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公开(公告)号：US20220080997A1
公开(公告)日：2022-03-17
申请号：US17024277
申请日：2020-09-17
Applicant: GM Global Technology Operations LLC
Inventor： Alon Raveh , Shaul Oron , Bat El Shlomo
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.
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公开(公告)号：US11270170B2
公开(公告)日：2022-03-08
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
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.
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公开(公告)号：US20220366173A1
公开(公告)日：2022-11-17
申请号：US17241532
申请日：2021-04-27
Applicant: GM Global Technology Operations LLC
Inventor： Alon Raveh , Shaul Oron
Abstract: A vehicle, system and method of navigating the vehicle. The system includes a sensor and a processor. The sensor is configured to obtain a first set of detection points representative of a lane of a road section at a first time step and a second set of detection points representative of the lane at a second time step. The processor is configured to determine a set of predicted points for the second time step from the first set of detection points, obtain a set of fused points from the second set of detection points and the set of predicted points, and navigate the vehicle using the set of fused points.
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公开(公告)号：US10474908B2
公开(公告)日：2019-11-12
申请号：US15642816
申请日：2017-07-06
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Dan Levi , Noa Garnett , Ethan Fetaya , Shaul Oron
Abstract: A method in a vehicle for performing multiple on-board sensing tasks concurrently in the same network using deep learning algorithms is provided. The method includes receiving vision sensor data from a sensor on the vehicle, determining a set of features from the vision sensor data using a plurality of feature layers in a convolutional neural network, and concurrently estimating, using the convolutional neural network, bounding boxes for detected objects, free-space boundaries, and object poses for detected objects from the set of features determined by the plurality of feature layers. The neural network may include a plurality of free-space estimation layers configured to determine the boundaries of free-space in the vision sensor data, a plurality of object detection layers configured to detect objects in the image and to estimate bounding boxes that surround the detected objects, and a plurality of object pose detection layers configured to estimate the direction of each object.
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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
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.
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Patent Agency Ranking
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
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.
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公开(公告)号：US20240143074A1
公开(公告)日：2024-05-02
申请号：US18489338
申请日：2023-10-18
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Ron M. Hecht , Omer Tsimhoni , Dan Levi , Shaul Oron , Andrea Forgacs , Ohad Rahamim , Gershon Celniker
CPC classification number: G06F3/013 , G06T7/50 , G06V10/761 , G06T2207/20084 , G06T2207/20228 , G06V2201/07
Abstract: A method of training a disparity estimation network. The method includes obtaining an eye-gaze dataset having first images with at least one gaze direction associated with each of the first images. A gaze prediction neural network is trained based on the eye-gaze dataset to develop a model trained to provide a gaze prediction for an external image. A depth database is obtained that includes second images having depth information associated with each of the second images. A disparity estimation neural network for object detection is trained based on an output from the gaze prediction neural network and an output from the depth database.
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公开(公告)号：US11756312B2
公开(公告)日：2023-09-12
申请号：US17024265
申请日：2020-09-17
Applicant: GM Global Technology Operations LLC
Inventor： Alon Raveh , Shaul Oron , Bat El Shlomo
CPC classification number: G06V20/588 , G05D1/0212 , G06F18/217 , G05D1/0088 , G05D2201/0213
Abstract: Systems and methods include obtaining observation points of a lane line using a sensor of a vehicle. Each observation point indicates a location of a point on the lane line. A method includes generating or updating a lane model with the observation points. The lane model indicates a path of the lane line and the lane model is expressed in a lane-specific coordinate system that differs from a vehicle coordinate system that is defined by an orientation of the vehicle. The method also includes transforming the lane-specific coordinate system to maintain a correspondence between the lane-specific coordinate system and the vehicle coordinate system based on a change in orientation of the vehicle resulting in a change in the vehicle coordinate system.
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9.发明授权公开(公告)号：US11214261B2
公开(公告)日：2022-01-04
申请号：US16437317
申请日：2019-06-11
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Max Bluvstein , Shaul Oron , Bat El Shlomo
Abstract: Methods and apparatus are provided for detecting and assigning objects to sensed values. An object detection arrangement includes a processor that is programmed to execute a first branch of instructions and a second branch of instructions. Each branch of instructions includes receiving a modality from at least one sensor of a group of sensors via a respective interface and determining an output value based on the modality. The object detection arrangement includes an association distance matrix. Modalities of different branches of instructions define different modalities of an object external to the object detection arrangement. The object detection arrangement cumulates the output values, and the association distance matrix associates an object to the cumulated output values to thereby detect and track the object external to the object detection arrangement.
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10.发明申请公开(公告)号：US20190012548A1
公开(公告)日：2019-01-10
申请号：US15642816
申请日：2017-07-06
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Dan Levi , Noa Garnett , Ethan Fetaya , Shaul Oron
CPC classification number: G06K9/00791 , G06K9/00805 , G06K9/6267 , G06T7/11 , G06T7/73 , G06T2207/10024 , G06T2207/20081 , G06T2207/20084 , G06T2207/30252 , G06T2207/30261
Abstract: A method in a vehicle for performing multiple on-board sensing tasks concurrently in the same network using deep learning algorithms is provided. The method includes receiving vision sensor data from a sensor on the vehicle, determining a set of features from the vision sensor data using a plurality of feature layers in a convolutional neural network, and concurrently estimating, using the convolutional neural network, bounding boxes for detected objects, free-space boundaries, and object poses for detected objects from the set of features determined by the plurality of feature layers. The neural network may include a plurality of free-space estimation layers configured to determine the boundaries of free-space in the vision sensor data, a plurality of object detection layers configured to detect objects in the image and to estimate bounding boxes that surround the detected objects, and a plurality of object pose detection layers configured to estimate the direction of each object.
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