International Roughness Index (IRI) prediction models for freeways

Abstract

In Pavement Management Systems (PMS), pavement performance models, or pavement deterioration (or evolution) models are regarded as a key element because they are able to forecast the future condition of the pavement based on available data. Hence, once pavement performance is predicted for next years, the optimal moment and treatment can be planned to be conducted, maximizing the existing limited budget for road maintenance and rehabilitation (M&R). There is a wide variety of characteristics that are assessed in a pavement, and additionally, there are various indices to measure those characteristics too. However, it can be said that there is a property, pavement roughness, measured by the International Roughness Index (IRI), which is the most widely employed index worldwide. Most of the road administrations around the world measure the roughness by means of IRI. The Regional Government of Gipuzkoa (RGA) manages the entire road network in the province of Gipuzkoa, except from the municipal roads. Using the IRI data, traffic and pavement structure information of the A-636 freeway of Gipuzkoa, the aim of this paper is to develop some IRI prediction models for freeways in Gipuzkoa, adjusted to the climate characteristics of the province. Results showed that accurate models can be created if adequate variables are included, such as the pavement type, achieving a determination coefficient of R2 = 0.827. This fact underlines the importance of recording as much information as possible, especially pavement structural section, in the PMS.