There are 1 repository under traffic-forecasting topic.
LibCity: An Open Library for Urban Spatial-temporal Data Mining
A Standard and Fair Time Series Forecasting Benchmark and Toolkit.
Traffic Graph Convolutional Recurrent Neural Network
Code for our SIGKDD'22 paper Pre-training-Enhanced Spatial-Temporal Graph Neural Network For Multivariate Time Series Forecasting.
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).
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.
Paper list in traffic prediction field
Code for our CIKM'22 paper Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting.
Code for our VLDB'22 paper Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting.
ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction
Useful resources for traffic prediction, including popular papers, datasets, tutorials, toolkits, and other helpful repositories.
"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022
[AAAI23] This it the official github for AAAI23 paper "Spatio-Temporal Meta-Graph Learning for Traffic Forecasting"
[ICDE'2023] When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks
[Pattern Recognition] Decomposition Dynamic Graph Conolutional Recurrent Network for Traffic Forecasting
[CIKM 2023] This is the official source code of "TrendGCN: Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting" based on Pytorch.
Source codes of CIKM2022 Full Paper "Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities"
[IJCNN 2021] Unified Spatio-Temporal modeling for traffic forecasting using Graph Convolutional Network
[PAKDD 2021] SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network
[IJCAI'2022] FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting
Graph Neural Networks utilization for Spatiotemporal graphs. These methods will be applied into the problem of forecasting traffic flow on PEMS-Bay, METR-LA and Seattle Loop Datasets
A PyTorch implementation of the Attention Diffusion Network from "Structured Time Series Prediction without Structural Prior"
Repository for the paper "Graph Convolutional Networks for Traffic Forecasting with Missing Values" in DMKD'22
An eXplainable AI system to elucidate short-term speed forecasts in traffic networks obtained by Spatio-Temporal Graph Neural Networks.
LogiTraffic is an IoT based Deep Learning Powered Traffic Management and Theft Detection Solution. It’s an online website platform using which user can keep check on certain real-time parameters associated with the vehicle which includes fuel-level, GPS location, Brake System Temperature, Speed, Traffic Forecasting using Vehicle Detection and obtaining vehicle count through different road nodes and predicting Traffic Congestion/Jams. In case the user suspects his/her car has been stolen by logging in using the credentials one can lock the vehicles and see driver’s real time video stream and a picture of the driver is downloaded on the system so that it can be used for further investigation and police cases. (YouTube Video Presentation by Team Aztecs: https://youtu.be/rP2OGjZJ5NY) – Presented in E-Ujjwala Hackathon 2020 by Birsa Institute of Technology, Jharkhand (Team Aztecs - Finalists)
Model-based AI approach for network and service coordination leveraging uncertain traffic forecasts
ST-MAN: Spatio-Temporal Multimodal Attention Network for Traffic Prediction (KSEM 2023)
Repository for advanced traffic forecasting models integrating GCN, LSTM/Bi-LSTM, and attention mechanisms for improved accuracy, including weather data processing.
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)
Computation of dynamic selfish flows using predicted travel times
This repository contains code and resources for a project focused on predicting traffic volume using Temporal Convolutional Networks (TCNs). Leveraging the Metro Interstate Traffic Volume dataset from 2012-2018, the project aims to develop an accurate model for short- to medium-term traffic volume forecasting in Minneapolis-St Paul, MN.
BIND: Binding Intertemporal Nodes for Multivariate Timeseries Forecasting (Ongoing)
Understanding the UNet for Traffic Forecasting Task - A Visual Analytics Approach
Final Degree Project