Application of propensity scores and potential outcomes to estimate effectiveness of traffic safety countermeasures: Exploratory analysis using intersection lighting data

Abstract

More than 5.5 million police-reported traffic crashes occurred in the United States in 2009, resulting in 33,808 fatalities and more than 2.2 million injuries. Significant funds are expended annually by federal, state, and local transportation agencies in an effort to reduce traffic crashes. Effective safety management involves selecting highway and street locations with potential for safety improvements; correctly diagnosing safety problems; identifying appropriate countermeasures; prioritizing countermeasure implementation at selected sites; and, evaluating the effectiveness of implemented countermeasures. Accurate estimation of countermeasure effectiveness is a critical component of the safety management process. In this study, a statistical modeling framework, based on propensity scores and potential outcomes, is described to estimate countermeasure effectiveness from non-randomized observational data. Average treatment effects are estimated using semi-parametric estimation methods. To demonstrate the framework, the average treatment effect of fixed roadway lighting at intersections in Minnesota is estimated. The results indicate that fixed roadway lighting reduces expected nighttime crashes by approximately 6%, which compares favorably to other, recent lighting-safety research findings.