Overview

Traffic forecasting estimates how movement and demand will change across road networks, transit systems, airspace, and communications networks, supporting planning, routing, and resource allocation. Common approaches combine graph neural networks, temporal convolutions, attention-based Transformers, and newer state-space models; other work uses signal decomposition, physical or agent-based simulation, and contextual data such as incidents, weather, or mobility patterns. Researchers are extending these models with probabilistic predictions, foundation models, and online, continual, or federated adaptation to handle uncertainty, privacy, and changing conditions. A central challenge is making forecasts accurate and efficient while ensuring they transfer across places, sensor configurations, and traffic regimes—and that improvements in forecast metrics actually help downstream decisions.

Latest papers

CardsList

87 papers8 papers in the last four weeks, down 20% on the four weeks before. 0.0% of all new papers.

  1. TSNN: A Non-parametric and Interpretable Framework for Traffic Time Series Forecasting

    May 9, 2026Bowen Liu, Haijian Lai, Chan-Tong Lam +4Time Series ForecastingTraffic Forecasting

  2. Efficient Prompt Learning for Traffic Forecasting

    May 8, 2026Qianru Zhang, Xinyi Gao, Alexander Zhou +3OOD GeneralizationPrompt Tuning

  3. Generalising Travel Time Prediction To Varying Route Choices In Urban Networks

    May 7, 2026Łukasz Gorczyca, Kacper Drozd, Michał Bujak +1Intelligent Transportation SystemsTraffic Flow Estimation

  4. Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting

    May 5, 2026Xiao Zhang, Yafei Li, Ruixiang Wang +3Spatiotemporal ForecastingNeural ODEs

  5. CNN-based Multi-In-Multi-Out Model for Efficient Spatiotemporal Prediction

    May 2, 2026Hyeonseok JinEfficient Neural Network InferencePrecipitation Forecasting

  6. Forecasting Individual NetFlows using a Predictive Masked Graph Autoencoder

    Apr 22, 2026Georgios Anyfantis, Pere Barlet-RosTemporal GNNsTraffic Forecasting

  7. GAMMA-Net: Adaptive Long-Horizon Traffic Spatio-Temporal Forecasting Model based on Interleaved Graph Attention and Multi-Axis Mamba

    Apr 18, 2026Dongyi He, Yuanquan Gao, Bin Jiang +1Long-Term Time Series ForecastingIntelligent Transportation Systems

  8. FedLLM: A Privacy-Preserving Federated Large Language Model for Explainable Traffic Flow Prediction

    Apr 17, 2026Seerat Kaur, Sukhjit Singh Sehra, Dariush EbrahimiPrivacy-Preserving Language ModelsTraffic Flow Estimation

  9. Unveiling Stochasticity: Universal Multi-modal Probabilistic Modeling for Traffic Forecasting

    Apr 17, 2026Weijiang Xiong, Robert Fonod, Nikolas GeroliminisTraffic ForecastingProbabilistic Time Series Forecasting

  10. FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction

    Apr 15, 2026Xinjin Li, Jinghan Cao, Mengyue Wang +5Spatiotemporal ForecastingTraffic Forecasting

  11. Interpretable long-term traffic modelling on national road networks using theory-informed deep learning

    Mar 27, 2026Yue Li, Shujuan Chen, Akihiro Shimoda +1Traffic ForecastingTraffic Flow Estimation

  12. Ultra-fast Traffic Nowcasting and Control via Differentiable Agent-based Simulation

    Mar 26, 2026Fumiyasu Makinoshima, Yuya Yamaguchi, Eigo Segawa +2Intelligent Transportation SystemsAgent-Based Modeling

  13. Long-Horizon Traffic Forecasting via Incident-Aware Conformal Spatio-Temporal Transformers

    Mar 17, 2026Mayur Patil, Qadeer Ahmed, Shawn Midlam-Mohler +4Spatiotemporal TransformersTraffic Forecasting

  14. Spatial PDE-aware Selective State-space with Nested Memory for Mobile Traffic Grid Forecasting

    Mar 12, 2026Zineddine Bettouche, Khalid Ali, Andreas Fischer +1Spatiotemporal ForecastingTraffic Forecasting

  15. VisiFold: Long-Term Traffic Forecasting via Temporal Folding Graph and Node Visibility

    Mar 12, 2026Zhiwei Zhang, Xinyi Du, Weihao Wang +2Traffic ForecastingLong-Term Time Series Forecasting

  16. Deep Learning Network-Temporal Models For Traffic Prediction

    Mar 12, 2026Yufeng Xin, Ethan FanMultivariate Time Series ForecastingLLM-Based Time Series Forecasting

  17. AI-Enhanced Spatial Cellular Traffic Demand Prediction with Contextual Clustering and Error Correction for 5G/6G Planning

    Mar 11, 2026Mohamad Alkadamani, Colin Brown, Halim YanikomerogluTraffic ForecastingWireless Communications

  18. DWAFM: Dynamic Weighted Graph Structure Embedding Integrated with Attention and Frequency-Domain MLPs for Traffic Forecasting

    Mar 1, 2026Sen Shi, Zhichao Zhang, Yangfan HeTraffic ForecastingSpatiotemporal Forecasting

  19. Learning from Yesterday's Error: An Efficient Online Learning Method for Traffic Demand Prediction

    Feb 25, 2026Xiannan Huang, Quan Yuan, Chao YangTraffic ForecastingTime Series Forecasting

  20. Positional-aware Spatio-Temporal Network for Large-Scale Traffic Prediction

    Feb 25, 2026Runfei ChenTraffic ForecastingSpatiotemporal GNNs

  21. MMCAformer: Macro-Micro Cross-Attention Transformer for Traffic Speed Prediction with Microscopic Connected Vehicle Driving Behavior

    Feb 17, 2026Lei Han, Mohamed Abdel-Aty, Younggun Kim +2Traffic ForecastingSpatiotemporal Forecasting

  22. HieraMix: A Hierarchical MLP-Mixer for Large-Scale Traffic Forecasting

    Nov 26, 2025Yongyao Wang, Xie Yu, Jingyuan Wang +2Intelligent Transportation SystemsSpatiotemporal Forecasting

  23. Efficient Traffic State Prediction With Dynamic Joint Spatio-Temporal Relation Inference

    Apr 10, 2025Zhifeng Hao, Kai Hu, Juncai Zhang +2Temporal Convolutional NetworksDynamic Graph Learning

  24. Spatio-Temporal Partial Sensing Forecast for Long-term Traffic

    Aug 2, 2024Zibo Liu, Zhe Jiang, Zelin Xu +5Long-Term Time Series ForecastingSpatiotemporal Forecasting