Waymo LLC

Scott Morgan Ettinger

Dragomir Dimitrov Anguelov

Khaled Refaat

Wei Chai

Benjamin Sapp

Benjamin James Caine

Liting Sun

Rebecca Dawn Roelofs

Methods, systems, and apparatus for predicting future trajectories of agents in an environment. In one aspect, a system comprises one or more computers configured to receive a data set comprising multiple training examples. The training examples include scene data comprising respective agent data for multiple agents and a ground truth trajectory for a target agent that represents ground truth motion of the target agent after a corresponding time point. The one or more computers obtain data identifying one or more of the multiple agents as non-causal agents for each training example. A non-causal agent is an agent whose states do not cause the ground truth trajectory for the target agent to change. The one or more computers generate a respective modified training example from each of the multiple training examples.

Robust behavior prediction neural networks through non-causal agent based augmentation

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for evaluating a behavior prediction system.

Evaluating multi-modal trajectory predictions for autonomous driving

Growing community of inventors

San Carlos, CA, United States of America

Scott Morgan Ettinger