This project provides a sandbox environment for training self-driving car agents using the Nvidia PilotNet neural network architecture. It combines Unity for realistic physics simulation with Python, Keras, and TensorFlow for model training. Users generate image-steering training pairs by driving in the simulator, then train a convolutional neural network to predict steering angles from camera input. The trained model can be loaded back into the simulator to autonomously control the vehicle.