Linda S. Angell

An Evaluation of Alternative Methods for Assessing Driver Workload in the Early Development of In-Vehicle Information Systems

This study examined whether the effect of subsidiary tasks on driving performance can be predicted from stationary (static) testing. Alternative methods for assessing the performance of drivers during their use of in-vehicle information systems were examined. These methods included static testing in stationary vehicles, as well as dynamic, on-road testing. The measures that were obtained from static tests were evaluated in terms of how well they could predict measures obtained from driving performance during on-road testing (which included concurrent use of secondary information systems). The results indicated that measures obtained in static test settings were highly correlated with corresponding measures obtained from on-road performance testing. Also, the regression slopes and intercepts of on-road driving performance measures when predicting on-road lane deviations were more closely approximated under static conditions which required drivers to attend to concurrent, driving-like activities as well as secondary tasks. It is suggested that tests using multiple measures, together with a multivariate model, may hold the most promise for predicting eventual on-road driver performance in the early development of in-vehicle information systems. Although additional research and theoretical development are required, this research demonstrates that a set of relatively simple measures obtained analytically and from static testing can be used even now to help guide early system development.

An Exploratory Study of Vehicle Type in Alcohol-Related Crashes

This report describes an exploratory statistical analysis of two large national traffic accident databases (NASS and FARS) to determine whether certain car types are at higher risk of being driven by crash-involved drinking drivers. A primary objective of the research was to provide a new perspective with which to identify and study the types of persons who tend to crash while driving after drinking.