Transportation Infrastructure

Transportation infrastructure research focuses on optimizing the design, management, and maintenance of systems like roads, bridges, and traffic networks to enhance safety, efficiency, and sustainability. Current research emphasizes data-driven approaches, employing machine learning models such as deep learning (including convolutional neural networks like ResNet and U-Net, and transformer-based models), reinforcement learning, and graph neural networks to improve infrastructure monitoring (e.g., crack detection), predictive maintenance, and resource allocation. These advancements offer significant potential for reducing costs, improving safety, and enabling more resilient and efficient transportation systems.