Development of Roughness Prediction Models for Laos National Road Network

The International Roughness Index (IRI) has been accepted globally as an essential indicator for assessing pavement condition. Laos Road Management System (RMS) utilizes a default Highway Development and (HDM-4) IRI prediction model. However, developed values have shown the need to calibrate Data records are not fully available yet, making it difficult local conditions. This paper aims develop model National Network (NRN) based on RMS database. Multiple Linear Regression (MLR) analysis technique was applied two new models Double Bituminous Surface Treatment (DBST) Asphalt Concrete (AC) sections. final database consisted of 83 sections with 269 observations over 1850 km length DBST NRN 29 122 718 AC NRN. proposed predict function age Cumulative Equivalent Single-Axle Load (CESAL). model’s parameter confirmed their significance, R2 were 0.89 0.84 models, respectively. It can be concluded that serve useful tool engineers maintaining paved