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    Neural network based prediction of hidden context of traffic entities for autonomous vehicles
    22.
    发明授权
    Neural network based prediction of hidden context of traffic entities for autonomous vehicles 有权

    公开(公告)号：US11572083B2

    公开(公告)日：2023-02-07

    申请号：US16932680

    申请日：2020-07-17

    Applicant: Perceptive Automata, Inc.

    Inventor： Jacob Reinier Maat

    IPC: G06V10/50 ,  G06V20/58 ,  B60W60/00 ,  B60W40/02 ,  G06N3/08 ,  B60W40/09 ,  G05D1/02 ,  G06N3/04

    Abstract: An autonomous vehicle uses machine learning based models such as neural networks to predict hidden context attributes associated with traffic entities. The hidden context represents behavior of the traffic entities in the traffic. The machine learning based model is configured to receive a video frame as input and output likelihoods of receiving user responses having particular ordinal values. The system uses a loss function based on cumulative histogram of user responses corresponding to various ordinal values. The system identifies user responses that are unlikely to be valid user responses to generate training data for training the machine learning mode. The system identifies invalid user responses based on response time of the user responses.

    GROUND TRUTH BASED METRICS FOR EVALUATION OF MACHINE LEARNING BASED MODELS FOR PREDICTING ATTRIBUTES OF TRAFFIC ENTITIES FOR NAVIGATING AUTONOMOUS VEHICLES
    25.
    发明申请
    GROUND TRUTH BASED METRICS FOR EVALUATION OF MACHINE LEARNING BASED MODELS FOR PREDICTING ATTRIBUTES OF TRAFFIC ENTITIES FOR NAVIGATING AUTONOMOUS VEHICLES 有权

    公开(公告)号：US20210357662A1

    公开(公告)日：2021-11-18

    申请号：US17321297

    申请日：2021-05-14

    Applicant: Perceptive Automata, Inc.

    Inventor： Till S. Hartmann ,  Jeffrey D. Zaremba ,  Samuel English Anthony

    IPC: G06K9/00 ,  B60W60/00 ,  G06N3/08

    Abstract: A system uses a machine learning based model to determine attributes describing states of mind and behavior of traffic entities in video frames captured by an autonomous vehicle. The system classifies video frames according to traffic scenarios depicted, where each scenario is associated with a filter based on vehicle attributes, traffic attributes, and road attributes. The system identifies a set of video frames associated with ground truth scenarios for validating the accuracy of the machine learning based model and predicts attributes of traffic entities in the video frames. The system analyzes video frames captured after the set of video frames to determine actual attributes of the traffic entities. Based on a comparison of the predicted attributes and actual attributes, the system determines a likelihood of the machine learning based model making accurate predictions and uses the likelihood to generate a navigation action table for controlling the autonomous vehicle.

    NEURAL NETWORKS FOR NAVIGATION OF AUTONOMOUS VEHICLES BASED UPON PREDICTED HUMAN INTENTS
    28.
    发明申请
    NEURAL NETWORKS FOR NAVIGATION OF AUTONOMOUS VEHICLES BASED UPON PREDICTED HUMAN INTENTS 有权

    公开(公告)号：US20210114627A1

    公开(公告)日：2021-04-22

    申请号：US17071115

    申请日：2020-10-15

    Applicant: Perceptive Automata, Inc.

    Inventor： Mel McCurrie

    IPC: B60W60/00 ,  G06N3/04 ,  G06K9/00

    Abstract: A system uses neural networks to determine intents of traffic entities (e.g., pedestrians, bicycles, vehicles) in an environment surrounding a vehicle (e.g., an autonomous vehicle) and generates commands to control the vehicle based on the determined intents. The system receives images of the environment captured by sensors on the vehicle, and processes the images using neural network models to determine overall intents or predicted actions of the one or more traffic entities within the images. The system generates commands to control the vehicle based on the determined overall intents of the traffic entities.

    SYSTEM AND METHOD OF PREDICTING HUMAN INTERACTION WITH VEHICLES
    29.
    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.

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