SelfD: Self-Learning Large-Scale Driving Policies From the Web

Abstract

Our goal is to develop robust, generalized, and easily deployable decision-making policies for navigation. Our key insight is to make use of the hours of freely available and highly diverse navigation data from the web in order to augment the knowledge and robustness of an initially trained navigation policy.