Efficient & Realistic Simulation for Autonomous Driving

About the Speaker

Shimon Whiteson is a Professor of Computer Science at the University of Oxford and a Senior Staff Research Scientist at Waymo UK. His research focuses on deep reinforcement learning and imitation learning, with applications in robotics and video games. He completed his doctorate at the University of Texas at Austin in 2007. He spent eight years as an Assistant and then an Associate Professor at the University of Amsterdam before joining Oxford as an Associate Professor in 2015. He was awarded a Starting Grant from the European Research Council in 2014, a Google Faculty Research Award in 2017, and a JPMorgan Faculty Award in 2019. His spin-out company Latent Logic was acquired by Waymo in 2019.

Abstract

In this talk, I will discuss some of the key challenges in performing efficient and realistic simulation for autonomous driving, with a particular focus on how to train simulated agents that model the human road users, such as cars, cyclists, and pedestrians who share the road with autonomous vehicles. I will discuss the need for distributionally realistic agents and describe methods for training hierarchical agents to this end. I will also discuss the need to model the safety-critical events that rarely appear in the data and describe a diffusion-based method for doing so. Finally, I'll describe the Waymo Sim Agent Challenge and the Waymo Open Motion Dataset on which it is based.