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Limitations of historical crash data and the advantages of surrogate measures of safety have already been stressed by various authors. To describe nearness-to-collision, mostly time-based indicators are applied, and there is a consensus among researchers that speed-related indicators are needed to account for the severity dimension. There have been attempts to fit bivariate Extreme Value models to predict the number of crashes, however modeling crash frequency together with severity has received much less attention.

The aim of this paper is to apply Extreme Value models to various pairs of temporal and speed-related indicators in order to investigate the dependence structure between them as well as to construct probability based risk levels and examine them in relation to severity levels. Bivariate threshold excess models were fitted to a dataset of left-turning and straight moving vehicle interactions recorded …