Iowa's Experience with Road Diet Measures: Use of Bayesian Approach to Assess Impacts on Crash Frequencies and Crash Rates
Abstract
A before-and-after study implemented from a Bayesian perspective to assess crash history reduction due to road diets in Iowa was conducted by the Iowa State University Department of Statistics in cooperation with the Iowa Department of Transportation's Office of Traffic and Safety. The study used both monthly crash data and estimated volumes obtained from TAS for 30 sites—15 treatment and 15 comparison—over 23 years (1982 to 2004). The sites had volumes ranging from 2,030 to 15,350 during this period and were largely located in smaller urbanized areas. The research objective was to assess whether road diets appear to result in crash reductions on Iowa roads. Crash data were analyzed at each site before and after the conversions were completed. Given the random, rare nature of crash events, a hierarchical Poisson model was fitted, such that log mean rate was expressed as a piecewise linear function of time period, seasonal effects, and a random effect corresponding to each site. Monthly traffic volumes were incorporated as exposures. Estimation of model parameters was conducted within a Bayesian framework. Results indicate a 25.2% reduction in crash frequency per mile and an 18.8% reduction in crash rate. This differs from a previously publicized study that reported a 6% reduction in crash frequency per mile and an insignificant indication for crash rate effects. The results from the Iowa study fit practitioner experience and agree with another Iowa study that used a simple before-and-after approach on the same sites.
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