Traffic Prediction

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

33 leaderboard tables shown for this task, 33 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 33 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

20 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 164 papers with code (375 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Sequence to Sequence Learning with Neural Networks
  10 Sep 2014 74 repositories listed Syntology ran 11 of 25 samples · 14 unverified · 9 pointer-only (licence)
  Our method uses a multilayered Long Short-Term Memory (LSTM) to map the input sequence to a vector of a fixed dimensionality, and then another deep LSTM to decode the target sequence from the vector.
• Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
  6 Jul 2017 19 repositories listed Syntology ran 17 of 35 samples · 18 unverified · 15 pointer-only (licence)
  Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain.
• T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction
  12 Nov 2018 10 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  However, traffic forecasting has always been considered an open scientific issue, owing to the constraints of urban road network topological structure and the law of dynamic change with time, namely, spatial dependence…
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling
  31 May 2019 9 repositories listed Syntology ran 5 of 7 samples · 2 unverified
  Spatial-temporal graph modeling is an important task to analyze the spatial relations and temporal trends of components in a system.
• Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
  14 Sep 2017 7 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Timely accurate traffic forecast is crucial for urban traffic control and guidance.
• SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction
  17 Jun 2021 6 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  One unique property of time series is that the temporal relations are largely preserved after downsampling into two sub-sequences.
• GMAN: A Graph Multi-Attention Network for Traffic Prediction
  11 Nov 2019 6 repositories listed Syntology ran 0 of 10 samples · 10 unverified
  Between the encoder and the decoder, a transform attention layer is applied to convert the encoded traffic features to generate the sequence representations of future time steps as the input of the decoder.
• Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction
  3 Mar 2018 5 repositories listed
  Although both factors have been considered in modeling, existing works make strong assumptions about spatial dependence and temporal dynamics, i.
• Incrementally Improving Graph WaveNet Performance on Traffic Prediction
  11 Dec 2019 4 repositories listed
  We present a series of modifications which improve upon Graph WaveNet's previously state-of-the-art performance on the METR-LA traffic prediction task.
• Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective
  13 Dec 2024 3 repositories listed Syntology ran 3 of 6 samples · 3 unverified
  From the spatial data management perspective, we present a novel Transformer framework called PatchSTG to efficiently and dynamically model spatial dependencies for large-scale traffic forecasting with interpretability…
• Spatial-Temporal Large Language Model for Traffic Prediction
  18 Jan 2024 3 repositories listed
  In the ST-LLM, we define timesteps at each location as tokens and design a spatial-temporal embedding to learn the spatial location and global temporal patterns of these tokens.
• DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction
  20 Aug 2021 3 repositories listed Syntology ran 4 of 5 samples · 1 unverified
  Nowadays, with the rapid development of IoT (Internet of Things) and CPS (Cyber-Physical Systems) technologies, big spatiotemporal data are being generated from mobile phones, car navigation systems, and traffic sensors.
• Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
  13 Mar 2021 3 repositories listed Syntology ran 2 of 13 samples · 11 unverified · 2 pointer-only (licence)
  In this paper, we propose Spectral Temporal Graph Neural Network (StemGNN) to further improve the accuracy of multivariate time-series forecasting.
• Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
  6 Jul 2020 3 repositories listed Syntology ran 5 of 7 samples · 2 unverified · 1 pointer-only (licence)
  We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.
• Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
  24 May 2020 3 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 1 pointer-only (licence)
  Modeling multivariate time series has long been a subject that has attracted researchers from a diverse range of fields including economics, finance, and traffic.
• BjTT: A Large-scale Multimodal Dataset for Traffic Prediction
  8 Mar 2024 2 repositories listed
  The key challenge of the TTG task is how to associate text with the spatial structure of the road network and traffic data for generating traffic situations.
• MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation
  25 Sep 2023 2 repositories listed
  Urban time series data forecasting featuring significant contributions to sustainable development is widely studied as an essential task of the smart city.
• STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
  2 Jul 2023 2 repositories listed
  However, a survey study of graph learning, spatial-temporal graph models for traffic, as well as a fair comparison of baseline models are pending and unavoidable issues.
• TraffNet: Learning Causality of Traffic Generation for What-if Prediction
  28 Mar 2023 2 repositories listed
  Real-time what-if traffic prediction is crucial for decision making in intelligent traffic management and control.
• Graph Neural Rough Differential Equations for Traffic Forecasting
  20 Mar 2023 2 repositories listed Syntology ran 6 of 17 samples · 11 unverified
  A prevalent approach in the field is to combine graph convolutional networks and recurrent neural networks for the spatio-temporal processing.
• Multi-task Learning for Sparse Traffic Forecasting
  18 Nov 2022 2 repositories listed
  For this reason, we propose a multi-task learning network that can simultaneously predict the congestion classes and the speed of each road segment.
• PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting
  20 Sep 2022 2 repositories listed
  In this novel task, the numerical input and output are transformed into prompts and the forecasting task is framed in a sentence-to-sentence manner, making it possible to directly apply language models for forecasting…
• Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting
  10 Aug 2022 2 repositories listed
  These results suggest that we can design efficient and effective models as long as they solve the indistinguishability of samples, without being limited to STGNNs.
• Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting
  18 Jun 2022 2 repositories listed
  However, the patterns of time series and the dependencies between them (i.
• A Correlation Information-based Spatiotemporal Network for Traffic Flow Forecasting
  20 May 2022 2 repositories listed
  In this paper, based on the maximal information coefficient, we present two elaborate spatiotemporal representations, spatial correlation information (SCorr) and temporal correlation information (TCorr).
• Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs
  17 Feb 2022 2 repositories listed Syntology ran 2 of 5 samples · 3 unverified
  Multivariate time series forecasting has long received significant attention in real-world applications, such as energy consumption and traffic prediction.
• Traffic signal prediction on transportation networks using spatio-temporal correlations on graphs
  27 Apr 2021 2 repositories listed
  Multivariate time series forecasting poses challenges as the variables are intertwined in time and space, like in the case of traffic signals.
• Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting
  15 Dec 2020 2 repositories listed
  SFTGNN could effectively learn hidden spatial-temporal dependencies by a novel fusion operation of various spatial and temporal graphs, which is generated by a data-driven method.
• Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting
  3 Apr 2020 2 repositories listed
  Spatial-temporal network data forecasting is of great importance in a huge amount of applications for traffic management and urban planning.
• Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction
  2 Sep 2019 2 repositories listed
  Specifically, the first ConvLSTM unit takes normal traffic flow features as input and generates a hidden state at each time-step, which is further fed into the connected convolutional layer for spatial attention map…

Syntology lines on 14 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.