Computational Modeling of Driving Behaviors: Challenges and Approaches

Abstract

Computational modeling has great advantages in human behavior research, such as abstracting the problem space, simulating the situation by varying critical variables, and predicting future outcomes. Although much research has been conducted on driver behavior modeling, relatively little modeling research has appeared at the Auto-UI Conferences. If any, most work has focused on qualitative models about manual driving. In this workshop, we will first describe why computational driver behavior modeling is crucial for automotive research and then, introduce recent driver modeling research to researchers, practitioners, and students. By identifying research gaps and exploring solutions together, we expect to form the basis of a new modeling special interest group combining the Auto-UI community and the computational modeling community. The workshop will be closed with suggestions on the directions for future transdisciplinary work.