🚗 Autonomous Vehicle Brake Control System (Fuzzy Logic)

📌 About the Project

This repository contains an application study demonstrating an Autonomous Vehicle Brake Control System powered by Fuzzy Logic. The system evaluates real-time environmental factors to determine the optimal braking pressure, ensuring safety and ride comfort.

This project was developed to model human-like decision-making processes in autonomous driving scenarios using mathematical fuzzy sets and rules, moving away from rigid binary constraints.

⚙️ Features

• Mamdani Fuzzy Inference System: Implements logical rules to mimic human driving intuition.
• Input Variables: Evaluates dynamic environmental inputs such as Speed (Hız) and Distance (Mesafe).
• Output Variable: Calculates the precise and safe Brake Pressure (Fren Basıncı).
• Visualization: Graphical representations of membership functions and the defuzzification process.

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📈 Visualizations

Here are the fuzzy set representations for our system's inputs and outputs:

1. Speed (Hız) Input

2. Distance (Mesafe) Input

3. Brake Pressure (Fren Basıncı) Output

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🛠️ Technologies & Libraries

• Python 3.x
• NumPy & SciPy: For numerical operations, mathematical modeling, and scientific computing.
• NetworkX: For structural analysis and modeling.
• Matplotlib: For visualizing the fuzzy sets and output graphs.

🚀 Installation & Setup

1. Clone the repository:

   git clone [https://github.com/OmerFarukAY/fuzzyLogicProject.git](https://github.com/OmerFarukAY/fuzzyLogicProject.git)
   cd fuzzyLogicProject
   

2. Install the required dependencies:

   pip install scipy networkx matplotlib numpy scikit-fuzzy
   

3. Run the application:

   python otonomFrenleme.py
   

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Author: Ömer Faruk AY