Stopping sight distance is one of the most important criteria for highway design. However, the literature has shown limited quantitative evidence as to the nature of this relationship. As such, the results from this study provide an important contribution to the research literature.
The study demonstrated the value of high-fidelity LiDAR data, which allowed for a large-scale investigation of the relationship between crash risk and available sight distance on a diverse set of roadway facilities. Negative binomial regression models were estimated separately for freeway and non-freeway facilities while controlling for the effects of other important variables.
The results show similar relationships for both facility types, with crashes persistently increasing as the amount of available sight distance is reduced. The safety performance functions estimated as a part of this study provide an empirical basis for estimating the potential impacts of design scenarios where it may be impractical to satisfy the minimum recommendation distances from the AASHTO Green Book. The results can also help to inform agency practices and the development of projects to mitigate the sources of the sight distance limitations.