TMS2 - MARL Traffic Management Models
Multi-Agent Reinforcement Learning Models
Coordinated multi-intersection traffic control using MARL algorithms.
Algorithms:
- IQL: Independent Q-Learning
- VDN: Value Decomposition Networks
- QMIX: Monotonic value factorization
Features:
- Multi-intersection coordination
- Green wave optimization
- Network-wide throughput maximization
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