There are 17 repositories under traffic-prediction topic.
LibCity: An Open Library for Urban Spatial-temporal Data Mining
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
GMAN: A Graph Multi-Attention Network for Traffic Prediction (GMAN, https://fanxlxmu.github.io/publication/aaai2020/) was accepted by AAAI-2020.
Traffic Graph Convolutional Recurrent Neural Network
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc.
This repo includes introduction, code and dataset of our paper Deep Sequence Learning with Auxiliary Information for Traffic Prediction (KDD 2018).
Summary of open source code for deep learning models in the field of traffic prediction
Paper list in traffic prediction field
Traffic data processing tools in LibCity
[AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.
A collection of research on spatio-temporal data mining
Useful resources for traffic prediction, including popular papers, datasets, tutorials, toolkits, and other helpful repositories.
Paper & Code & Dataset Collection of Spatial-Temporal Data Mining.
Predict traffic flow with LSTM. For experimental purposes only, unsupported!
[Pattern Recognition] Decomposition Dynamic Graph Conolutional Recurrent Network for Traffic Forecasting
Organize some grid-based traffic flow datasets, mainly New York City bicycle and taxi data
[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"
Welcome to quote our published papers, and the codes have been uploaded.
Spatial-Temporal Graph Convolutional Neural Network with LSTM layers
We have used Support Vector Regression and Random Forest Regression to predict traffic or congestion.
Repository for Deep Learning on Traffic Prediction: Methods, Analysis and Future Directions<https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9352246>
Reproduce - Traffic_prediction - StemGNN(NeurIPS20)
Code repository accompanying the research paper "Uncertainty Quantification for Image-based Traffic Prediction across Cities"
Traffic prediction using Spatio-Temporal Graph Neural Network
The project aims to develop models that can forecast traffic congestion, aiding in effective traffic management and planning.
ST-MAN: Spatio-Temporal Multimodal Attention Network for Traffic Prediction (KSEM 2023)
Traffic prediction with graph neural network using PyTorch Geometric. The implementation uses the MetaLayer class to build the GNN which allows for separate edge, node and global models.
Dijkstra adjacency distance matrices were calculated for 40 cities from traffic sensor locations provide by UTD19 https://utd19.ethz.ch/.