Road Flooding

Road flooding, a significant problem in low-lying coastal areas and urban centers, is increasingly studied to improve prediction and mitigation strategies. Current research focuses on developing faster, more accurate predictive models using machine learning techniques, such as deep learning architectures (LSTMs, GRUs) and random forests, to overcome the limitations of computationally expensive physics-based simulations. These efforts aim to provide near real-time flood detection, potentially leveraging satellite imagery and onboard computing for dynamic map updates, ultimately enhancing transportation safety and reducing property damage.