GenCast: Traffic Forecasting for Unobserved Regions (official code)
April 20, 2026 ยท View on GitHub
๐ AAAI 2026
What problem?
Forecast traffic in regions WITHOUT sensors
Why hard?
No historical observations โ generalisation issue
What we do?
- Physics-informed learning
- Weather-traffic fusion
- Spatial grouping
Result
โ error 3.1%, โ Rยฒ 125%
Quick start
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 ๆๅ็ : 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