We propose a demonstration of our novel DeepRacing framework at NeurIPS 2020 as a platform for training and evaluating high-speed autonomous race cars. DeepRacing uses the immensely popular and photo-realistic Formula One racing game and converts it into a simulation environment for autonomous racing.

We will demo both the ability to autonomously race the F1 car in the game using control inputs predicted by machine learned driving policies as well as tag images of the driver's point-of-view with various state information (such as the position, velocity, and control values for the racing agents) to enable generation of labelled datasets for supervised machine learning. We will demonstrate this technology in a real-time web broadcast with interactive inputs from the NeurIPS audience.