As driver distraction from in-vehicle devices becomes an increasingly critical issue, researchers have aimed to establish better scientific understanding of distraction along with better engineering tools to build less distracting devices. This article presents a new system, Distract-R, that allows designers to rapidly prototype and evaluate new in-vehicle interfaces. The core engine of the system relies on a rigorous cognitive model of driver behavior which, when integrated with models of task behavior on the prototyped interfaces, generate predictions of driver performance and distraction. Distract-R allows a designer to prototype basic interfaces, demonstrate possible tasks on these interfaces, specify relevant driver characteristics and driving scenarios, and finally simulate, visualize, and analyze the resulting behavior as generated by the cognitive model. The article includes three modeling studies that demonstrate the system’s ability to account for various aspects of driver performance for several types of in-vehicle interfaces. More generally, Distract-R illustrates how cognitive models can be used as internal simulation engines for design tools intended for nonmodelers, with the ultimate goal of helping to understand and predict user behavior in multitasking environments. (Author/publisher)
Abstract