A model to compute service life of rural roads using present pavement condition and pavement age
Keywords:
Pavement distress, international roughness index, linear regression analysis pavement maintenance, remaining service lifeAbstract
This paper presents a scientific approach to forecast Remaining Service Life (RSL) of low volume rural roads. A case study of twenty six roads constructed under Pradhan Mantry Gram Sadak Yojna in Hamirpur district of Himachal Pradesh state in India has been selected to implement the approach. Pavement age and Pavement Condition Index (PCI) are the key factors considered to predict RSL of each road. PCI is calculated from the pavement surface distress and roughness data. Bump Integrator is used to calculate the pavement condition based on surface roughness (PCIR)and seven major types of pavement surface distresses namely: alligator cracking, edge cracks, pothole, patching, ravelling, rutting and longitudinal cracks are used in calculating pavement condition index based on distresses (PCID). PCIO is defined as the overall PCI computed from assigning 40% weight to the PCID and 60% to the PCIR. A correlation equation is developed between the pavement age and the PCIO using linear regression analysis: y = -25.62ln(x) + 116.16. However, this equation is valid in conditions similar to those in the study area. A correlation coefficient (r) of 0.8899 was obtained which shows that the curve is a good fit. The developed relationship can help plan repair and maintenance works based on RSL of each road.
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