-
公开(公告)号：US10395144B2
公开(公告)日：2019-08-27
申请号：US15658138
申请日：2017-07-24
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Shuqing Zeng , Wei Tong , Upali P. Mudalige
Abstract: Methods and apparatus are provided for controlling an autonomous vehicle. A sensor fusion system with a sensor system for providing environment condition information and a convolutional neural network (CNN) is provided. The CNN includes a receiving interface configured to receive the environment condition information from the sensor system, a common convolutional layer configured to extract traffic information from the received environment condition information, and a plurality of fully connected layers configured to detect objects belonging to different object classes based on the extracted traffic information, wherein the object classes include at least one of a road feature class, a static object class, and a dynamic object class.
-
公开(公告)号：US10373000B2
公开(公告)日：2019-08-06
申请号：US15677649
申请日：2017-08-15
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Wei Tong , Qingrong Zhao , Shuqing Zeng , Bakhtiar B. Litkouhi
Abstract: A method of identifying a condition of a road surface includes capturing at least a first image of the road surface with a first camera, and a second image of the road surface with a second camera. The first image and the second image are tiled together to form a combined tile image. A feature vector is extracted from the combined tile image using a convolutional neural network, and a condition of the road surface is determined from the feature vector using a classifier.
-
公开(公告)号：US20190228504A1
公开(公告)日：2019-07-25
申请号：US15878937
申请日：2018-01-24
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Wei Tong , Shuqing Zeng , Upali P. Mudalige
Abstract: A system and method for generating a range image using sparse depth data is disclosed. The method includes receiving, by a controller, image data of a scene. The image data includes a first set of pixels. The method also includes receiving, by the controller, a sparse depth data of the scene. The sparse depth data includes a second set of pixels, and the number of the second set of pixels is less than the number of first set of pixels. The method also includes combining the image data and the sparse depth data into a combined data. The method also includes generating a range image using the combined data.
-
公开(公告)号：US20160378118A1
公开(公告)日：2016-12-29
申请号：US14747888
申请日：2015-06-23
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Shuqing Zeng , Wei Tong , Jinsong Wang , Wende Zhang
CPC classification number: G05D1/0246 , B60D1/36 , B60D1/62 , B60R1/00 , B60R2300/202 , B60R2300/808 , B62D13/00 , G05D1/0212
Abstract: A method for autonomously aligning a tow hitch ball on a towing vehicle and a trailer drawbar on a trailer through a human-machine interface (HMI) assisted visual servoing process. The method includes providing rearview images from a rearview camera. The method includes touching the tow ball on a display to register a location of the tow ball in the image and touching the drawbar on the display to register a location of a target where the tow ball will be properly aligned with the drawbar. The method provides a template pattern around the target on the image and autonomously moves the vehicle so that the tow ball moves towards the target. The method predicts a new location of the target as the vehicle moves and identifies the target in new images as the vehicle moves by comparing the previous template pattern with an image patch around the predicted location.
Abstract translation: 一种用于通过人机界面（HMI）辅助的视觉伺服过程来自动地将牵引车上的牵引牵引球和拖车上的拖车牵引杆对准的方法。 该方法包括从后视摄像机提供后视图像。 该方法包括在显示器上触摸拖球，以将拖曳球的位置注册在图像中并且在显示器上接触牵引杆以登记目标的位置，其中拖曳球将与牵引杆正确对准。 该方法提供围绕图像上的目标的模板图案，并且自动地移动车辆，使得拖曳球朝向目标移动。 当车辆移动时，该方法预测目标的新位置，并通过将先前的模板模式与预测位置周围的图像补丁进行比较来识别车辆移动时的新图像中的目标。
-
公开(公告)号：US20240383503A1
公开(公告)日：2024-11-21
申请号：US18319026
申请日：2023-05-17
Applicant: GM Global Technology Operations LLC
Inventor： Alaa M. Khamis , Wei Tong , Upali P. Mudalige
Abstract: A system for determining opportunity and capability for identified adversarial behavior within an autonomous vehicle, comprising a pedestrian detection system, a vehicle controller and an adversarial intent algorithm adapted to determine a risk level of adversarial behavior from at least one pedestrian within proximity of the autonomous vehicle, and, when the adversarial intent algorithm determines that there is a risk of adversarial behavior, to determine a risk level of the adversarial behavior based on opportunity and capability.
