Traffic Forecasting Model

Introduction

Traffic forecasting is a crucial component of intelligent transportation systems, enabling efficient traffic flow management, congestion reduction, and improved road safety. This model leverages machine learning techniques to predict traffic flow based on historical data and related factors.

Installation

1. Clone the repository:

   git clone https://github.com/Mr-1504/Traffic-Forecasting-Model.git

2. Install dependencies:

   cd Traffic-Forecasting-Model
   pip install -r requirements.txt

Usage

1. Prepare the data:

   • Collect historical traffic data from reliable sources.
   • Ensure the data is correctly formatted and stored in the resource/ directory.

2. Train the model:

   python train.py

3. Make predictions:

   python predict.py --input your_input_data.csv --output your_output_predictions.csv

Directory Structure

Traffic-Forecasting-Model/
├── res/                # Resources and model results
│   ├── GAN/            # Results for GAN model
│   ├── GRU/            # Results for GRU model (e.g., metrics and saved models)
│   ├── LSTM/           # Results for LSTM model
│   ├── MLP/            # Results for MLP model
│   ├── MLP_LSTM/       # Results for MLP_LSTM model
│   ├── RCNN/           # Results for RCNN model
│   ├── RNN/            # Results for RNN model
│   └── SVR/            # Results for SVR model
├── resource/           # Directory containing input data files
│   ├── Traffic - Copy.csv
│   └── train27303.csv
├── src/                # Main source code of the project
│   ├── Decision Tree.py
│   ├── GAN.py
│   ├── GRU.py
│   ├── LSTM.py
│   ├── MLP.py
│   ├── MLP_LSTM.py
│   ├── Plot.py         # Script for visualizing results
│   ├── RCNN.py
│   ├── RNN.py
│   └── SVR.py
|__ requirements.txt

Contributing

We welcome contributions from the community. Please create a new branch, make your changes, and submit a pull request.

License

This project is licensed under the MIT License.

Contact

If you have any questions or suggestions, feel free to open an issue on GitHub.