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    GENERATING TRAINING DATA FOR MACHINE LEARNING BASED MODELS FOR AUTONOMOUS VEHICLES
    11.
    发明公开
    GENERATING TRAINING DATA FOR MACHINE LEARNING BASED MODELS FOR AUTONOMOUS VEHICLES 审中-公开

    公开(公告)号：US20230339504A1

    公开(公告)日：2023-10-26

    申请号：US17730048

    申请日：2022-04-26

    Applicant: Perceptive Automata, Inc.

    Inventor： Elon Gaffin-Cahn

    IPC: B60W40/04 ,  B60W60/00

    CPC classification number: B60W60/0011 ,  B60W40/04 ,  B60W2554/402 ,  B60W2554/4041 ,  B60W2556/10

    Abstract: A system receives information describing paths traversed by vehicles of a vehicle type, for example, a bicycle or a motorcycle. The system determines locations along the paths. For each location the system determines a measure of likelihood of encountering vehicles of the vehicle type in traffic at the location. The system selects a subset of locations based on the measure of likelihood and obtains sensor data captured at the subset of locations. The system uses the sensor data as training dataset for training a machine learning based model configured to receive input sensor data describing traffic and output a score used for navigation of autonomous vehicles. The machine learning model is provided to a vehicle, for example, an autonomous vehicle for navigation of the autonomous vehicle.

    Adaptive sampling of stimuli for training of machine learning based models for predicting hidden context of traffic entities for navigating autonomous vehicles
    15.
    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.

    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES
    16.
    发明申请
    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES 有权

    公开(公告)号：US20210182604A1

    公开(公告)日：2021-06-17

    申请号：US17190619

    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.

    Generating Training Datasets for Training Machine Learning Based Models for Predicting Behavior of Traffic Entities for Navigating Autonomous Vehicles
    17.
    发明申请
    Generating Training Datasets for Training Machine Learning Based Models for Predicting Behavior of Traffic Entities for Navigating Autonomous Vehicles 有权

    公开(公告)号：US20210133500A1

    公开(公告)日：2021-05-06

    申请号：US17081202

    申请日：2020-10-27

    Applicant: Perceptive Automata Inc.

    Inventor： Avery Wagner Faller

    IPC: G06K9/62 ,  G06K9/00 ,  G06N20/00 ,  B60W60/00 ,  B60W30/095

    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 the sampled video frames are presented to users to provide input on a traffic entity's state of mind. The system determines an attribute value that describes a statistical distribution of user responses for the traffic entity. If the attribute for a sampled video frame is within a threshold of the attribute of another video frame, the system interpolates attribute for a third video frame between the two sampled video frames. Otherwise, the system requests further user input for a video frame captured between the two sampled video frames. The interpolated and/or user based attributes are used to train a machine learning based model that predicts a hidden context of the traffic entity. The trained model is used for navigation of autonomous vehicles.

    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES
    19.
    发明申请
    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES 审中-公开

    公开(公告)号：US20190340465A1

    公开(公告)日：2019-11-07

    申请号：US16512560

    申请日：2019-07-16

    Applicant: Perceptive Automata, Inc.

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

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

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