Traffic Prediction Open Code Summary Save

Summary of open source code for deep learning models in the field of traffic prediction

Project README

Deep learning models for traffic prediction

This is a summary for deep learning models with open code for traffic prediction.

These models are classified based on the following tasks.

  • Traffic flow prediction

  • Traffic speed prediction

  • On-Demand service prediction

  • Travel time prediction

  • Traffic accident prediction

  • Traffic location prediction

  • Others

Task Model Paper Code Publication
Traffic flow prediction ST-ResNet Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction tf，Pytorch，Keras AAAI2017/A
ACFM ACFM: A Dynamic Spatial-Temporal Network for Traffic Prediction Pytorch ACM MM2018/A
STDN Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction Keras AAAI2019/A
ASTGCN Attention based spatial-temporal graph convolutional networks for traffic flow forecasting Pytorch AAAI2019/A
ST-MetaNet Urban traffic prediction from spatio-temporal data using deep meta learning MXNet KDD2019/A
STSGCN Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting MXNet AAAI2020/A
STGNN STGNN: Traffic Flow Prediction via Spatial Temporal Graph Neural Network Pytorch WWW2020/A
AGCRN Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting Pytorch NIPS2020/A
DSAN Preserving Dynamic Attention for Long-Term Spatial-Temporal Prediction tf2 KDD2020/A
MPGCN Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network Pytorch ICDE2020/A
ST-GDN Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network tf AAAI2021/A
TrGNN Traffic Flow Prediction with Vehicle Trajectories Pytorch AAAI2021/A
STFGNN Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting MXNet AAAI2021/A
STGODE STGODE : Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting Pytorch KDD2021/A
ASTGNN Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting Pytorch TKDE2021/A
STG-NCDE Graph Neural Controlled Differential Equations for Traffic Forecasting Pytorch AAAI2022/A
STDEN STDEN Towards Physics-Guided Neural Networks for Traffic Flow Prediction Pytorch AAAI2022/A
SAE Traffic Flow Prediction With Big Data: A Deep Learning Approach Keras TITS2015/B
STNN Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery Pytorch ICDM2017/B
ST-3DNet Deep Spatial–Temporal 3D Convolutional Neural Networks for Traffic Data Forecasting Keras TITS2019/B
STAG-GCN Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic Flow Forecasting Pytorch CIKM2020/B
ST-CGA Spatial-Temporal Convolutional Graph Attention Networks for Citywide Traffic Flow Forecasting Keras CIKM2020/B
ResLSTM Deep Learning Architecture for Short-Term Passenger Flow Forecasting in Urban Rail Transit Keras TITS2020/B
DGCN Dynamic Graph Convolution Network for Traffic Forecasting Based on Latent Network of Laplace Matrix Estimation Pytorch TITS2020/B
ToGCN Topological Graph Convolutional Network-Based Urban Traffic Flow and Density Prediction Pytorch TITS2020/B
Multi-STGCnet Multi-STGCnet: A Graph Convolution Based Spatial-Temporal Framework for Subway Passenger Flow Forecasting Keras IJCNN2020/C
Conv-GCN Multi-Graph Convolutional Network for Short-Term Passenger Flow Forecasting in Urban Rail Transit Keras IET-ITS2020/C
TCC-LSTM-LSM A temporal-aware LSTM enhanced by loss-switch mechanism for traffic flow forecasting Keras Neurocomputing2021/C
LSTM/GRU Using LSTM and GRU neural network methods for traffic flow prediction Keras YAC2016/none
Cluster_LSTM Foreseeing Congestion using LSTM on Urban Traffic Flow Clusters Keras ICSAI2019/none
CRANN A Spatio-Temporal Spot-Forecasting Framework forUrban Traffic Prediction Pytorch Applied Soft Computing2020/none
GNN-flow Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks Pytorch IEEE SMARTCOMP2020/none
Deep_Sedanion_Network Traffic flow prediction using Deep Sedenion Networks Pytorch arXiv2020
MATGCN Multi-Attention Temporal Graph Convolution Network for Traffic Flow Forecasting Pytorch 本科毕设
Traffic speed prediction DCRNN Diffusion convolutional recurrent neural network: Data-driven traffic forecasting tf，Pytorch ICLR2018/none
STGCN Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting tf，MXNet，Pytorch，Keras IJCAI2018/A
BaiduTraffic Deep sequence learning with auxiliary information for traffic prediction tf KDD2018/A
Graph WaveNet Graph wavenet for deep spatial-temporal graph modeling Pytorch IJCAI2019/A
Graph WaveNet-V2 Incrementally Improving Graph WaveNet Performance on Traffic Prediction Pytorch arXiv2019/none
GMAN Gman: A graph multi-attention network for traffic prediction tf AAAI2020/A
MRA-BGCN Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting Pytorch AAAI2020/A
MTGNN Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks Pytorch KDD2020/A
Curb-GAN Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks Pytorch KDD2020/A
AF Stochastic origin-destination matrix forecasting using dual-stage graph convolutional, recurrent neural networks tf ICDE2020/A
FC-GAGA FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting tf AAAI2021/A
HGCN Hierarchical Graph Convolution Networks for Traffic Forecasting Pytorch AAAI2021/A
ST-Norm ST-Norm: Spatial and Temporal Normalization for Multi-variateTime Series Forecasting Pytorch KDD2021/A
DMSTGCN Dynamic and Multi-faceted Spatio-temporal Deep Learning for Traffic Speed Forecasting Pytorch KDD2021/A
GTS Discrete Graph Structure Learning for Forecasting Multiple Time Series Pytorch ICLR2021/none
DKFN Graph Convolutional Networks with Kalman Filtering for Traffic Prediction Pytorch SIGSPATIAL2020/none
T-GCN T-gcn: A temporal graph convolutional network for traffic prediction tf TITS2019/B
