Report Number

INLTAP-TR-1-2011

Sponsoring Organization

Indiana Local Technical Assistance Program

Performing Organization

Purdue University School of Civil Engineering

Date of this Version

5-2011

Keywords

sign retroreflectivity, retroreflectivity, sign degradation, sign retroreflectivity degradation, MUTCD retroreflectivity, sign asset management

Abstract

The 2009 Manual on Uniform Traffic Control Devices (MUTCD) requires that all agencies implement traffic sign management programs by January 8th, 2012. Most agencies are expected to adopt some type of systematic replacement policy based on life expectancy, augmented by visual inspection to identify signs with obvious damage. Several previous efforts have developed models based on average degradation of the retroreflective sheeting as the signs age. This paper develops a series of survival curves characterizing the percent of signs that pass the retroreflectivity standards for signs ranging from 0 to 20 years. The curves representing expected conformance with the retroreflectivity standards (survival curves) are believed of greater use than previous degradation curves of average retroreflectivity. A framework for using these survival curves for red, white, and yellow backgrounds, in conjunction with local cost information, is presented to aid in the development of sign management programs.

A model with sample calculations that reflect sign costs and life expectancy is developed to assist agencies in evaluating the implications of selecting alternative sheeting types and corresponding replacement schedules. The paper concludes that based on the longer warranty, the larger proportion of signs meeting the MUTCD minimums at their warranty age, and the annual cost over the warranty period that Type III High Intensity Beaded sheeting performs better than Type I Engineering Grade Beaded sheeting and has an overall lower annual cost to the agency. The paper documents the cost data and survival assumption so that local agencies can apply the model with local cost data to determine if our conclusions are consistent with local data.

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