Traffic Data

Traffic data analysis focuses on understanding and predicting traffic patterns for improved transportation management and urban planning. Current research emphasizes developing sophisticated models, including graph neural networks, transformers, and large language models, to analyze diverse data sources (e.g., GPS trajectories, sensor readings, textual information) and address challenges like data sparsity, missing values, and the need for real-time predictions. These advancements enable more accurate traffic forecasting, incident detection, and resource optimization, impacting areas such as autonomous driving, traffic signal control, and urban infrastructure planning.