公开(公告)号：US20230150550A1

公开(公告)日：2023-05-18

申请号：US17988701

申请日：2022-11-16

Applicant: Waymo LLC

Inventor： Xinwei Shi ,  Tian Lan ,  Jonathan Chandler Stroud ,  Zhishuai Zhang ,  Junhua Mao ,  Jeonhyung Kang ,  Khaled Refaat ,  Jiachen Li

IPC: B60W60/00 ,  B60W50/00 ,  B60W40/04 ,  G06N3/04 ,  G06N3/08

CPC classification number: B60W60/00274 ,  B60W60/0015 ,  B60W50/0097 ,  B60W40/04 ,  G06N3/049 ,  G06N3/08 ,  B60W2554/4029 ,  B60W2554/4045 ,  B60W2554/4046 ,  B60W2554/408 ,  B60W2556/10

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent behavior prediction using keypoint data. One of the methods includes obtaining data characterizing a scene in an environment, the data comprising: (i) context data comprising data characterizing historical trajectories of a plurality of agents up to the current time point; and (ii) keypoint data for a target agent; processing the context data using a context data encoder neural network to generate a context embedding for the target agent; processing the keypoint data using a keypoint encoder neural network to generate a keypoint embedding for the target agent; generating a combined embedding for the target agent from the context embedding and the keypoint embedding; and processing the combined embedding using a decoder neural network to generate a behavior prediction output for the target agent that characterizes predicted behavior of the target agent after the current time point.

公开(公告)号：US20220405618A1

公开(公告)日：2022-12-22

申请号：US17354232

申请日：2021-06-22

Applicant: Waymo LLC

Inventor： Khaled Refaat ,  Yun Jia Guan ,  Jeonhyung Kang

IPC: G06N5/04 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating roadway crossing intent labels for training a machine learning model to perform roadway crossing intent predictions. One of the methods includes obtaining data identifying a training input, the training input including data characterizing an agent in an environment as of a given time, wherein the agent is located in a vicinity of a roadway in the environment at the given time. Future data characterizing (i) the agent, (ii) the environment or (iii) both over a future time period that is after the given time is obtained. From the future data, an intent label that indicates a likelihood that the agent intended to cross the roadway at the given time is determined. The training input is associated with the intent label in training data for training the machine learning model.

公开(公告)号：US20230062158A1

公开(公告)日：2023-03-02

申请号：US17902670

申请日：2022-09-02

Applicant: Waymo LLC

Inventor： Xinwei Shi ,  Junhua Mao ,  Khaled Refaat ,  Tian Lan ,  Jeonhyung Kang ,  Zhishuai Zhang ,  Jonathan Chandler Stroud

IPC: B60W60/00 ,  B60W40/04 ,  B60W50/00 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that determine yield behavior for an autonomous vehicle, and can include identifying an agent that is in a vicinity of an autonomous vehicle navigating through a scene at a current time point. Scene features can be obtained and can include features of (i) the agent and (ii) the autonomous vehicle. An input that can include the scene features can be processed using a first machine learning model that is configured to generate (i) a crossing intent prediction that includes a crossing intent score that represents a likelihood that the agent intends to cross a roadway in a future time window after the current time, and (ii) a crossing action prediction that includes a crossing action score that represents a likelihood that the agent will cross the roadway in the future time window after the current time.