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    Event classification and object tracking
    11.
    发明授权
    Event classification and object tracking 有权

    公开(公告)号：US10520904B2

    公开(公告)日：2019-12-31

    申请号：US15419931

    申请日：2017-01-30

    Applicant: Mentor Graphics Corporation

    Inventor： Ljubo Mercep ,  Matthias Pollach

    IPC: G05B17/02 ,  G05D1/00 ,  G05D1/02 ,  G06F16/29 ,  G01C21/34 ,  G01C21/36 ,  G06F17/50 ,  G01C21/28 ,  G01S13/93 ,  G01S15/93 ,  G01S17/93 ,  G08G1/16 ,  G01S13/86 ,  G01S7/48 ,  G06K9/00 ,  G06F16/583 ,  G01S13/72

    Abstract: This application discloses a computing system to implement object tracking in an assisted or automated driving system of a vehicle. The computing system can assign a pre-classification to a detection event in an environmental model, update the environmental model with new sensor measurements and corresponding detection events over time, and track the detection event in the updated environmental model. The computing system can track the detection event by predicting a future state of the detection event with a state change model selected based on the assigned pre-classification, comparing the predicted future state to an actual future state of the detection event in an update to the environmental model, and determining the detection event corresponds to an object proximate to the vehicle based on the comparison. A control system for the vehicle can control operation of the vehicle based, at least in part, on the tracked detection event.

    LOW-LEVEL SENSOR FUSION
    14.
    发明申请
    LOW-LEVEL SENSOR FUSION 审中-公开

    公开(公告)号：US20180067489A1

    公开(公告)日：2018-03-08

    申请号：US15287537

    申请日：2016-10-06

    Applicant: Mentor Graphics Corporation

    Inventor： Rainer Oder ,  Andreas Erich Geiger ,  Ljubo Mercep ,  Matthias Pollach

    IPC: G05D1/00 ,  G05D1/02

    CPC classification number: G05D1/0088 ,  G05D1/0231 ,  G05D1/0255 ,  G05D1/0257 ,  G06K9/00791

    Abstract: This application discloses a computing system to implement low-level sensor fusion in an assisted or automated driving system of a vehicle. The low-level sensor fusion can include receiving raw measurement data from sensors in the vehicle and temporally aligning the raw measurement data based on a time of capture. The low-level sensor fusion can include spatially aligning measurement coordinate fields of the sensors into an environmental coordinate field based, at least in part, on where the sensors are mounted in the vehicle, and then populating the environmental coordinate field with raw measurement data captured by the sensors based on the spatial alignment of the measurement coordinate fields to the environmental coordinate field. The low-level sensor fusion can detect at least one detection event or object based, at least in part, on the raw measurement data from multiple sensors as populated in the environmental coordinate field.

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