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    DETECTING TRAFFIC SIGNALING STATES WITH NEURAL NETWORKS
    2.
    发明申请
    DETECTING TRAFFIC SIGNALING STATES WITH NEURAL NETWORKS 有权

    公开(公告)号：US20220335731A1

    公开(公告)日：2022-10-20

    申请号：US17738339

    申请日：2022-05-06

    Applicant: Waymo LLC

    Inventor： Edward Hsiao ,  Yu Ouyang ,  Maoqing Yao

    IPC: G06V20/58 ,  G06T7/73 ,  G06V10/56 ,  G06V20/56 ,  G06N3/04

    Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.

    DETECTING TRAFFIC SIGNALING STATES WITH NEURAL NETWORKS
    3.
    发明申请
    DETECTING TRAFFIC SIGNALING STATES WITH NEURAL NETWORKS 有权

    公开(公告)号：US20220027645A1

    公开(公告)日：2022-01-27

    申请号：US16936739

    申请日：2020-07-23

    Applicant: Waymo LLC

    Inventor： Edward Hsiao ,  Yu Ouyang ,  Maoqing Yao

    IPC: G06K9/00 ,  G06K9/46 ,  G06T7/73 ,  G06N3/04

    Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.

    Detecting traffic signaling states with neural networks
    4.
    发明授权
    Detecting traffic signaling states with neural networks 有权

    公开(公告)号：US11328519B2

    公开(公告)日：2022-05-10

    申请号：US16936739

    申请日：2020-07-23

    Applicant: Waymo LLC

    Inventor： Edward Hsiao ,  Yu Ouyang ,  Maoqing Yao

    IPC: G06K9/00 ,  G06V20/58 ,  G06N3/04 ,  G06T7/73 ,  G06V10/56 ,  G06V20/56

    Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.

    TRAJECTORY PREDICTION FROM MULTI-SENSOR FUSION
    5.
    发明申请
    TRAJECTORY PREDICTION FROM MULTI-SENSOR FUSION 有权

    公开(公告)号：US20250162618A1

    公开(公告)日：2025-05-22

    申请号：US18517750

    申请日：2023-11-22

    Applicant: Waymo LLC

    Inventor： Yu Ouyang ,  Daniel Ho ,  Alper Ayvaci ,  Tencia Lee ,  Bayram Safa Cicek

    IPC: B60W60/00 ,  B60W50/00

    Abstract: Methods and systems for predicting a trajectory an autonomous vehicle (AV) are disclosed. A method includes generating, based on sensor data from a sensing system of the AV, one or more embeddings, generating, using a machine learning model (MLM) and the one or more embeddings, one or more predicted future trajectories for the AV, and causing, using the one or more predicted future trajectories, a planning system of the AV to generate an update to a current trajectory of the AV.

    LONG RANGE DISTANCE ESTIMATION USING REFERENCE OBJECTS
    9.
    发明申请
    LONG RANGE DISTANCE ESTIMATION USING REFERENCE OBJECTS 有权

    公开(公告)号：US20220156972A1

    公开(公告)日：2022-05-19

    申请号：US17526682

    申请日：2021-11-15

    Applicant: Waymo LLC

    Inventor： Yu-Han Chen ,  Maya Kabkab ,  Ruichi Yu ,  Yingwei Li ,  Hang Zhao ,  Yu Ouyang

    IPC: G06T7/73 ,  G06N3/04 ,  G01S17/89

    Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for generating a distance estimate for a target object that is depicted in an image of a scene in an environment. The system obtains data specifying (i) a target portion of the image that depicts the target object detected in the image, and (ii) one or more reference portions of the image that each depict a respective reference object detected in the image. The system further obtains, for each of the one or more reference objects, a respective distance measurement for the reference object that is a measurement of a distance from the reference object to a specified location in the environment. The system processes the obtained data to generate a distance estimate for the target object that is an estimate of a distance from the target object to the specified location in the environment.

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