Conventional Datasets (1)
Large-Scale Datasets (3)
LargeST (X. Liu, National University of Singapore, Singapore)
X. Liu, Y. Xia, Y. Liang, J. Hu, Y. Wang, L. Bai, C. Huang, Z. Liu, B. Hooi, R. Zimmerman, "LargeST: A Benchmark Dataset For Large-Scale Traffic Forecasting", Conference on Neural Information Processing Systems, NeurIPS 2023, 2023.
XXLTraffic ()
D. Yin, H. Xue, A. Prabowo, S. Aon F Salim, "XXLTraffic: Expanding and Extremely Long Traffic Dataset for Ultra-Dynamic Forecasting Challenges, Preprint, 2024.
TraffiDent (X. Gou, KAUST, Kingdom of Saudi Arabia)
X. Gou, “Explainability and Efficiency in Spatio-Temporal Models: Applications to Traffic Forecasting”, PhD Thesis, King Abdullah University of Science and Technology Thuwal, Kingdom of Saudi Arabia, 2025.
Benchmark Datasets (2)
STG4Traffic ()
X. Luo, C. Zhu, D. Zhang, Q. Li, “STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction”, Preprint, 2024
STGym (C. Shen)
C. Shen, J. Jiang, H. Hsieh, “STGym: A Modular Benchmark for Spatio-Temporal Networks with a Survey and Case Study on Traffic Forecasting”, IEEE Transactions on Big Data, February 2026.