect data from a group of experienced car drivers, to simulate human monitoring behavior, and to end up with valid predictions. We invited two different groups: automotive human factors experts (n=9) and experienced car drivers (n=20) to predict car drivers' monitoring behavior for a highway overtaking scenario with the HEE. Previous research did not detail the amount and experience of the HF experts involved in generating predictions, whereas our study revealed a quite high variance of individual HF experts' predictions about drivers' typical monitoring behavior. We measured car drivers' monitoring behavior using an eye tracking device in a car driving simulator (n=20). The aggregated prediction of the group of car drivers was high (R=0.719) and better than the average prediction of an individual HF experts.