Not So Fast! An Investigation of Real-World Speeding Behaviors

Although speeding is a major contributor to traffic fatalities, attempts to address this problem have not led to significant reductions in speed-related crashes. In this paper, the authors describe an investigation of speeding behaviors that was intended to: (1) identify which drivers speed, (2) model the relative roles of situational, demographic, and personality factors in predicting travel speeds, and (3) classify drivers based on their speeding patterns. The speeding behaviors of 88 drivers were recorded over the course of approximately four weeks of naturalistic driving in Seattle, Washington. Data collected included 1-Hz recordings of vehicle position and speed using a GPS receiver, and responses to survey questions. Regression models were developed to identify predictors of 1) “any” speeding and 2) amount of speeding. Significant predictors included demographic variables such as age and gender, situational factors such as time-of-day and day-of-week, and key personality factors such as attitudes towards reckless driving.