To Veer or Not to Veer: Learning from Experts How to Stay Within the Crosswalk

One of the many challenges faced by visually impaired (VI) individuals is the crossing of intersections while remaining within the crosswalk. We present a Learning from Demonstration (LfD) approach to tackle this problem and provide VI users with an assistive agent. Contrary to previous methods, our solution does not presume the existence of particular features in crosswalks. The application of the LfD framework helped us transfer sighted individuals' abilities to the intelligent assistive agent. Our proposed approach started from a collection of 215 demonstrative videos of intersection crossings executed by sighted individuals ("the experts"). We labeled the video frames to gather the experts' recommended actions, and then applied a policy derivation technique to extract the optimal behavior using state-of-the-art Convolutional Neural Networks. Finally, to assess the feasibility of such a solution, we evaluated the performance of the trained agent in predicting expert actions.