Study Details

Study Title: Estimation of the Safety Effect of Pavement Condition on Rural Two-Lane Highways

Authors: Zeng et al.

Publication Date:JAN, 2014

Abstract: The condition of the pavement surface can have an important effect on highway safety. For example, skidding crashes are often related to pavement rutting, polishing, bleeding, and dirty pavements. When transportation agencies develop paving schedules for their roadways, they often make decisions based on asset management condition targets but do not explicitly account for the role of pavement condition in roadway safety. The Virginia Department of Transportation (VDOT) began automated pavement condition data collection using digital images and an automated crack detection methodology in 2007. This development enabled the DOT to track historical pavement condition information, and thus facilitates research regarding pavement condition impacts on safety. Information on how pavement condition influences safety could be used to inform paving decisions and better set priorities for maintenance. The objective of this study is to quantitatively evaluate the safety effectiveness of good pavement conditions versus deficient pavement conditions on rural two-lane undivided highways in Virginia. Using the Empirical Bayes method, it was found that good pavements are able to reduce fatal and injury (FI) crashes by 26 percent over deficient pavements, but do not have a statistically significant impact on overall crash frequency. Further analysis indicated that the safety benefit of pavement condition improvement on FI crashes does not statistically significantly change as the lane or shoulder width increases. In conclusion, improving pavement condition from deficient to good can offer a significant safety benefit in terms of reducing crash severity.

Study Citation: Zeng, H., M.D.Fontaine.,and B.L.Smith.,Estimation of the Safety Effect of Pavement Condition on Rural Two-Lane Highways.Presented at the 93rd Annual Meeting of the Transportation Research Board, Washington, D.C., (2014).


CMFs Associated With This Study

Category: Roadway

Countermeasure: Change street surface condition from poor to good

CMF CRF(%)QualityCrash TypeCrash SeverityRoadway TypeArea Type
1.03-34 StarsAllAllNot specifiedRural
0.74265 StarsAllK,A,B,CNot specifiedRural
1.03-34 StarsAllAllNot specifiedRural
0.74264 StarsAllK,A,B,CNot specifiedRural
0.9824 StarsAllAllNot specifiedRural
0.74264 StarsAllK,A,B,CNot specifiedRural
1.04-44 StarsAllAllNot specifiedRural
0.77234 StarsAllK,A,B,CNot specifiedRural
1.26-264 StarsAllAllNot specifiedRural
0.78224 StarsAllK,A,B,CNot specifiedRural