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A study was designed to develop accident prediction models for estimating the safety performance of urban unsignalized intersections. The models were developed with the generalized linear modeling approach, which addresses and overcomes the shortcomings associated with conventional linear regression. The safety predictions obtained from the models were refined by the empirical Bayes approach to provide more accurate, site-specific safety estimates. The study made use of sample accident and traffic volume data corresponding to unsignalized (T-leg and four-leg) intersections located in urban areas of the Greater Vancouver Regional District and Vancouver Island, British Columbia. Four applications of the models are described: identifying accident-prone locations, developing critical accident frequency curves, ranking the identified accident-prone location, and evaluating before-and-after safety. These applications show the importance of using accident prediction models to reliably assess the safety of unsignalized intersections.

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The cornerstone of most safety management programs consists of a “collision-prone location” program, where significant collision history must exist and be identified before improvements are recommended. Often, these programs are solely dependent on collision records and thus program success is governed by the data quality. Unfortunately, in many jurisdictions in North America, the quantity and quality of collision data have been degrading for several years. This growing problem is jeopardizing the success and continuance of many road safety programs. To help mitigate this problem, it is believed that a subjective evaluation technique could be developed that does not rely on collision statistics and that could be used to identify and diagnose problematic areas. The development and application of a risk index used for road safety evaluation are described. The risk index is developed as a driver-based, subjective assessment of the potential road safety risks for in-service roadways. The objective of developing the safety risk index is to produce a technique to support road safety analysis that does not rely on deteriorating collision data. The road safety risk index was developed and tested to ensure consistency between observers in their subjective assessment of safety. In addition, the results from the risk index were compared with results from objectively derived road safety measures to evaluate the success of the road safety risk index. The comparison indicates that there is a statistically significant agreement between the results of the risk index and the objectively derived road safety measures.

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