公开(公告)号：US20210253128A1

公开(公告)日：2021-08-19

申请号：US17178464

申请日：2021-02-18

Applicant: NVIDIA Corporation

Inventor： David Nister ,  Yizhou Wang ,  Julia Ng ,  Rotem Aviv ,  Seungho Lee ,  Joshua John Bialkowski ,  Hon Leung Lee ,  Hermes Lanker ,  Raul Correal Tezanos ,  Zhenyi Zhang ,  Nikolai Smolyanskiy ,  Alexey Kamenev ,  Ollin Boer Bohan ,  Anton Vorontsov ,  Miguel Sainz Serra ,  Birgit Henke

IPC: B60W60/00 ,  G06N3/08 ,  G05D1/02 ,  B60W50/00

Abstract: Embodiments of the present disclosure relate to behavior planning for autonomous vehicles. The technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. The various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. This scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. In examples, the trajectory with the best combined score may be selected for implementation. As such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.

公开(公告)号：US20240239374A1

公开(公告)日：2024-07-18

申请号：US18620096

申请日：2024-03-28

Applicant: NVIDIA Corporation

Inventor： David Nister ,  Yizhou Wang ,  Julia Ng ,  Rotem Aviv ,  Seungho Lee ,  Joshua John Bialkowski ,  Hon Leung Lee ,  Hermes Lanker ,  Raul Correal Tezanos ,  Zhenyi Zhang ,  Nikolai Smolyanskiy ,  Alexey Kamenev ,  Ollin Boer Bohan ,  Anton Vorontsov ,  Miguel Sainz Serra ,  Birgit Henke

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

CPC classification number: B60W60/0011 ,  B60W50/0097 ,  G06N3/08

Abstract: Embodiments of the present disclosure relate to behavior planning for autonomous vehicles. The technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. The various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. This scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. In examples, the trajectory with the best combined score may be selected for implementation. As such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.

公开(公告)号：US11981349B2

公开(公告)日：2024-05-14

申请号：US17178464

申请日：2021-02-18

Applicant: NVIDIA Corporation

Inventor： David Nister ,  Yizhou Wang ,  Julia Ng ,  Rotem Aviv ,  Seungho Lee ,  Joshua John Bialkowski ,  Hon Leung Lee ,  Hermes Lanker ,  Raul Correal Tezanos ,  Zhenyi Zhang ,  Nikolai Smolyanskiy ,  Alexey Kamenev ,  Ollin Boer Bohan ,  Anton Vorontsov ,  Miguel Sainz Serra ,  Birgit Henke

IPC: B60W60/00 ,  B60W50/00 ,  G05D1/00 ,  G06N3/08

CPC classification number: B60W60/0011 ,  B60W50/0097 ,  G05D1/0212 ,  G06N3/08

Abstract: Embodiments of the present disclosure relate to behavior planning for autonomous vehicles. The technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. The various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. This scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. In examples, the trajectory with the best combined score may be selected for implementation. As such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.

公开(公告)号：US11878682B2

公开(公告)日：2024-01-23

申请号：US16895250

申请日：2020-06-08

Applicant: NVIDIA Corporation

Inventor： Seungho Lee ,  Michael Watson

IPC: B60W30/09 ,  G08G1/01 ,  G08G1/16 ,  G06N5/022 ,  G06N3/08

CPC classification number: B60W30/09 ,  G06N5/022 ,  G08G1/0112 ,  G08G1/0133 ,  G08G1/0145 ,  G08G1/166 ,  G08G1/167 ,  B60W2300/145 ,  G06N3/08

Abstract: In various examples, systems and methods are disclosed for generating and/or analyzing candidate paths for a multi-body vehicle—e.g., a tractor trailer truck—based on obstacle avoidance considerations and using an uncertainty representation for the vehicle. The uncertainty representation may correspond to a trailer portion of the multi-body vehicle to account for the variations in rotation of the trailer with respect to the tractor. As such, the uncertainty representation may be indicative of a probability that the trailer of the vehicle occupies locations and/or points in world space. This probability—combined with the probability of locations of actors in the environment—may be used to generate candidate paths that satisfy various constraints—e.g., a minimum stochastic distance—between the vehicle and the actor.

公开(公告)号：US20210380099A1

公开(公告)日：2021-12-09

申请号：US16895250

申请日：2020-06-08

Applicant: NVIDIA Corporation

Inventor： Seungho Lee ,  Michael Watson

IPC: B60W30/09 ,  G08G1/01 ,  G08G1/16 ,  G06N5/02

Abstract: In various examples, systems and methods are disclosed for generating and/or analyzing candidate paths for a multi-body vehicle—e.g., a tractor trailer truck—based on obstacle avoidance considerations and using an uncertainty representation for the vehicle. The uncertainty representation may correspond to a trailer portion of the multi-body vehicle to account for the variations in rotation of the trailer with respect to the tractor. As such, the uncertainty representation may be indicative of a probability that the trailer of the vehicle occupies locations and/or points in world space. This probability—combined with the probability of locations of actors in the environment—may be used to generate candidate paths that satisfy various constraints—e.g., a minimum stochastic distance—between the vehicle and the actor.