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    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES
    2.
    发明申请
    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES 有权

    公开(公告)号：US20210182605A1

    公开(公告)日：2021-06-17

    申请号：US17190631

    申请日：2021-03-03

    Applicant: Perceptive Automata, Inc.

    Inventor： Samuel English Anthony ,  Kshitij Misra ,  Avery Wagner Faller

    IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06K9/00 ,  G08G1/16 ,  G08G1/04 ,  G05D1/00 ,  B60W30/00

    Abstract: Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.

    Adaptive Sampling of Stimuli for Training of Machine Learning Based Models for Predicting Hidden Context of Traffic Entities For Navigating Autonomous Vehicles
    5.
    发明申请
    Adaptive Sampling of Stimuli for Training of Machine Learning Based Models for Predicting Hidden Context of Traffic Entities For Navigating Autonomous Vehicles 有权

    公开(公告)号：US20210133497A1

    公开(公告)日：2021-05-06

    申请号：US17081211

    申请日：2020-10-27

    Applicant: Perceptive Automata Inc.

    Inventor： Avery Wagner Faller

    IPC: G06K9/62 ,  G08G1/01 ,  G06K9/00 ,  G06N20/00 ,  G05D1/02

    Abstract: A vehicle collects video data of an environment surrounding the vehicle including traffic entities, e.g., pedestrians, bicyclists, or other vehicles. The captured video data is sampled and presented to users to provide input on a traffic entity's state of mind. The user responses on the captured video data is used to generate a training dataset. A machine learning based model configured to predict a traffic entity's state of mind is trained with the training dataset. The system determines input video frames and associated dimension attributes for which the model performs poorly. The dimension attributes characterize stimuli and/or an environment shown in the input video frames. The system generates a second training dataset based on video frames that have the dimension attributes for which the model performed poorly. The model is retrained using the second training dataset and provided to an autonomous vehicle to assist with navigation in traffic.

    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES
    8.
    发明申请
    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES 审中-公开

    公开(公告)号：US20200293822A1

    公开(公告)日：2020-09-17

    申请号：US16828823

    申请日：2020-03-24

    Applicant: Perceptive Automata Inc.

    Inventor： Samuel English Anthony ,  Kshitij Misra ,  Avery Wagner Faller

    IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06K9/00 ,  G08G1/16 ,  G08G1/04 ,  G05D1/00 ,  B60W30/00

    Abstract: Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.

    Adaptive sampling of stimuli for training of machine learning based models for predicting hidden context of traffic entities for navigating autonomous vehicles
    10.
    发明授权
    Adaptive sampling of stimuli for training of machine learning based models for predicting hidden context of traffic entities for navigating autonomous vehicles 有权

    公开(公告)号：US11615266B2

    公开(公告)日：2023-03-28

    申请号：US17081211

    申请日：2020-10-27

    Applicant: Perceptive Automata Inc.

    Inventor： Avery Wagner Faller

    IPC: G06K9/62 ,  G08G1/01 ,  G06N20/00 ,  G05D1/02 ,  G06V20/56 ,  G06V40/10 ,  G05D1/00

    Abstract: A vehicle collects video data of an environment surrounding the vehicle including traffic entities, e.g., pedestrians, bicyclists, or other vehicles. The captured video data is sampled and presented to users to provide input on a traffic entity's state of mind. The user responses on the captured video data is used to generate a training dataset. A machine learning based model configured to predict a traffic entity's state of mind is trained with the training dataset. The system determines input video frames and associated dimension attributes for which the model performs poorly. The dimension attributes characterize stimuli and/or an environment shown in the input video frames. The system generates a second training dataset based on video frames that have the dimension attributes for which the model performed poorly. The model is retrained using the second training dataset and provided to an autonomous vehicle to assist with navigation in traffic.

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