Article thumbnail

IRI performance models for recently constructed low and medium-traffic two lane roads of the province of Biscay

By Heriberto Pérez Acebo and Hernán Gonzalo-Orden


[EN] Reliable pavement prediction models are needed for pavement management systems (PMS), as they are a key component to forecast future conditions of the pavement and to prioritize maintenance, rehabilitation, and reconstruction strategies. The International Roughness Index (IRI) is the most used parameter worldwide for calibrating pavement roughness and measures reasonably the ride comfort perceived by occupants of passenger cars. The Regional Government of Biscay also collects this value on the road network under its control. These surveys are carried out regularly in the XXI century. Several IRI performance models have been proposed by different authors and administrations, varying greatly in their comprehensiveness, the ability to predict performance with accuracy and input data requirements. The aim of this paper is to develop a roughness performance model for Biscay’s roads, based on available IRI data, taking into account heavy traffic volume and the age of pavement. Local characteristics as climate conditions and average rainfall are not considered. IRI performance models have been suggested for regional two lane highways with low and medium heavy traffic constructed in the last 20 years in the province of Biscay, with no treatments during their life. They can be applied for flexible pavements, but no logical coherent results have been concluded for semi-rigid pavementsPérez Acebo, H.; Gonzalo-Orden, H. (2016). IRI performance models for recently constructed low and medium-traffic two lane roads of the province of Biscay. En XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València. 582-597.

Topics: IRI performance models, International roughness index, Pavement management, Pavement deterioration
Publisher: 'Universitat Politecnica de Valencia'
Year: 2016
DOI identifier: 10.4995/CIT2016.2015.4108
OAI identifier:
Provided by: RiuNet
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.