@article{ref1,
title="Methods for Evaluation the Effectiveness of Road Intersection Treatments",
journal="Road and transport research",
year="2004",
author="bo-Qudais, SA and Al-Mughrabi, M",
volume="13",
number="1",
pages="39-50",
abstract="The main purpose of this study was to evaluate the effect that the analysis method has on the assessed impact of an intersection treatment. Accident data for three years before and three years after the treatment were collected for 20 improved intersections. The after/before accident ratio at each intersection was computed by four different methods: the direct comparison method, the Empirical Bayes approach, the regression technique, and the statistical accident-prediction models. The results of these four methods did not produce the same conclusions about the impact of the treatment on traffic safety. The direct comparison method of evaluation estimated accident ratios in the range of 0.28-4.93 compared with 0.33-3.48 for the Empirical Bayes approach, 0.20-6.05 for regression technique, and 0.08-2.64 for the statistical prediction models. Analysis of the results indicated that the impact of intersection treatment on traffic safety is significantly affected by the evaluation method used. At one of the evaluated intersections, the treatment was found to have a positive effect on traffic safety when the Empirical Bayes approach and the statistical prediction models were used. The same treatment appeared to have a negative impact when the two other evaluation methods were used. In general, the regression technique was found to underestimate the impact of intersection treatment. The Empirical Bayes approach considered the effect of factors that had been ignored in other methods, and is believed to provide a better estimate of the impact of an intersection treatment. In this study, statistical models were used to predict the accident rates after treatments. The values predicted by these models were compared to the actual accident rate. This comparison indicated that there is a difference between actual and predicted values. However, the statistical approach might be considered a good analysis tool, especially if evaluation of different highway alternatives is required.   <p>Language: en</p>",
language="en",
issn="1037-5783",
doi="",
url="http://dx.doi.org/"
}