-
Patent Agency Ranking
公开(公告)号：US11975714B2
公开(公告)日：2024-05-07
申请号：US16671727
申请日：2019-11-01
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Shige Wang , Wei Tong , Stephen N. McKinnie , Shuqing Zeng
CPC classification number: B60W30/146 , B60W30/09 , B60W30/17 , H04J3/0644 , H04J3/0664 , H04L12/403 , H04L67/12 , H04L2012/40215 , H04L2012/40273
Abstract: Presented are embedded control systems with logic for computation and data sharing, methods for making/using such systems, and vehicles with distributed sensors and embedded processing hardware for provisioning automated driving functionality. A method for operating embedded controllers connected with distributed sensors includes receiving a first data stream from a first sensor via a first embedded controller, and storing the first data stream with a first timestamp and data lifespan via a shared data buffer in a memory device. A second data stream is received from a second sensor via a second embedded controller. A timing impact of the second data stream is calculated based on the corresponding timestamp and data lifespan. Upon determining that the timing impact does not violate a timing constraint, the first data stream is purged from memory and the second data stream is stored with a second timestamp and data lifespan in the memory device.
-
公开(公告)号：US20240116527A1
公开(公告)日：2024-04-11
申请号：US17938443
申请日：2022-10-06
Applicant: GM Global Technology Operations LLC
Inventor： Wei Tong , Xiaofeng Frank Song , Shige Wang , Shuqing Zeng , Gopichand Movva
CPC classification number: B60W50/14 , B60Q1/525 , B60W40/04 , G08G1/096783 , H04W4/44 , H04W4/46 , B60W2420/54 , B60W2556/45
Abstract: A dynamic side blind zone method includes determining that a host vehicle is approaching a first lane that is nonparallel to a second lane. The host vehicle is moving in the second lane. The method further includes activating an adaptive side blind zone alert system of the host vehicle in response to determining that the host vehicle is approaching the first lane that is nonparallel to the second lane, determining a warning zone in response to activating the adaptive side blind zone alert system of the host vehicle, and detecting a remote vehicle inside the warning zone after determining the warning zone. The remote vehicle is moving in the first lane. The method further includes providing an alert to a vehicle user of the host vehicle in response to detecting that the remote vehicle is inside the warning zone.
-
58.发明授权公开(公告)号：US11954916B2
公开(公告)日：2024-04-09
申请号：US17665895
申请日：2022-02-07
Applicant: GM Global Technology Operations LLC
Inventor： Wei Tong , Siddhartha Gupta , Jacob Alan Bond , Zhuoning Yuan
CPC classification number: G06V20/58 , B60W40/04 , B60W60/001 , G06V10/40 , G06V10/761 , G06V10/764 , G06V10/82 , B60W2420/403 , B60W2554/4026 , B60W2554/4029
Abstract: An automated driving system includes an object detection system. A neural network image encoder generates image embeddings associated with an image including an object. A neural network text encoder generates concept embeddings associated with each of a plurality of concepts. Each of the plurality of concepts is associated with one of at least two object classes. A confidence score module generates a confidence score for each of the plurality of concepts based on the image embeddings and the concept embeddings associated with the concept. An object class prediction module generates a predicted object class of the object based on an association between a set of concepts of the plurality of concepts having at least two of the highest values of the generated confidence scores and the one of the at least two object classes associated with a majority of the set of concepts.
-
59.发明公开公开(公告)号：US20230252795A1
公开(公告)日：2023-08-10
申请号：US17665895
申请日：2022-02-07
Applicant: GM Global Technology Operations LLC
Inventor： Wei Tong , Siddhartha Gupta , Jacob Alan Bond , Zhuoning Yuan
CPC classification number: G06V20/58 , G06V10/82 , G06V10/764 , G06V10/40 , G06V10/761 , B60W60/001 , B60W40/04 , B60W2554/4026 , B60W2554/4029 , B60W2420/42
Abstract: An automated driving system includes an object detection system. A neural network image encoder generates image embeddings associated with an image including an object. A neural network text encoder generates concept embeddings associated with each of a plurality of concepts. Each of the plurality of concepts is associated with one of at least two object classes. A confidence score module generates a confidence score for each of the plurality of concepts based on the image embeddings and the concept embeddings associated with the concept. An object class prediction module generates a predicted object class of the object based on an association between a set of concepts of the plurality of concepts having at least two of the highest values of the generated confidence scores and the one of the at least two object classes associated with a majority of the set of concepts.
-
公开(公告)号：US20230162039A1
公开(公告)日：2023-05-25
申请号：US17535129
申请日：2021-11-24
Applicant: GM Global Technology Operations LLC
Inventor： Siddhartha Gupta , Jacob Alan Bond , Wei Tong , Upali P. Mudalige
CPC classification number: G06N3/084 , G06V10/751 , 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, at a selective dropout layer of a neural network, a plurality of adversarial image features and a plurality of natural image features, select one or more nodes within the selective dropout layer to deactivate based on a comparison of the plurality of adversarial image features with the plurality of natural image features, and deactivate the selected one or more nodes.
-
-
-
-
-
-
-
-
-
Search Results
103
records
(took 0.021 seconds)
