M. Ben-Akiva
A. Ceder
B. L-h. Cheng
C. M. Liss
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Intersection accidents represent a significant proportion of overall motor vehicle accidents. In Massachusetts, for example, intersection accidents amount to almost half of all reported accidents. With limited funds available for improving hazardous locations, state transportation departments require more accurate estimates of the actual effectiveness of intersection safety improvements. This study develops and implements an improved methodology for post-implementation evaluation of safety countermeasures at intersections. Accidents are random, rarely occurring events. For a given time period, this leads to random fluctuations in accident frequencies, which suggests that statistical analysis employing confidence intervals, rather than point estimates, is required. Two technical problems complicate this treatment of accident occurrence as a random variable, however, and preclude simple before-and-after analysis of unadjusted accident data utilizing hypothesis testing. The first problem is that identifying of hazardous locations is generally based on above-average accident frequency during the most recent period(s) for which data is available. A sample of locations receiving treatment, then, will be characterized by selectivity bias (also known as the "regression-to-the-mean" effect). This implies that accident frequencies at the selected (hazardous) intersections may be expected to decrease in future periods even without the safety countermeasures. The second problem arises from changes in external factors such as traffic volume, land use patterns, motor vehicle safety standards, etc., during the period of analysis, which may also affect traffic safety. Such changes may obscure or exaggerate the safety effects of the improvement project. The primary contribution of this study is the development of a "combined" approach which addresses these technical issues. Empirical Bayesian methodology is combined with regression techniques to derive a more accurate measure of the effect of safety treatments. This measure is based on a comparison of actual accident occurrence in the "after" period with expected occurrence, where this expectation is conditioned on the above-mentioned technical issues. An important consideration is the derivation of the variance of this measure, so that appropriate confidence intervals may be constructed. The approach is then applied to a sample of locations that underwent treatment by the Massachusetts Department of Public Works (MDPW). We compare our results to those which might be obtained using alternative methodologies that correct for neither or only one of the technical problems. We also illustrate how preliminary conclusions may be drawn regarding the effectiveness of broad categories of treatments, and how individual sites requiring further investigation may be identified. |
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