Updates to Research on Recommended Minimum Levels for Pavement Marking Retroreflectivity to Meet Driver Night Visibility Needs

Updates to Research on Recommended Minimum Levels for Pavement Marking Retroreflectivity to Meet Driver Night Visibility Needs
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Total Pages : 54
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ISBN-10 : UOM:39015072077905
ISBN-13 :
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Book Synopsis Updates to Research on Recommended Minimum Levels for Pavement Marking Retroreflectivity to Meet Driver Night Visibility Needs by :

Download or read book Updates to Research on Recommended Minimum Levels for Pavement Marking Retroreflectivity to Meet Driver Night Visibility Needs written by and published by . This book was released on 2007 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, the Pavement Marking Visibility Module of the Tarvip model was validated by comparing field data from various studies to prediction results under similar conditions from Tarvip. Next, a comprehensive survey on the factors that affect pavement marking visibility and minimum RL levels was performed, with key factors identified, including pavement marking configuration, pavement surface type, vehicle speed, vehicle type, and presence of RRPMs. From these key factors, a methodology of using Tarvip to do a sensitivity analysis on factors modeled in it was developed. The plan was executed, and resulting RL values under typical conditions on United States roadways formed the basis of new recommendations. Finally, limitations of the recommendations were analyzed, and a plan for future research was presented. This study was aimed at completing the research to develop and scrutinize minimum levels for pavement marking retroreflectivity to meet nighttime driving needs. A previous study carried out in the 1990s was based on the CARVE model developed at Ohio University and resulted in a table of minimum levels of pavement marking retroreflectiviy values. Since then, a newer, more powerful analytical tool, Tarvip, which was developed at the Operator Performance Lab of the University of Iowa, overcomes a lot of limitations of the CARVE model and uses updated data that reflect the current states of vehicles and roadways in the United States.


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