Advancing knowledge of the safety implications of transportation engineering decisions with surrogate safety data and innovative statistical techniques

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The way transportation engineers study and evaluate road and traffic safety has remarkably advanced in recent years. Engineers can now employ a systematic and rigorous process to analyze safety at road sites that identifies opportunities to reduce crashes and implement potential safety countermeasures. This process mainly relies on a set of statistical techniques and models developed over several years of research. In turn, these models rely on crash observations as the main data source to quantify safety levels. However, the use of crash data in safety models has several limitations, mainly related to quality and availability issues. Moreover, the use of crash observations is reactive: a substantial number of crashes must occur before any action is taken. These limitations also inhibit application of new opportunities offered by methodological advancements in the field.