Abstract
This study sought to create a simulation model to provide the North Carolina Department of Transportation (NCDOT) with recommendations to improve its sign inspection and replacement procedures. This research focuses on two key factors built into the model: (a) the rate at which signs are damaged beyond usefulness based on natural or man-made causes and (b) the accuracy rate of visual sign inspections based on retroreflectivity. The research team conducted nighttime rides with sign inspectors in 5 of 14 NCDOT divisions. During subsequent daytime rides, the team measured sign retroreflectivity to allow estimation of sign deterioration and inspector accuracy rates. Data were collected for white, yellow, red, and green signs and for sheeting Types I and III. About 2.3% of inspected signs (per year) were damaged to the point of needing replacement, and inspectors did not reject a large percentage of signs that had retroreflectivity values below the proposed minimum Federal Highway Administration standard.
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