Beschreibung:
<jats:title>Abstract</jats:title><jats:p>Although it is well documented that optimized barrier dimensions would yield a benefit by enhancement of traffic safety, not many studies have been conducted quantifying how much money could be saved by enhancing barriers to their optimum heights, especially with the help of machine learning technique. Equivalent property damage only (EPDO) was considered as a response in the modeling to account for both aspects of crash frequency and severity. A hurdle model was developed to explore the impact of enhancing the geometric characteristics of barriers while accounting for zero inflation. The two components of the model, logistic regression and truncated negative binomial, could account for both abundance of zeroe<jats:italic>s</jats:italic> and the skewed nature of non‐zero EPDO. The methodological approach provides a new understanding of the economic/monetary evaluation of an asset enhancement in the state with the help of machine learning technique. Our methodological approach provides the policy makers about the monetary benefit that they could expect by optimization of barriers heights. The analysis summarized in this paper will not only help Wyoming, but it provides other states with the justification of safety enhancement to their road barriers or assets.</jats:p>