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Assessment on Harmony of Pavement Condition Index Using ASTM, IRC and Regression Techniques

Abstract—Pavement maintenance and rehabilitation of low volume roads to the designated level of serviceability is a daunting task. Pavement condition index (PCI) is a promising numerical indexing technique for the structural integrity and performance of in-service pavements. Assessment of PCI is depending on theresults obtained from the visual inspection survey from which type, intensity and severity of various distresses are diagnosed. Indexes estimated from various techniques are appearing to be similar and tempting to adopt different indexes for comparing the performance of in-service pavement sections. The basic objective of this study is to carry out a comparative study on PCI values estimated from American Standard for Testing Materials (ASTM) and Indian Road Congress (IRC) techniques. To determine the level of agreement between these estimated indexes, a database composed of PCI values of 20.35 km of in-service distressed low volume PMGSY roads in India was used. The comparison of rating scales depicts that only 32% of pavement sections were representing similar rating whereas, for the other sections shown significant differences among seemingly similar pavement condition indexes. In addition, Index values estimated from the developed linear regression model for low volume roads shows good agreement with in-situ measured data. The developed model index values were also compared with ASTM and IRC techniques which show substantial increase in the similarity of ratings varying from 50% to 69% of pavement sections. Thus the developed model is simpler and robust in indicating the realistic performance of the pavement condition for defining optimum maintenance strategy. 

Index Terms— visual inspection survey, pavement condition index, low volume roads, linear regression
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