公开(公告)号：US12086511B2

公开(公告)日：2024-09-10

申请号：US17098609

申请日：2020-11-16

申请人： Nuro, Inc.

发明人： Varun Krish Mohan ,  Chuan Qiu

IPC分类号： G06F30/20 ,  B60W30/09 ,  B60W30/095 ,  B60W60/00 ,  G06F8/60 ,  G06F8/71 ,  G06F11/34 ,  G06F11/36 ,  G06F18/22 ,  G06F18/241 ,  G06F30/15 ,  G06V20/58 ,  G06F11/30 ,  G06F30/27

CPC分类号： G06F30/15 ,  B60W30/09 ,  B60W30/0956 ,  B60W60/0015 ,  G06F8/60 ,  G06F8/71 ,  G06F11/3476 ,  G06F11/3664 ,  G06F11/3688 ,  G06F11/3692 ,  G06F18/22 ,  G06F18/241 ,  G06F30/20 ,  G06V20/58 ,  G06F11/3013 ,  G06F30/27

摘要： Collision filtering for autonomous vehicle simulations is disclosed herein. A simulation system can be configured to identify a simulated collision involving a simulated autonomous vehicle and a simulated agent representing an obstacle with which the simulated autonomous vehicle may collide. For example, the simulated collision can be simulated based on logged data from a real-world autonomous vehicle. The simulation system can classify the simulated collision as unrealistic or realistic. For example, classification can involve considering a nature of the simulated agent (including, e.g., whether the simulated agent is a drivable obstacle), a nature of the collision, whether the collision is avoidable through an evasive maneuver, whether the collision is similar to a known false positive, and/or input from a human operator. The simulation system can filter the simulated collision from participating in a collision triage analysis in response to classifying the simulated collision as an unrealistic simulated collision.

公开(公告)号：US20210165932A1

公开(公告)日：2021-06-03

申请号：US17098609

申请日：2020-11-16

申请人： Nuro, Inc.

发明人： Varun Krish Mohan ,  Chuan Qiu

IPC分类号： G06F30/20 ,  G06K9/00 ,  G06K9/62 ,  G06F11/36 ,  G06F8/71 ,  G06F8/60 ,  B60W30/09 ,  B60W60/00 ,  B60W30/095

摘要： Collision filtering for autonomous vehicle simulations is disclosed herein. A simulation system can be configured to identify a simulated collision involving a simulated autonomous vehicle and a simulated agent representing an obstacle with which the simulated autonomous vehicle may collide. For example, the simulated collision can be simulated based on logged data from a real-world autonomous vehicle. The simulation system can classify the simulated collision as unrealistic or realistic. For example, classification can involve considering a nature of the simulated agent (including, e.g., whether the simulated agent is a drivable obstacle), a nature of the collision, whether the collision is avoidable through an evasive maneuver, whether the collision is similar to a known false positive, and/or input from a human operator. The simulation system can filter the simulated collision from participating in a collision triage analysis in response to classifying the simulated collision as an unrealistic simulated collision.