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Investigating Speeding Behavior with Naturalistic Approaches

Although speeding is a significant contributor to traffic fatalities, attempts to address this problem have not led to a significant reduction in speed-related fatalities. There are a number of inherent shortcomings in using primarily self-report surveys and crash data to learn more about why drivers speed and in selecting countermeasures that will most effectively address speeding behaviors. An emerging empirical approach is to study the speeding choices that drivers make under everyday driving conditions by using naturalistic driving methods. Such an approach has the potential to yield highly informative data about speeding. These data, however, are complicated and prone to analytical confusion and uncertain interpretation if some key conceptual and methodological issues are not addressed. In this paper, an overview is provided of a naturalistic driving study that was intended to (a) identify the reasons why drivers speed; (b) model the relative roles of situational, demographic, and personality factors in predicting travel speeds; (c) classify speeders; and (d) identify interventions, countermeasures, and strategies for reducing speeding behaviors. The focus here is on discussing lessons learned associated with three methodological issues in particular (defining speeding, identifying a way to measure exposure, and obtaining accurate posted speeds) that were crucial to successfully analyzing the data that this study provided and for generating useful results and conclusions. It is believed that careful consideration of these issues will greatly benefit the traffic safety community, especially as future analyses of naturalistic driving data are considered.