A simplified Empirical Bayesian method to safety evaluation of traffic calming treatment for urban road systems
by Fang Clara Fang, Joseph H. Rimiller, Najib O. Habesch
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 6, No. 3/4, 2009

Abstract: The City of Hartford in Connecticut developed and implemented a comprehensive citywide traffic calming master plan in 2005–2006; the first of its kind in the USA. 'Before' and 'after' crash data for many of the traffic calming devices were measured to study their impact on vehicular safety and so that the future deployments may be validated. This article presents the main findings in the estimation of safety effectiveness of deploying road diets, one of the treatments identified in the plan. Five of Hartford's arterial roadways that were placed on road diets were compared to similar comparison roads that had not received any treatments. A simplified Empirical Bayesian (EB) method was developed to predict the 'expected' crash rate of study sites during the 'after' period without implementation. The method combined the mean and variance of the crash counts at comparison sites. The observed 'before' crash rates, the crash rate expected without improvement, and the observed 'after' crash rate were compared and discussed. Both the simple before-and-after analysis and the EB method study exhibited consistent results. All implemented streets revealed some safety benefits of crash reduction; the higher the crash rate and traffic demand were, the larger reduction resulted. The EB method results had also shown that there was no bias associated with regression-to-mean.

Online publication date: Mon, 30-Mar-2009

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