Modeling pavement performance using LTPP database for flexible pavements

Abstract

In many countries, incredible investments have been made in constructing roads that require conducting periodic evaluation and timely maintenance and rehabilitation (M&R) plan to keep the network operating under acceptable level of service. The timely M&R plan necessitates accurately predicting pavement performance, which is an essential element of road infrastructure asset management systems or Pavement Management Systems (PMS). Consequently, there is always a need to develop and to update performance prediction models embedded in PMS applications. This study focuses on developing distress prediction models for flexible pavements located in non-freeze climatic zone, which represent most of the Middle East countries using data extracted from the Long-Term Pavement Performance (LTPP) program. Six distress performance prediction models were developed in this study for both wet- and dry-non-freeze climatic zones, which are Fatigue (Alligator) cracking, longitudinal cracking, transverse cracking, raveling, bleeding, and rut depth models. These models can play an important role assisting decision makers in predicting pavement performance, identifying M&R needs, rational budget planning and resource allocation.