Abstract
Improving road safety through proper pavement maintenance is one of the goals of pavement management. Many studies have found that pavement conditions significantly influence traffic safety. Although several studies have explored the relationship between pavement conditions and crash occurrence, the effect of poor pavement conditions on crash severity levels has not been investigated, especially by using a discrete model that can handle ordered data. This paper focuses on the development of the relationship between poor pavement conditions and crash severity levels using a series of Bayesian ordered logistic models for low/medium/high speed roads and single/multiple collision cases. The Bayesian ordered logistic regression models indicated that the poor pavement condition decreases the severity of single-vehicle collisions on low-speed roads whereas it increases their severity on high-speed roads. On the other hand, the poor pavement condition increases the severity of multiple-vehicle crashes on all roads. Findings of this study can assist transportation agencies at the federal, state, and local levels to select appropriate pavement maintenance and rehabilitation strategies to reduce traffic crash severity levels.
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Acknowledgments
The authors wish to thank the Florida Department of Transportation for providing data.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 141 • Issue 10 • October 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Oct 6, 2014
Accepted: Mar 19, 2015
Published online: May 22, 2015
Published in print: Oct 1, 2015
Discussion open until: Oct 22, 2015
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