TGC-LSTM Traffic graph convolutional recurrent neural network: A deep learning framework for network-scale traffic learning and forecasting Pytorch TITS2020/B
ST-GRAT ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed Pytorch CIKM2020/B
GaAN GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs MXNet UAI2018/B
TL-DCRNN Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting tf ICPR2020/C
ST-MGAT ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting Pytorch ICTAI2020/C
DGFN Dynamic Graph Filters Networks: A Gray-box Model for Multistep Traffic Forecasting tf2 ITSC2020/none
ATDM On the Inclusion of Spatial Information for Spatio-Temporal Neural Networks Pytorch arXiv2020/none
STTN Spatial-Temporal Transformer Networks for Traffic Flow Forecasting Pytorch arXiv2020/none
DGCRN Dynamic Graph Convolutional Recurrent Network for Traffic Prediction Benchmark and Solution Pytorch arXiv2021/none
STAWnet Spatial-temporal attention wavenet: A deep learning framework for traffic prediction considering spatial-temporal dependencies Pytorch IET Intelligent Transport Systems2021/C
On-Demand service prediction DMVST-Net Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction Keras AAAI2018/A
STG2Seq Stg2seq: Spatial-temporal graph to sequence model for multi-step passenger demand forecasting tf IJCAL2019/A
GEML Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling Keras KDD2019/A
CCRNN Coupled Layer-wise Graph Convolution for Transportation Demand Prediction Pytorch AAAI2021/A
CSTN Contextualized Spatial–Temporal Network for Taxi Origin-Destination Demand Prediction Keras TITS2019/B
GraphLSTM Grids versus graphs: Partitioning space for improved taxi demand-supply forecasts Pytorch TITS2020/B
DPFE Estimating multi-year 24/7 origin-destination demand using high-granular multi-source traffic data Pytorch Transportation Research Part C: Emerging Technologies2018/none
ST-ED-RMGC Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network Keras Transportation Research Part C: Emerging Technologies2021/none
Travel time prediction DeepTTE When will you arrive? estimating travel time based on deep neural networks Pytorch AAAI2018/A
HetETA HetETA: Heterogeneous Information Network Embedding for Estimating Time of Arrival tf KDD2020/A
TTPNet TTPNet: A Neural Network for Travel Time Prediction Based on Tensor Decomposition and Graph Embedding Pytorch TKDE2020/A
HyperETA HyperETA: An Estimated Time of Arrival Method based on Hypercube Clustering Pytorch techrxiv2021/None
GSTA GSTA: gated spatial–temporal attention approach for travel time prediction tf2 Neural Computing and Applications2021/None
Traffic accident prediction RiskOracle RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework tf AAAI2020/A
RiskSeq Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective tf TKDE2020/A
GSNet GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting Pytorch AAAI2021/A
DSTGCN Deep Spatio-Temporal Graph Convolutional Network for Traffic Accident Prediction Pytorch Neurocomputing2020/C
Traffic location prediction STRNN Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts Pytorch AAAI2016/A
DeepMove DeepMove: Predicting Human Mobility with Attentional Recurrent Networks Pytorch WWW2018/A
HST-LSTM HST-LSTM: A Hierarchical Spatial-Temporal Long-Short Term Memory Network for Location Prediction Pytorch IJCAI2018/A
VANext Predciting Human Mobility via Variational Attention tf WWW2019/A
FQA Multi-agent Trajectory Prediction with Fuzzy Query Attention Pytorch NIPS2020/A
MALMCS Dynamic Public Resource Allocation based on Human Mobility Prediction python UbiComp2020/A
SERM SERM: A Recurrent Model for Next Location Prediction in Semantic Trajectories Keras CIKM2017/B
Map matching ST-Matching Map-matching for low-sampling-rate GPS trajectories Python SIGSPATIAL2009/None
IVMM An Interactive-Voting Based Map Matching Algorithm Python MDM2010/C
HMMM Hidden Markov map matching through noise and sparseness Python SIGSPATIAL2009/None
PIF The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe Vehicle Data Python TITS2014/B
Others seq2seq Sequence to Sequence Learning with Neural Networks Keras NIPS2014/A
NASR Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation tf KDD2019/A
HRNR Learning Effective Road Network Representation with Hierarchical Graph Neural Networks Pytorch KDD2020/A
SHARE Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction Pytorch AAAI2020/A
TALE Pre-training Time-Aware Location Embeddings from Spatial-Temporal Trajectories Pytorch TKDE2021/A
PVCGN Physical-Virtual Collaboration Modeling for Intra-and Inter-Station Metro Ridership Prediction Pytorch TITS2020/B
DCRNN Evaluation and prediction of transportation resilience under extreme weather events: A diffusion graph convolutional approach tf Transportation Research Part C: Emerging Technologies2020/none
LibCity LibCity: An Open Library for Traffic Prediction Pytorch SIGSPATIAL2021/None
Open Source Agenda is not affiliated with "Traffic Prediction Open Code Summary" Project. README Source: aptx1231/Traffic-Prediction-Open-Code-Summary
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Repository
aptx1231/Traffic-Prediction-Open-Code-Summary
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Tags
Deep Learning Estimated Time Of Arrival Graph Convolutional Networks Graph Neural Networks On Demand On Demand Service Open Code Open Source Paper List Spatio Temporal Spatio Temporal Prediction Time Series Prediction Traffic Traffic Accident Prediction Traffic Flow Prediction Traffic Prediction Traffic Speed Prediction Trajectory Prediction Travel Time Prediction Libcity

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