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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 50-60 |
| Number of pages | 11 |
| Journal | Transportation Research Record |
| Issue number | 2103 |
| DOIs | |
| State | Published - Dec 1 2009 |
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All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Mechanical Engineering
Cite this
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Analysis of effects of pavement marking retroreflectivity on traffic crash frequency on highways in North Carolina. / Donnell, Eric Todd; Karwa, Vishesh; Sathyanarayanan, Sudhakar.
In: Transportation Research Record, No. 2103, 01.12.2009, p. 50-60.Research output: Contribution to journal › Article
TY - JOUR
T1 - Analysis of effects of pavement marking retroreflectivity on traffic crash frequency on highways in North Carolina
AU - Donnell, Eric Todd
AU - Karwa, Vishesh
AU - Sathyanarayanan, Sudhakar
PY - 2009/12/1
Y1 - 2009/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=71549140621&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71549140621&partnerID=8YFLogxK
U2 - 10.3141/2103-07
DO - 10.3141/2103-07
M3 - Article
AN - SCOPUS:71549140621
SP - 50
EP - 60
JO - Transportation Research Record
JF - Transportation Research Record
SN - 0361-1981
IS - 2103
ER -