Review on Machine Learning Techniques for Developing Pavement Performance Prediction Models

Road transportation has always been inherent in developing societies, impacting between 10–20% of Gross Domestic Product (GDP). It is responsible for personal mobility (access to services, goods, and leisure), that why world economies rely upon the efficient safe functioning facilities. maintenance vital since need increases as road infrastructure ages based on sustainability, meaning spending money now saves much more future. Furthermore, plays a significant role safety. However, pavement management challenging task because available budgets are limited. agencies set programming plans short term long select schedule rehabilitation operations. Pavement performance prediction models (PPPMs) crucial element systems (PMSs), providing distresses and, therefore, allowing active management. This work aims review modeling techniques commonly used development these models. The deterioration process stochastic by nature. requires complex deterministic or probabilistic techniques, which will be presented here, well advantages disadvantages each them. Finally, conclusions drawn, some guidelines support PPPMs proposed.