TMS2 - LSTM Traffic Management Models
LSTM Traffic Prediction Models
Long Short-Term Memory networks for traffic flow prediction.
Capabilities:
- Short-term traffic flow forecasting
- Congestion prediction
- Temporal pattern recognition
Input/Output:
- Input: Historical traffic sequences
- Output: Future traffic flow predictions
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