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Explaining Property Damage from Crashes at Signalized Intersections

Abstract
 In this article, we estimate a Tobit model of property damage costs of crashes that occur at signalized intersections with data from one US city – Greensboro, North Carolina. The model includes data on technological variables, types of crash, types of vehicle, traffic and intersection characteristics, and driver condition at the time of crash. The results indicate that driver condition and type of vehicle contribute more to higher property damage costs than any other variable. Those variables that have negative effects on these costs are being a female driver, traffic volume, commercial and institutional land uses. From the results, we conclude that traffic countermeasures such as reducing the amber signal phase time and posting lower speed limits on urban roads could reduce property damage costs.