IRI data used in optimum pavement rehabilitation models for developing countries: Palestine as a case study

Abstract

This paper investigates the potential use of the International Roughness Index (IRI) in generating optimal rehabilitation plans at the network-level. The IRI data used in the study was obtained using the portable vehicle-mounted IRIMETER-2 profilometer, which is a product of Englo LLC, Tallinn, Estonia. An optimum rehabilitation model is proposed to minimize the average IRI value at the network-level subject to variable and budget constraints. The model mainly focuses on using major rehabilitation strategies that can produce a major improvement in pavement condition. An alternate maximization model that can use other pavement condition indicators, such as the present serviceability index (PSI) and pavement condition index (PCI), is also presented. The PSI and PCI can be estimated from the IRI using correlation models. The proposed optimum models are linear in form and can easily be solved using the proposed cost-effectiveness ratio. The sample results presented for a 27.1-km suburban highway indicate the reliability of using the IRI data to generate optimal rehabilitation plans. A statistical uncertainty analysis of IRI measurements produced a mild impact on optimal solutions derived using ten independent IRI tests and 99% confidence level. The uncertainty analysis has also indicated that the use of a single IRI test provides results that are statistically indifferent from those obtained using ten IRI tests.