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In recent years it seems we have been continuously bombarded by research and popular press articles dealing with the dangers of driver distraction, particularly that resulting from the use of cell phones or other telematic systems while behind the wheel. Based on the volume and vitriolic nature of these articles, one would suppose that the U.S. was undergoing a dramatic increase in the number of accidents on our roadways, largely as a function of operators focusing on these devices, rather than on the road. In reality, the opposite is true. Fifty years worth of vigilance research suggests that our entire perspective on the “driver distraction” problem may be incorrect. It is possible that we are fixating on the result of a problem, rather than on a problem cause. Research has repeatedly demonstrated that high workload levels negatively affect performance; what is less well-recognized is that too low of a workload level has virtually the same impact.

This paper describes the cluster analysis technique and how it can be used to support menu interface design for in-vehicle multimedia applications. Cluster analysis and similar types of classifying techniques have proven effective for developing simple menu interfaces. This paper extends the use of the cluster analysis technique to a more complex system that consists of 201 generic functions. These functions are representative of those being incorporated into near-term multimedia products. Study results show promise for using cluster analysis as a tool for incorporating the user's organizational structure into the design of a complex menu architecture. Cluster analysis may also benefit the automotive menu designer by providing a means for partitioning menu tasks into chunkable units that can be easily accessed by the driver in single glances.