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    Determining Ego Motion
    5.
    发明公开
    Determining Ego Motion 审中-公开

    公开(公告)号：US20240019566A1

    公开(公告)日：2024-01-18

    申请号：US18353661

    申请日：2023-07-17

    Applicant: Aptiv Technologies Limited

    Inventor： Igor Kossaczky ,  Mirko Meuter

    IPC: G01S13/60 ,  G01S13/89 ,  G01S13/931 ,  G01S7/41

    CPC classification number: G01S13/60 ,  G01S13/89 ,  G01S13/931 ,  G01S7/417

    Abstract: A computer implemented method to determine ego motion of a vehicle, the vehicle having at least one radar emitter with a plurality of reception antennae, the method including the operations of acquiring, from the reception antennae, different frames of radar data of the vehicle surrounding environment, each frame being acquired at a different time; deriving from the radar data of each different frame, an environment map of the vehicle surrounding environment; and deriving the ego motion of the vehicle by: merging environment maps from at least two different frames into one accumulated map, computing, from the accumulated map, a motion vector for each pixel of the accumulated map, and extracting, from the accumulated map, a mask map including a tensor mapping a weight for each pixel of the accumulated map.

    Image based lane marking classification
    6.
    发明授权
    Image based lane marking classification 有权

    公开(公告)号：US10943131B2

    公开(公告)日：2021-03-09

    申请号：US16409035

    申请日：2019-05-10

    Applicant: Aptiv Technologies Limited

    Inventor： Yu Su ,  Andre Paus ,  Kun Zhao ,  Mirko Meuter ,  Christian Nunn

    IPC: G06K9/00 ,  B60W30/12

    Abstract: An image processing method includes: determining a candidate track in an image of a road, wherein the candidate track is modelled as a parameterized line or curve corresponding to a candidate lane marking in the image of a road; dividing the candidate track into a plurality of cells, each cell corresponding to a segment of the candidate track; determining at least one marklet for a plurality of said cells, wherein each marklet of a cell corresponds to a line or curve connecting left and right edges of the candidate lane marking; determining at least one local feature of each of said plurality of cells based on characteristics of said marklets; determining at least one global feature of the candidate track by aggregating the local features of the plurality of cells; and determining if the candidate lane marking represents a lane marking based on the at least one global feature.

    Methods and Systems for Controlling a Vehicle
    8.
    发明申请
    Methods and Systems for Controlling a Vehicle 有权

    公开(公告)号：US20230067751A1

    公开(公告)日：2023-03-02

    申请号：US17820830

    申请日：2022-08-18

    Applicant: Aptiv Technologies Limited

    Inventor： Sebastian Yousef ,  Christian Prediger ,  Thorsten Rosenthal ,  Mirko Meuter

    IPC: B60W30/18

    Abstract: The present disclosure describes a computer-implemented method for controlling a vehicle. In aspects, the computer-implemented method includes acquiring sensor data from a sensor, determining first processed data related to a first area around the vehicle based on the sensor data using a machine-learning method, and determining second processed data related to a second area around the vehicle based on the sensor data using a conventional method. The second area may include a subarea of the first area. In addition, the computer-implemented method includes controlling the vehicle based on the first processed data and the second processed data.

    Motion Compensation and Refinement in Recurrent Neural Networks
    9.
    发明申请
    Motion Compensation and Refinement in Recurrent Neural Networks 有权

    公开(公告)号：US20220269921A1

    公开(公告)日：2022-08-25

    申请号：US17649791

    申请日：2022-02-02

    Applicant: Aptiv Technologies Limited

    Inventor： Igor Kossaczky ,  Sven Labusch ,  Mirko Meuter

    IPC: G06N3/04 ,  G06V20/58 ,  G06V10/82 ,  G07C5/08

    Abstract: Provided is a method and system for tracking a motion of information in a spatial environment of a vehicle. Sensor-based data regarding the spatial environment is acquired for a plurality of timesteps, the sensor-based data defining the information in spatially resolved cells. For each of the timesteps, the sensor-based data is input into a recurrent neural network, RNN, having one or more internal memory states. For each of the timesteps, the internal states of the RNN are transformed by using a motion map describing a speed and/or a direction of motion of the information of the spatially resolved cells individually. For each of the plurality of timesteps, the transformed internal states are used in a processing of the RNN to track the motion of the information in the environment of the moving vehicle.

    Object Detection with Multiple Ranges and Resolutions
    10.
    发明申请
    Object Detection with Multiple Ranges and Resolutions 有权

    公开(公告)号：US20220244383A1

    公开(公告)日：2022-08-04

    申请号：US17649666

    申请日：2022-02-01

    Applicant: Aptiv Technologies Limited

    Inventor： Yu Su ,  Mirko Meuter

    IPC: G01S17/42 ,  G06N3/08 ,  G01S17/89 ,  G01S17/86

    Abstract: Provided is a method for object detection in a surrounding of a vehicle using a deep neural network, comprising: inputting a first set of sensor-based data for a first Cartesian grid having a first spatial dimension and a first spatial resolution into a first branch of the deep neural network; inputting a second set of sensor-based data for a second Cartesian grid having a second spatial dimension and a second spatial resolution into a second branch of the deep neural network; providing an interaction between the first branch of the deep neural network and the second branch of the deep neural network at an intermediate stage of the deep neural network; and fusing a first output of the first branch of the deep neural network and a second output of the second branch of the deep neural network to detect the object in the surrounding of the vehicle.

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