Regional implementation of the mechanistic empirical pavement design and analysis approach: Egyptian case study

Abstract

The Mechanistic-Empirical (ME) pavement design approaches have many advantages including; considering a wide range of traffic loadings along with a diversity of climatic conditions. This is in addition to the ability to comprehensively and thoroughly characterizing the pavement materials, which consequently led to the enhanced capability of predicting pavement performance. However, the implementation of the ME procedures has many challenges including the huge amount of traffic and climatic data needed, the needed advanced characterization of the pavement materials, and the need for the calibration and validation to the local conditions. Accordingly, an increased required time to develop and evaluate the design is warranted. Furthermore, the lack of the experience with the ME pavement design approaches is considered an additional challenge. In order to encourage the ME design procedures implementation in a scarcity of data and lack of experience regions, this research proposes a ME regional implementation model. This model was developed then implemented in Egypt as a case study representing the developing countries of scarcity of both data and experience of the ME approaches. First, libraries of the local material/traffic inputs were created. Second, the performance of typical designed pavement sections was predicted using the ME approach in terms of the most regional prevailing performance indicators; rutting, fatigue cracking, and thermal cracking. The Machine Learning (ML) technique was then used to develop correlation models. Third, the developed models were presented in the form of ME pavement design/analysis tool. Three performance ML based-models were developed with good R2 (coefficient of determination) of 0.789, 0.755, and 0.959 for fatigue cracking, thermal cracking, and rutting, respectively. Finally, the developed performance models were implemented in the form of a user-friendly design/analysis tool ready for use as a mechanistic empirical tool developed based on the regional conditions. The Egyptian case study proved a good validation and verification of the developed model.