| Summary: | Motor vehicle speed is a key risk factor contributing to many road accidents. Historical data shows that speed-related accidents account for a significant proportion of all the fatal and serious injury accidents and result in considerable social and economic costs. The objective of this thesis is to understand and quantify the relationship between traffic speed and accident frequency at urban signalized intersections in the city of Edmonton and Vancouver, Canada. This objective is achieved by developing accident prediction models which relate accident frequency to speed variables and other intersection characteristics. Road accident, traffic speed, traffic flow and road geometric data were obtained from the two cities for the purpose of the models development. The generalized linear modelling techniques are used to develop the accident prediction models assuming negative binomial error structure. A total of 15 models are developed relating accident frequency with five speed variables: average speed, mode speed, 85th percentile speed, speed standard deviation and percent of vehicles speeding. The results show that all five speed variables are positively correlated with accident frequency. A quantitative relationship between the change in the value of speed variables and the change in accident frequency is derived from the developed models.
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