Neural transportation networks

This is the final project of the course 10-617 Intermediate Deep Learning at Carnegie Mellon University. It studies the use of Deep Learning model to estimate the travelers' utility function in route choice models using traffic count data. The analyses were performed using synthetic data and the models were implemented with PyTorch primarily.

Development setup

1. Clone the repository
2. Create virtual environment (e.g. "venv") python3 -m venv venv
3. Activate virtual environment source venv/bin/activate
4. Install the development dependencies: pip install -r requirements.txt
5. Run python3 main.py

Visualizations