Traffic Forecasting

Setup

$ git clone https://github.com/akashsonowal/traffic-forecasting.git && cd traffic-forecasting
$ virtualenv --python=python3.8 myenv && source myenv/bin/activate 
$ pip install -r requirements.txt

Usage

$ python experiment.py

In a single day, we forecast at multiple time stamps (N_SLOTS) and at each time stamp we forecast for a window of 9.

The plot above shows the node 1 forecast only for the 1st prediction in a single window for all time stamps in the first day of test dataset.

Citation

@inproceedings{yu2018spatio,
    title={Spatio-temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting},
    author={Yu, Bing and Yin, Haoteng and Zhu, Zhanxing},
    booktitle={Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI)},
    year={2018}
}