PREDICTING 5G USER PLANE USING CONTROL PLANE FEATURES AND GRANGER CAUSALITY FOR FEATURE SELECTION

    公开(公告)号:US20250142359A1

    公开(公告)日:2025-05-01

    申请号:US18494189

    申请日:2023-10-25

    Abstract: A system for predicting a user plane using control plane features and Granger causality includes a host device a cloud computing server and controllers. The controllers execute control logic including a prediction application (PA) that obtains sensor data from the sensors, sends control and user plane data to infrastructure, and to the cloud computing servers, and accesses prior knowledge data stored within memory of the cloud computing servers. Additional control logic performs a Granger causality test on the user and control plane data, and utilizes a prediction model to generate a prediction from fused user and control plane data. A prediction verifier is applied to the prediction from the prediction model, and the PA enables the host device to make reliable predictions that allow the host device to adapt to dynamic wireless communications network conditions even when a best possible model is not fully trained.

    GUIDED TRAINING DATA COLLECTION FOR MACHINE LEARNING

    公开(公告)号:US20240378487A1

    公开(公告)日:2024-11-14

    申请号:US18313636

    申请日:2023-05-08

    Abstract: A method for training a machine learning algorithm includes performing at least one exploratory training session of the machine learning algorithm using an input data set. The input data set includes a first plurality of input data samples. The method further includes dividing the input data set into a plurality of input data categories. The method further includes determining a regression curve equation for each of the plurality of input data categories based at least in part on the at least one exploratory training session. The method further includes collecting a second plurality of input data samples based at least in part on the regression curve equation for each of the plurality of input data categories. The method further includes training the machine learning algorithm using the second plurality of input data samples and the input data set.

    INFRASTRUCTURE-SUPPORTED PERCEPTION SYSTEM FOR CONNECTED VEHICLE APPLICATIONS

    公开(公告)号:US20240338793A1

    公开(公告)日:2024-10-10

    申请号:US18297870

    申请日:2023-04-10

    Abstract: An infrastructure-supported perception system for connected vehicle applications includes one or more infrastructure perception sensors that capture perception data having a reduced resolution and a reduced frame rate. The reduced resolution includes a reduced number of pixels for a given frame when compared to a standard resolution and the reduced frame rate captures data at a lower rate when compared to a standard frame rate. The infrastructure-supported perception system includes one or more controllers that are part of a connected vehicle. The controllers of the connected vehicle are in wireless communication with the one or more infrastructure perception sensors and one or more servers, and the one or more servers are in wireless communication with the one or more infrastructure perception sensors. The controllers receive dynamic information regarding one or more detected objects in an environment surrounding the connected vehicle from the one or more servers.

    VEHICLE VIDEO RECORDING FRAMEWORK
    6.
    发明公开

    公开(公告)号:US20240282114A1

    公开(公告)日:2024-08-22

    申请号:US18170033

    申请日:2023-02-16

    CPC classification number: G06V20/56 G06V10/25 G06V20/41 G06V20/44

    Abstract: A system for processing a plurality of video recordings for a vehicle includes a camera system including a camera buffer. The system also includes a video storage device. The system also includes a vehicle communication system configured to communicate with a remote server. The system also includes a vehicle controller. The vehicle controller is programmed to capture one of the plurality of video recordings using the camera system. The one of the plurality of video recordings is stored to the camera buffer. The vehicle controller is also programmed to generate at least one event video file based on the one of the plurality of video recordings and save the at least one event video file to the video storage device. The vehicle controller is also programmed to upload the at least one event video file from the video storage device to the remote server using the vehicle communication system.

    HYBRID POSITIONING SYSTEM FOR DETERMINING A PRECISE POSITION OF A VEHICLE

    公开(公告)号:US20240272266A1

    公开(公告)日:2024-08-15

    申请号:US18168154

    申请日:2023-02-13

    CPC classification number: G01S5/0268 G01S5/0284 G01S5/04

    Abstract: A hybrid positioning system for a vehicle includes one or more controllers in wireless communication with a plurality of surrounding vehicles located in an environment surrounding the vehicle and a cellular software defined network including an edge positioning function. The one or more controllers execute instructions to receive, from the plurality of surrounding vehicles, relative position measurements that are each indicative of a position of one of the plurality of surrounding vehicles relative to the vehicle, wherein the relative position measurements are received by the one or more controllers in real-time. The one or more controllers receive a precise global position of the vehicle and the plurality of surrounding vehicles from the edge positioning function of the cellular software defined network, and fuse together the relative position measurements and the precise global position of the vehicle to determine a precise position of the vehicle.

    Filtering and aggregating detection points of a radar point cloud for an autonomous vehicle

    公开(公告)号:US11977149B2

    公开(公告)日:2024-05-07

    申请号:US17511968

    申请日:2021-10-27

    CPC classification number: G01S13/89 B60W60/001 G01S7/298 G01S7/40 B60W2420/408

    Abstract: A scan aggregator and filter for an autonomous vehicle includes a plurality of radar sensors, where each radar sensor performs a plurality of individual scans of a surrounding environment to obtain data in the form of a radar point cloud including a plurality of detection points. The scan aggregator and filter also includes an automated driving controller in electronic communication with the plurality of radar sensors. The automated driving controller is instructed to filter each of the individual scans to define a spatial region of interest and to remove the detection points of the radar point cloud that represent moving objects based on a first outlier-robust model estimation algorithm. The automated driving controller aggregates a predefined number of individual scans together based on a motion compensated aggregation technique to create an aggregated data scan and applies a plurality of density-based clustering algorithms to filter the aggregated data scan.

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