- Make sure that your computer's or server's OS is Ubuntu 18.04 or lower, or Mac.
- Follow instructions here to install Miniconda, likely wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.shfollowed bybash Miniconda3-latest-Linux-x86_64.sh
- Run bash scripts/setup_sumo_<os_version>.shcorresponding to your OS version to set up SUMO and add~/sumo_binaries/binto yourPATHenvironment variable. Try runningsumo
- Install PyTorch from pytorch.org.
- Clone the util directory with git clone git@github.com:ZhongxiaYan/util.git uorgit clone https://github.com/ZhongxiaYan/util.git uandpip install -r u/requirements.txt
- Install dependencies pip install -r requirements.txt
Let <res_dir> be the result directory, which is where the model checkpoints, training logs, and training csv results will be saved. Add render as an argument for using sumo-gui instead of sumo. E.g. python pexps/<script>.py <res_dir> render.
python pexps/bneck.py <res_dir>
python pexps/g2x1.py <res_dir>
This is currently incomplete and only has some SUMO support for custom 8-way networks, but RL support is not implemented at the moment.
python pexps/8way.py <res_dir>