There are 25 repositories under traffic-flow-prediction topic.
LibCity: An Open Library for Urban Spatial-temporal Data Mining
Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).
Traffic Graph Convolutional Recurrent Neural Network
Some TrafficFlowForecasting Solutions(交通流量预测解决方案)
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
Summary of open source code for deep learning models in the field of traffic prediction
[AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.
ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction
[ICML'2024] "FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction"
[Pattern Recognition] Decomposition Dynamic Graph Conolutional Recurrent Network for Traffic Forecasting
[AAAI 2019] DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis
A PyTorch implementation of T-GCN
Attention Feature Fusion base on spatial-temporal Graph Convolutional Network(AFFGCN)
Long Short-Term Memory(LSTM) is a particular type of Recurrent Neural Network(RNN) that can retain important information over time using memory cells. This project includes understanding and implementing LSTM for traffic flow prediction along with the introduction of traffic flow prediction, Literature review, methodology, etc.
This work considers combine multi-tricks with highway network to achieve traffic flow prediction accurately.
A time series task- predicting traffic flow using LSTM model
ST-MAN: Spatio-Temporal Multimodal Attention Network for Traffic Prediction (KSEM 2023)
M-LibCity: An Open Source Library for Urban Spatio-temporal Prediction Models Based on MindSpore
DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction
Traffic flow prediction using Spatio-Temporal Residual Networks
Official repo for the following paper: Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training (SCPT) (ECML PKDD DAMI '23)
Predict traffic flow data by lstm in Keras
Predict traffic flow by affinity propagation clustering and LSTM
2022年讯飞开发者大赛-考虑时空依赖及全局要素的城市道路交通流量预测挑战赛-Top3解决方案
This project is intended to create, develop and tune a neural network to predict traffic flow. The data provided was intended to be a list of log records written every 1 hour about the city of Braga, Portugal containing information about temperature, humidity, rain, traffic flow, etc. The data was incomplete, days were missing, there were hour gaps and corrupted information. All the data was treated to the best of my and my coworkers abilities.
A Pytorch Implementation of Pattern Sensitive Network (PSN)
A project leverages external data (traffic incidents, weather) to predict traffic flow. Graph is used to model the complex relationship of data.
Bilgisayar Mühendisliği Bölümü Bilgisayar (Ara) Projesi
New works about traffic prediction
🌎 🚙📚 Predicting travel times and traffic density on a highway in Slovenia
Ambient Sensorization Techniques to monitor the traffic flow in Braga
Submitted to Introduction to Machine Learning (CS480/680, 2020 Spring).