GERMANY

Abstract. Human labeled datasets have enabled enormous breakthroughs in terms of autonomous vehicle performance. In this presentation I will share insights from annotating six widely used public datasets. We will look at the highlights and shortcomings of these datasets and how the performance of leading methods improved over time. I argue that these datasets do not scale to level 4 (high automation) or even level 5 (full automation). Beyond that, I will discuss the latest trend of autolabeled datasets. Based on our newly released nuPlan dataset I will show that autolabeling, scenario mining and closed loop evaluation are key to scaling autonomous vehicles to new operational design domains.

Primary location: Delft Netherlands