EVALUATING THE IMPACTS OF FILEXIBLE TYPE HIGHWAY PAVEMENTS AND PROVIDING STOCHASTIC MODEL FOR ITS MAINTENANACE COST: (A CASE STUDY IN ADDIS-ADAMA EXPRESSWAY AND SODO-ARBA MINCH TRUNK ROAD)

Abstract

Evaluating the Impacts of Flexible Type Highway Pavements and Providing Stochastic Model for its Maintenance Cost Admassu Abera Arba Minch University, Ethiopia Advisor: Adane Abebe (PhD.) May, 2017 Transportation of goods and passengers are backbone of any economic growth. A widespread road network encourages and improves economic transactions and communication. Ethiopian Road Construction Corporation (ERCC) is specialized in the construction of roads and bridges. The company has built many roads and bridges across the country. Every road requires periodical maintenance to extend its functionality. ERCC maintained different roads around the country successfully. The lack of analytical methods for Life Cycle Cost Analysis (LCCA) creates many challenges of Ethiopian Road Authority (ERA) to comply with the rule. To address these critical issues, this study aims at developing a new methodology for quantifying the future maintenance cost to assist ERA in performing a LCCA. The major objectives of this research are twofold: 1) identify the critical factors that affect pavement performances; 2) develop a stochastic model that predicts future maintenance costs (MC) of flexible-type pavement in Addis-Adama expressway and Soda-Arba Minch trunk road. The study data were gathered from ERA, ERCC, and Highway Contractors containing relevant archival data and collection of interviews were taken. These data were grouped by critical performance-driven factor which was identified by K-means cluster analysis. Many factors were evaluated to identify the most critical factors that affect pavement maintenance need. With these data, a series of regression analyses were carried out to develop predictive models. Lastly, a validation study with PRESS statistics was conducted to evaluate reliability o f the model. The research results reveal that for Sodo-Arba Minch trunk road, five factors; annual precipitation, traffic volume, pavement age, sub-base strength, and grade of bitumen, were the most critical factors. Whereas Addis-Adama expressway, four factors; annual precipitation, pavement thickness, traffic volume, and grade of bitumen were the most critical factors. This research effort was the first of its kind undertaken in this subject. The MC stochastic model will assist ERA in carrying out a LCCA, with the reliable estimation of MC. This research provides the research community with the first view and systematic estimation method that ERA can use to determine long-term MC. It will reduce the agency’s expenses in the time and effort required for conducting a LCCA. Estimating long-term MC is a core component of the LCCA. Therefore, methods developed from this project have the great potential to improve the accuracy of LCCA.