公开(公告)号：US11842546B2

公开(公告)日：2023-12-12

申请号：US17319570

申请日：2021-05-13

Applicant: GM Global Technology Operations LLC

Inventor： Keren Rotker ,  Max Bluvstein ,  Bat El Shlomo

IPC: G06V20/58 ,  B60W60/00 ,  G06N3/08 ,  G06F18/25

CPC classification number: G06V20/58 ,  B60W60/001 ,  G06F18/25 ,  G06N3/08 ,  B60W2420/42 ,  B60W2554/4049

Abstract: A system in a vehicle includes a first sensor to obtain first sensor data from a first field of view and provide a first top-view feature representation. The system also includes a second sensor to obtain second sensor data from a second field of view with an overlap with the first field of view and provide a second top-view feature representation. Processing circuitry implements a neural network and provides a top-view stixel representation based on the first top-view feature representation and the second top-view feature representation. The top-view three-dimensional stixel representation is used to control an operation of the vehicle.

公开(公告)号：US11613272B2

公开(公告)日：2023-03-28

申请号：US17024277

申请日：2020-09-17

Applicant: GM Global Technology Operations LLC

Inventor： Alon Raveh ,  Shaul Oron ,  Bat El Shlomo

IPC: B60W60/00 ,  G06T7/73 ,  G06T7/246 ,  B60W40/06 ,  B60W30/12 ,  G01C21/00 ,  G06V20/56

Abstract: Systems and methods involve obtaining observation points of a lane line using one or more sensors of a vehicle. Each observation point indicates a location of a point on the lane line. A method includes obtaining uncertainty values, each uncertainty value corresponding with one of the observation points. A lane model is generated or updated using the observation points. The lane model indicates a path of the lane line. An uncertainty model is generated or updated using the uncertainty values corresponding with the observation points. The uncertainty model indicates uncertainty associated with each portion of the lane model.

公开(公告)号：US20220198203A1

公开(公告)日：2022-06-23

申请号：US17125379

申请日：2020-12-17

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Erez Ben Yaacov ,  Elad Plaut ,  Bat El Shlomo

IPC: G06K9/00 ,  G06T7/73 ,  G06N3/02 ,  B60W60/00 ,  B60W40/04

Abstract: Vehicles and methods for detecting a three-dimensional (3D) position of a traffic sign and controlling a feature of the vehicle based on the 3D position of the traffic sign. An image is received from a camera. The image is processed using a neural network. The neural network includes a traffic sign class block regressing a traffic sign class for a traffic sign included in the image and a rotation block regressing an orientation for the traffic sign. Dimensions for the traffic sign are retrieved from an information database based on the traffic sign class. A 3D position of the traffic sign is determined based on the dimensions of the traffic sign and the orientation of the traffic sign. A feature of the vehicle is controlled based on the 3D position of the traffic sign.

公开(公告)号：US20210295113A1

公开(公告)日：2021-09-23

申请号：US16822833

申请日：2020-03-18

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Liat Sless ,  Gilad Cohen ,  Shaul Oron ,  Bat El Shlomo ,  Roee Lahav

IPC: G06K9/62 ,  G06T7/20 ,  G06T7/50 ,  G06K9/20 ,  G06K9/00 ,  G01S13/86 ,  G01S13/931 ,  G01S7/41

Abstract: A vehicle, system and method of detecting an object. The system includes an image network, a radar network and a head. The image network receives image data and proposes a boundary box from the image data and an object proposal. The radar network receives radar data and the boundary box and generates a fused set of data including the radar data and the image data. The head determines a parameter of the object from the object proposal and the fused set of data.