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The official code for paper "Generalising Traffic Forecasting to Regions without Traffic Observations". This paper has been accepted by AAAI26.

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This is official code for GenCast.

Good News! Our paper Generalising Traffic Forecasting to Regions without Traffic Observations has been accepted by AAAI26. This code is based on our previous work STSM STSM Code. Our full paper is available at paper.

Requirements

-pytorch -pandas -numpy -tables -CUDA/12.5.1

The details are in the requirement.txt

Dataset

Google Drive: https://drive.google.com/drive/folders/1_imrTikGhIbZIyrRynG4bXhkaZA9xQgE?usp=share_link

Baidu Drive: https://pan.baidu.com/s/1DtyDp4stCKQ_P-4nox1O8A 提取码: cast Due to the dataset is large, we will upload it to google drive and baiduyun for sharing. Or you can download traffic data from STSM and weather data from ERA5.

Putting Dataset dir under the GenCast dir.

Train the model

go to dir GenCast-L or GenCast-H

chmod +x ./metr.sh ./metr.sh

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The official code for paper "Generalising Traffic Forecasting to Regions without Traffic Observations". This paper has been accepted by AAAI26.

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