Abstract
Identifying crash “black-spots”, “hot-spots” or “high-risk” locations is one of the most important and prevalent concerns in traffic safety and various methods have been devised and presented for solving this issue until now. In this paper, a new method based on the reliability analysis is presented to identify black-spots. Reliability analysis has an ordered framework to consider the probabilistic nature of engineering problems, so crashes with their probabilistic na -ture can be applied. In this study, the application of this new method was compared with the commonly implemented Frequency and Empirical Bayesian methods using simulated data. The results indicated that the traditional methods can lead to an inconsistent prediction due to their inconsider -ation of the variance of the number of crashes in each site and their dependence on the mean of the data.
Highlights
Identifying black-spots, ranking and determining the potential safety improvement for each location among a set of sites are the main purposes of studies in traffic safety
The purpose of this paper is to present a probabilistic method for black spots identification
In order to compare the performance of black-spots identification methods, these researchers used simulated data instead of empirical data
Summary
Identifying black-spots, ranking and determining the potential safety improvement for each location among a set of sites are the main purposes of studies in traffic safety. The simplest comparison is to rank the sites on the basis of the mean number of crashes occurring on each location. A comparison of each site with a reference site is made in order to identify the blackspots. The probabilistic methods should be used to compare the crash counts occurring on each site with those of a reference site. In this study, the reliability analysis method was proposed to identify the blackspots. This method has many remarkable advantages because the probabilistic nature of crash occurrence in each location is taken into account
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