Asphalt Pavement

Asphalt pavement research focuses on improving the durability and lifespan of this critical infrastructure component. Current efforts leverage advanced machine learning techniques, such as convolutional neural networks (CNNs), transformers, and extreme learning machines (ELMs), to automate crack detection and predict pavement fatigue life based on factors like binder content and air voids. These data-driven approaches, often coupled with digital image correlation (DIC) for precise strain measurement, aim to optimize maintenance strategies and enhance the accuracy of pavement performance assessments. The resulting improvements in predictive modeling and automated analysis have significant implications for cost-effective infrastructure management and improved road safety.