Human behavior models give insight into people's choices and actions and are tools for predicting performance and improving interface design. Most models focus on a task's cognitive aspects or its physical requirements. This research addresses the divide between cognitive and physical models by combining two models to produce an integrated cognitive-physical human model that enables studying of complex human-machine interactions. The capabilities of the integrated model are evaluated in a task scenario with both cognitive and physical components, i.e., driving while performing a secondary in-vehicle task. When applied in this way, the integrated model is called the Virtual Driver model and can replicate basic driving, in-vehicle tasks, and resource-sharing behaviors, providing a new way to study driver distraction. The model has applicability to interface design and predicting staffing requirements and performance.
|Journal||IEEE transactions on intelligent transportation systems|
|Publication status||Published - 2012|
Demcenko, A., Tamosiunaite, M., Vidugiriene, A., & Jakevicius, L. (2012). Estimation of lane marker parameters with high correlation to steering signal. IEEE transactions on intelligent transportation systems, 13(2), 962-967. https://doi.org/10.1109/TITS.2012.2182764