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Analysis of Effects of Pavement Marking Retroreflectivity on Traffic Crash Frequency on Highways in

Product Type

Journal Article

Author

Donnell, E.T., V. Karwa, and S. Sathyanarayanan

Date

Jan-09

Full citation

Donnell, E.T., V. Karwa, and S. Sathyanarayanan. Analysis of Effects of Pavement Marking Retroreflectivity on Traffic Crash Frequency on Highways in North Carolina. In Transportation Research Record: Journal of the Transportation Research Board, No. 2103, Transportation Research Board, National Research Council, Washington, D.C., 2009, pp. 50-60.

Abstract

Pavement markings provide useful visual and navigational guidance information to motorists. Current warrants for the application of pavement markings in the United States are based on traffic volume, traveled way width, and number of travel lanes. To be effective, pavement markings must be visible to drivers, particularly at night. The purpose of this paper is to perform an exploratory analysis to determine if a relationship between pavement marking retro-reflectivity and crash frequency exists. First, models of pavement marking retroreflectivity degradation were developed from selected highways in North Carolina using artificial neural networks. Monthly estimates of pavement marking retroreflectivity levels were then appended to roadway inventory and crash frequency data. Generalized estimating equations were used to estimate the monthly target crash frequency. The results indicate that the regression parameter estimates for yellow and white edgeline pavement markings were negative, but neither was statistically significant for the two-lane highway nighttime target crash frequency model. For multilane highways, all of the pavement marking retro-reflectivity parameter estimates were statistically significant. The white pavement marking retroreflectivity parameter estimates were negative, as expected. The yellow pavement marking retroreflectivity parameter estimate was positive.

Available From

Transportation Research Board

Link To Journal Article

Link not available.

Keywords

Accident rates
Edge lines
Generalized estimating equations
Multilane highways
Neural networks
Nighttime accidents
Retroreflectivity
Road markings
Traffic accidents
Two lane highways


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