IDENTIFYING AND QUANTIFYING CONGESTION WITHIN A TRAFFIC STREAM

    公开(公告)号:US20240304083A1

    公开(公告)日:2024-09-12

    申请号:US18179681

    申请日:2023-03-07

    CPC classification number: G08G1/0145 G08G1/0133 G08G1/096725 G08G1/096733

    Abstract: A system and method of identifying and quantifying congestion within a traffic stream including obtaining telemetric data from a plurality of vehicles traveling within a plurality of normalized road segments, determining a property of each normalized road segment based on the telemetric data and a road profile for each road segment, determining a disruption score indicative of a level of disruption in a traffic flow within each road segment, mapping the road segments within a two-dimensional spatial-temporal grid of cells, wherein each cell represents a normalized road segment at a specified time, for each cell, determining if the traffic flow is congested, identifying a congested traffic stream including a plurality of contiguous cells that have congested traffic flow, quantifying the congested traffic stream, and providing an output signal.

    OBJECT BLURRING ON COMPRESSED VIDEOS
    184.
    发明公开

    公开(公告)号:US20240282008A1

    公开(公告)日:2024-08-22

    申请号:US18170060

    申请日:2023-02-16

    CPC classification number: G06T9/00 G06T5/70 G06V10/764 G06V2201/07

    Abstract: A system for object blurring in compressed videos includes sensors, human machine interfaces (HMIs), and control modules. Each control module has a processor, memory, and input/output (I/O) ports. The control modules communicate with the sensors and the HMIs via the I/O ports. The memory stores control logic that is executed by the processor. The control logic receives raw image data from the sensors, encodes the raw image data into compressed image data and stores the compressed image data in memory. The control logic parses and partially decodes the compressed image data to access raw independent video frames and performs post-processing algorithms on the raw independent video frames to generate post-processed independent video frames. The post-processed independent video frames are encoded and replace raw independent video frames in the compressed image data. The control logic transmits an output including the encoded post-processed independent and dependent video frames to the HMI.

    WIRELESS CAMERA STREAMING WITH TEMPLATE MATCHING

    公开(公告)号:US20240233320A1

    公开(公告)日:2024-07-11

    申请号:US18150387

    申请日:2023-01-05

    CPC classification number: G06V10/751 H04N19/146 H04N19/517

    Abstract: A method for video streaming includes receiving an input image from a camera. The input image includes a plurality of input grid areas. The method further includes receiving a template image. The method further includes comparing the matching error with a template-matching error threshold to determine whether the matching error is equal to or greater than the template-matching error threshold in order to identify unmatched grid areas of the input image. The plurality of input grid areas includes the unmatched grid areas and matched grid areas. The matching error of the matched grid areas is not equal to or greater than the template-matching error threshold. The method further includes transmitting the unmatched grid areas of the input image and identification information of the matched grid areas to the vehicle, thereby minimizing bandwidth consumption used during video streaming.

    SYSTEM AND METHOD FOR DIAGNOSING SENSOR PERFORMANCE OF AN ULTRA WIDE BAND SENSOR LOCALIZATION

    公开(公告)号:US20240151805A1

    公开(公告)日:2024-05-09

    申请号:US18049911

    申请日:2022-10-26

    CPC classification number: G01S5/021 G01S5/10 H04B1/7163

    Abstract: Systems and methods of diagnosing sensor performance of an ultra wide band (UWB) sensor localization for a vehicle are provided. The method comprises receiving sensor signals from at least four UWB anchors and a UWB tag for a time period. The sensor signals represent anchor coordinates and real-time distances between the tag and each anchor. The method comprises aligning the sensor signals to define aligned data. The method comprises calculating a predicted location of the UWB tag based on the aligned data and a least square of error to define a first constructed matrix and a second constructed matrix. The method comprises determining a local error of each of the at least four UWB anchors based on the least square of error and comparing each local error with an error threshold to define a first threshold high. The method comprises determining an erratic anchor based on the first threshold high.

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