Date of Award
3-11-2011
Document Type
Thesis
Degree Name
Master of Science in Engineering Management
Department
Department of Systems Engineering and Management
First Advisor
William E. Sitzabee, PhD.
Abstract
The results of this research effort were captured in two manuscripts drafted for publication in peer reviewed journals. The first manuscript validated a previously published model with an expanded data set, updated service life predictions for painted pavement markings using recently released pavement marking retroreflectivity minimums, and incorporated recent cost data to evaluate two alternative methods of compliance with the new retroreflectivity minimums for two-lane roads. The second manuscript developed a new performance prediction model for paint pavement markings that includes the impact of snow removal operations and then applied the model to four real-world roadways to determine if replacement is required. This research determined that each snow plow event degrades paint pavement markings by 3.22 mcd/m2/lux which is more than one month of service life. The work also showed that with no snow fall, an AADT of 4,000, and an RL, Initial of 220 mcd/m2/lux, paint pavement markings have a service life greater than five years on roads with posted speeds less than 55 mph. Finally, the research confirmed that AADT has a small but significant impact on the degradation of painted pavement markings. The results also indicated the developed for North Carolina might be useful in other states.
AFIT Designator
AFIT-GEM-ENV-11-M04
DTIC Accession Number
ADA540463
Recommended Citation
Mull, Dale M., "Paint Pavement Marking Performance Prediction Model That Includes the Impacts of Snow Removal Operations" (2011). Theses and Dissertations. 1538.
https://scholar.afit.edu/etd/1538