Smart Traffic Signal Controller using Raspberry Pi

This project is designed to automate traffic signal timing based on live image processing. It utilizes a Raspberry Pi, Pi Camera 2, and GPIO components to dynamically adjust the green light duration according to traffic conditions.

🛠️ Project Structure

File	Description
camera_capture.py	Captures an image using the Pi Camera 2.
image_processing.py	Processes the captured image using Canny Edge Detection to assess traffic density.
lights.py	Sets the duration of the green signal based on processed image data.
lightspigpio.py	Interfaces with GPIO pins using the gpiozero library to control the signal lights.
main.py	Main script that orchestrates the full process from image capture to signal control.
references.py	Captures and stores a reference image for background subtraction or comparison.
servomotor.py	Controls a servo motor to rotate or move at specific time intervals.
__pycache__/	Contains Python bytecode files (auto-generated).

⚙️ How It Works

1. Image Capture: camera_capture.py triggers the Pi Camera to capture a real-time image of the traffic lane.
2. Image Analysis: image_processing.py applies Canny Edge Detection to identify vehicles and estimate traffic density.
3. Signal Timing: Based on the density, lights.py adjusts the green light duration dynamically.
4. Signal Control: lightspigpio.py handles GPIO interactions to turn the traffic lights on or off.
5. Reference Image: references.py allows capturing a reference image to help in differential analysis.
6. Servo Control: servomotor.py manages timed servo operations (e.g., gate opening/closing).

📦 Requirements

• Raspberry Pi 5 (or any model with GPIO support)
• Pi Camera 2
• Traffic Light Modules
• Servo Motor
• Python 3.x
• Libraries:
  • gpiozero
  • opencv-python
  • numpy

Install Python dependencies:

pip install gpiozero opencv-python numpy

🚀 Getting Started

1. Connect your Pi Camera and traffic signal LEDs to GPIO pins.
2. Run the main script:

python main.py

3. The system will:
   • Capture an image.
   • Analyze traffic density.
   • Adjust green signal timing.
   • Rotate servo motor (if applicable).

🧠 Future Improvements

• Integrate with cloud for data logging.
• Add GUI to visualize traffic and timings.
• Expand to multi-lane or multi-signal support.

⚠️ Disclaimer

Ensure safe practices when working with electronics and live environments. Use dummy loads during development.

---