tms2-gnn-encoders

TMS2 - GNN Traffic Management Models

Graph Neural Network Models

GNN-based traffic state encoders for learning road network representations.

Architectures:

• GCN: Graph Convolutional Networks
• GAT: Graph Attention Networks

Use Cases:

• Traffic state encoding for RL agents
• Network-level congestion prediction
• Spatial dependency modeling

Model Description

These models are part of the Traffic Management System 2 (TMS2) project, an intelligent traffic control system using deep learning and reinforcement learning.

Training Details

• Framework: PyTorch
• Training Platform: Google Colab (T4 GPU)
• Training Date: December 2025

Usage

import torch

# Load model
model = torch.load('model.pt')
model.eval()

# Inference
with torch.no_grad():
    output = model(input_tensor)

License

Apache 2.0