公开(公告)号：US20240367688A1

公开(公告)日：2024-11-07

申请号：US18658674

申请日：2024-05-08

Applicant: Aurora Operations, Inc.

Inventor： Alexander Yuhao Cui ,  Abbas Sadat ,  Sergio Casas ,  Renjie Liao ,  Raquel Urtasun

IPC: B60W60/00 ,  B60W40/04 ,  G05B13/02 ,  G06N3/045

Abstract: Systems and methods are disclosed for motion forecasting and planning for autonomous vehicles. For example, a plurality of future traffic scenarios are determined by modeling a joint distribution of actor trajectories for a plurality of actors, as opposed to an approach that models actors individually. As another example, a diversity objective is evaluated that rewards sampling of the future traffic scenarios that require distinct reactions from the autonomous vehicle. An estimated probability for the plurality of future traffic scenarios can be determined and used to generate a contingency plan for motion of the autonomous vehicle. The contingency plan can include at least one initial short-term trajectory intended for immediate action of the AV and a plurality of subsequent long-term trajectories associated with the plurality of future traffic scenarios.

公开(公告)号：US12103554B2

公开(公告)日：2024-10-01

申请号：US17150982

申请日：2021-01-15

Applicant: Aurora Operations, Inc.

Inventor： Raquel Urtasun ,  Kelvin Ka Wing Wong ,  Qiang Zhang ,  Bin Yang ,  Ming Liang ,  Renjie Liao

IPC: B60W60/00 ,  B60W50/00 ,  G06F30/27 ,  G06N3/08

CPC classification number: B60W60/001 ,  B60W50/00 ,  G06F30/27 ,  G06N3/08 ,  B60W2050/0019 ,  B60W2050/0083

Abstract: Systems and methods of the present disclosure are directed to a method. The method can include obtaining simplified scenario data associated with a simulated scenario. The method can include determining, using a machine-learned perception-prediction simulation model, a simulated perception-prediction output based at least in part on the simplified scenario data. The method can include evaluating a loss function comprising a perception loss term and a prediction loss term. The method can include adjusting one or more parameters of the machine-learned perception-prediction simulation model based at least in part on the loss function.