AUGMENTED DRIVING RELATED VIRTUAL FORCE FIELDS

    公开(公告)号:US20240083463A1

    公开(公告)日:2024-03-14

    申请号:US18510550

    申请日:2023-11-15

    CPC classification number: B60W60/0016 G06V20/58 B60W60/0013 B60W2554/80

    Abstract: A method for augmented driving related virtual fields, the method includes (a) obtaining object information regarding one or more objects located within an environment of a vehicle; wherein the object information comprises spatial and temporal information extracted from a set of sensed information units (SIUs) of the environment of the vehicle that were acquired at different points in time; and (b) determining, by a processing circuit, and based on the object information, one or more virtual fields of the one or more objects, wherein the determining of the one or more virtual fields is based on a virtual physical model, wherein the one or more virtual fields represent a potential impact of the one or more objects on a behavior of the vehicle, wherein the virtual physical model is built based on one or more physical laws.

    TRAINING AND TESTING A MACHINE LEARNING PROCESS

    公开(公告)号:US20240083431A1

    公开(公告)日:2024-03-14

    申请号:US18510591

    申请日:2023-11-15

    CPC classification number: B60W30/165 G06F11/3688

    Abstract: A method for training and testing a machine learning process, the method includes (a) learning virtual fields based on simulations of behaviors of a vehicle when faced with situations involving objects within environments of the vehicle, the virtual fields represent potential impacts of objects on the behaviors of the vehicle, wherein the learning is based on a virtual physical mode; (b) training the machine learning process to generate the virtual fields by applying a training process that uses outcomes of the simulations to provide a trained machine learning process; and (c) testing the trained machine learning process by feeding the trained machine learning process with other situations to provide test results.

    Virtual fields driving related operations

    公开(公告)号:US12291223B2

    公开(公告)日:2025-05-06

    申请号:US18350684

    申请日:2023-07-11

    Abstract: A method for communicating with a driver of a vehicle, the method includes (i) obtaining object information regarding one or more objects located within an environment of the vehicle; (ii) analyzing the object information; (iii) determining, by using one or more neural network (NNs), and based on the object information, a virtual force associated with a physical model and representing an impact of the one or more objects on a behavior of the vehicle; and (iv) determining, based on at least the virtual force, a force feedback for use in providing a physical restraining force to be applied in association with a driver action made by the driver using the vehicle.

    DRIVING POLICY VISUALIZATION
    5.
    发明公开

    公开(公告)号:US20240132093A1

    公开(公告)日:2024-04-25

    申请号:US18400823

    申请日:2023-12-29

    CPC classification number: B60W50/14 B60W2050/146

    Abstract: A method for driving policy visualization, the method includes (i) receiving, by a processing circuit, perception information that comprises environmental information about an environment of a vehicle and kinematic information regarding a movement of the vehicle; (ii) receiving, by the processing circuit, a multidimensional virtual force field representation of a driving policy applicable to the vehicle; (iii) reducing a dimension of the multidimensional virtual force field representation, based on the received perception information, to produce a reduced dimensional virtual force field representation that conforms with a driving of the vehicle; and (iv) dynamically visualizing, by applying the reduced dimensional virtual force field representation, the driving policy in the driving of the vehicle.

    PERCEPTUAL FIELDS FOR AUTONOMOUS DRIVING

    公开(公告)号:US20230064387A1

    公开(公告)日:2023-03-02

    申请号:US17823069

    申请日:2022-08-29

    Abstract: A method for perception fields driving related operations, the method may include (i) obtaining object information regarding one or more objects located within an environment of a vehicle; (ii) determining, using one or more neural network (NNs), one or more virtual forces that are applied on the vehicle, wherein the one or more virtual forces represent one or more impacts of the one or more objects on a behavior of the vehicle; wherein the one or more virtual forces belong to a virtual physical model; and (iii) performing one or more driving related operations of the vehicle based on the one or more virtual forces.

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