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公开(公告)号:US12280786B2
公开(公告)日:2025-04-22
申请号:US18319037
申请日:2023-05-17
Applicant: GM Global Technology Operations LLC
Inventor: Alaa M. Khamis , Wei Tong
Abstract: A system for identifying adversarial behavior directed to an autonomous vehicle includes a pedestrian detection system in communication with a vehicle controller adapted to identify a pedestrian within proximity of the autonomous vehicle, track the pedestrian, determine if the pedestrian is intending to cross in front of the autonomous vehicle, and if the pedestrian tracking system determines that the pedestrian is not intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to continue tracking the pedestrian, and if the pedestrian tracking system determines that the pedestrian is intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to determine, with an adversarial intent algorithm, if the pedestrian is exhibiting any adversarial behavior.
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公开(公告)号:US20240383481A1
公开(公告)日:2024-11-21
申请号:US18319037
申请日:2023-05-17
Applicant: GM Global Technology Operations LLC
Inventor: Alaa M. Khamis , Wei Tong
Abstract: A system for identifying adversarial behavior directed to an autonomous vehicle includes a pedestrian detection system in communication with a vehicle controller adapted to identify a pedestrian within proximity of the autonomous vehicle, track the pedestrian, determine if the pedestrian is intending to cross in front of the autonomous vehicle, and if the pedestrian tracking system determines that the pedestrian is not intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to continue tracking the pedestrian, and if the pedestrian tracking system determines that the pedestrian is intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to determine, with an adversarial intent algorithm, if the pedestrian is exhibiting any adversarial behavior.
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公开(公告)号:US12038870B2
公开(公告)日:2024-07-16
申请号:US17679388
申请日:2022-02-24
Applicant: GM Global Technology Operations LLC
Inventor: Shige Wang , Wei Tong , Donald K. Grimm
CPC classification number: G06F16/113 , B60W40/09 , B60W60/001 , B60W2420/403 , B60W2540/30 , B60W2555/20
Abstract: An on-demand, feature focused data collection system of an automobile vehicle includes at least one data collection device provided with an automobile vehicle. A data collection unit receives data from the at least one data collection device in response to a data collection request submitted by a user. A data scene group combines portions of the data received by the data collection unit and stored in the data collection unit of the automobile vehicle or at a remote server. A control logic device receives the data collection request and activates collection of the data. The control logic device includes: a data collection strategy which differs if different types of the data are available; a reference algorithm loaded or deployed; a storage capacity allocated for the data; and a storage policy employed to save the data.
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公开(公告)号:US20240046627A1
公开(公告)日:2024-02-08
申请号:US17817704
申请日:2022-08-05
Applicant: GM Global Technology Operations LLC
Inventor: Siddhartha Gupta , Wei Tong , Upali P. Mudalige
IPC: G06V10/778 , G06V10/74 , G06V10/25 , G06T7/11 , G06V10/26 , G06V10/774
CPC classification number: G06V10/778 , G06V10/761 , G06V10/25 , G06T7/11 , G06V10/26 , G06V10/774 , G06T2207/20132 , G06T2207/20084 , G06T2207/20081 , G06T2207/10024
Abstract: A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to determine a pairwise region of interest feature similarity based on features extracted from a first cropped image portion and corresponding point cloud data and features extracted from a second cropped image portion and corresponding point cloud data. The processor is also programmed to determine a loss using a loss function based on the pairwise region of interest feature similarity, wherein the loss function corresponds to at least one a first deep neural network or a second deep neural network. The processor is also programmed to update at least one weight of the at least one of the first deep neural network or the second deep neural network based on the loss.
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5.
公开(公告)号:US11875548B2
公开(公告)日:2024-01-16
申请号:US17382459
申请日:2021-07-22
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor: Wei Tong , Shige Wang , Shuqing Zeng
CPC classification number: G06V10/25 , B60W40/06 , B60W50/14 , B60W60/0011 , G01S17/89 , G01S17/931 , G06V20/58 , B60W2554/4041 , B60W2554/4046 , B60W2556/40
Abstract: A system for an attention-based perception includes a camera device configured to provide an image of an operating environment of a vehicle. The system further includes a computerized device monitoring the image, analyzing sensor data to identify a feature in the image as corresponding to an object in the operating environment and assign a score for the feature based upon an identification, a location, or a behavior of the object. The computerized device is further operable to define candidate regions of interest upon the image, correlate the score for the feature to the candidate regions of interest to accrue a total region score, select some of the candidate regions for analysis based upon the total region scores, and analyze the portion of the candidate regions to generate a path of travel output. The system further includes a device controlling the vehicle based upon the output.
