Evaluation of TAZ safety using EB method and macro models

Safety consideration in transportation planning requires macro-level safety indicators. This is possible using various variables in macro-level safety studies. Using macro variables lead to easier and less costly accident predictive models. In this study, the predictive model of accident frequency obtained using macro level variables. Independent variables include, total length of the road network, the ratio of the length of roads network across functional classification (principal arterial, minor arterial, collector and local) to the length of all the roads, ratio of length of the bus lines to the total length of road network and density of the intersections in a Traffic Analysis Zone (TAZ). Accordingly, information of 16137 accidents in 96 TAZ collected. Then, the TAZs prioritized based on safety using Empirical Bayesian Method and TAZs with the highest Potential for Improvement (PI) found. Based on the results, increasing in length of the road network and the ratio of the length of road network across minor arterial in a TAZ, increases the chance of an accident occurred in that TAZ and a higher ratio of collector roads and local roads decreases the number of accidents in the TAZ. In this regard, the ratio of collector roads has the least and the ratio of local roads has the greatest impact.