Autonomous Car Simulation with NEAT

This project demonstrates an autonomous car simulation using the NEAT algorithm. The simulation uses pygame for graphical rendering and neat-python to evolve neural networks that control the car's movement. The goal is to train the car to navigate a track without crashing into the borders.

Features

• Autonomous car controlled by evolved neural networks.
• Real-time simulation using pygame.
• Configurable NEAT parameters for custom experiments.
• Visualization of the car's sensors and movement.

Installation

Prerequisites

• Python 3.x
• pip

Steps

1. Clone the repository.

   https://github.com/codeabuu/Ai-Car_Simulation.git

2. Install the required libraries:

   pip install -r requirements.txt

Usage

1. Ensure you have the following files in your working directory:

   • config.txt (NEAT configuration file)
   • car.png (car sprite image)
   • map.png (track map image)

2. Run the simulation:

   python main.py

3. The simulation window will open, displaying the car's movement and evolution process.

The NEAT configuration is specified in config.txt. You can modify this file to experiment with different NEAT parameters.