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公开(公告)号:US20230316728A1
公开(公告)日:2023-10-05
申请号:US17709553
申请日:2022-03-31
Applicant: GM Global Technology Operations LLC
Inventor: Wei Tong , Jacob Alan Bond , Siddhartha Gupta
IPC: G06V10/774 , G06N3/08 , G06V10/82
CPC classification number: G06V10/7747 , G06N3/08 , G06V10/82
Abstract: A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: receive intermediate concept constraints at a neural network and train the neural network with training data, training labels, and the at least one of the data constraint, the feature constraint, or the intermediate concept constraint.
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7.
公开(公告)号:US20230264709A1
公开(公告)日:2023-08-24
申请号:US17679388
申请日:2022-02-24
Applicant: GM Global Technology Operations LLC
Inventor: SHIGE WANG , Wei Tong , Donald K. Grimm
CPC classification number: B60W60/001 , B60W40/09 , B60W2540/30 , B60W2420/42 , B60W2555/20
Abstract: An on-demand, feature focused data collection system of an automobile vehicle includes at least one data collection device provided with an automobile vehicle. A data collection unit receives data from the at least one data collection device in response to a data collection request submitted by a user. A data scene group combines portions of the data received by the data collection unit and stored in the data collection unit of the automobile vehicle or at a remote server. A control logic device receives the data collection request and activates collection of the data. The control logic device includes: a data collection strategy which differs if different types of the data are available; a reference algorithm loaded or deployed; a storage capacity allocated for the data; and a storage policy employed to save the data.
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公开(公告)号:US20220245598A1
公开(公告)日:2022-08-04
申请号:US17163748
申请日:2021-02-01
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor: Wei Tong , Shuqing Zeng , Shige Wang , Jiang-Ling Du , Upali P. Mudalige
Abstract: A vehicle communication and control system includes a servicing host capable of exchanging data with a vehicle. The servicing host provides a vehicle service and includes a service identifier (ID) that indicates the vehicle service. The vehicle is configured to actively detect the service ID and to determine the vehicle service in response to detecting the service ID. The vehicle and the servicing host establish a wireless connection to exchange data and automatically initiate the vehicle service in response to detecting the service ID.
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公开(公告)号:US11300974B2
公开(公告)日:2022-04-12
申请号:US16515592
申请日:2019-07-18
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor: Lawrence A. Bush , Upali P. Mudalige , Zachariah E. Tyree , Wei Tong , Shuqing Zeng
Abstract: Methods and systems are provided for detecting objects within an environment of a vehicle. In one embodiment, a method includes: receiving, by a processor, image data sensed from the environment of the vehicle; determining, by a processor, an area within the image data that object identification is uncertain; controlling, by the processor, a position of a lighting device to illuminate a location in the environment of the vehicle, wherein the location is associated with the area; controlling, by the processor, a position of one or more sensors to obtain sensor data from the location of the environment of the vehicle while the lighting device is illuminating the location; identifying, by the processor, one or more objects from the sensor data; and controlling, by the processor, the vehicle based on the one or more objects.
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10.
公开(公告)号:US10861176B2
公开(公告)日:2020-12-08
申请号:US16200932
申请日:2018-11-27
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor: Wei Tong , Shuqing Zeng , Mohannad Murad , Alaa M. Khamis
Abstract: Systems and methods for depth estimation of images from a mono-camera by use of radar data by: receiving, a plurality of input 2-D images from the mono-camera; generating, by the processing unit, an estimated depth image by supervised training of an image estimation model; generating, by the processing unit, a synthetic image from a first input image and a second input image from the mono-camera by applying an estimated transform pose; comparing, by the processing unit, an estimated three-dimensional (3-D) point cloud to radar data by applying another estimated transform pose to a 3-D point cloud wherein the 3-D point cloud is estimated from a depth image by supervised training of the image estimation model to radar distance and radar doppler measurement; correcting a depth estimation of the estimated depth image by losses derived from differences: of the synthetic image and original images; of an estimated depth image and a measured radar distance; and of an estimated doppler information and measured radar doppler information.
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