Efficient-Traffic-Controlling-System-using-Fuzzy-Logic

This project was developed as a mini project for the course Fuzzy Logic and Neural Network during my B.tech.

👨‍💻 Developed By:

• Krishanu Dev Sarma (ECB18006)

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📌 Project Overview

Traffic congestion is a major problem in urban areas. This project presents a fuzzy logic-based intelligent traffic light controller, which takes real-time inputs such as the number of waiting and incoming vehicles, and outputs the optimal wait time using fuzzy inference.

The system consists of:

• Fuzzification of crisp inputs (number of waiting and incoming cars)
• Rule-based inference using fuzzy logic
• Defuzzification to generate a crisp output (wait time in seconds)

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🔧 Technologies Used

• Python
• scikit-fuzzy
• NumPy
• Matplotlib (for optional visualization)

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📂 Folder Structure

Folder	Purpose
Codes/	Contains all Python scripts divided into modules
Results/	Example simulation outputs and visualizations
requirements.txt	Python dependencies list

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🚀 How to Run

1. Clone the repository:

git clone https://github.com/KrishanuDevSarma/Efficient-Traffic-Controlling-System-using-Fuzzy-Logic.git
cd fuzzy-traffic-control

2. Install dependencies:

pip install -r requirements.txt

3. Run the controller:

python Codes/Model/fuzzy_traffic_controller.py