公开(公告)号：US09386302B2

公开(公告)日：2016-07-05

申请号：US14283518

申请日：2014-05-21

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing Zeng ,  Wende Zhang ,  Jinsong Wang

IPC: H04N17/00 ,  G06K9/52 ,  G06T7/00 ,  G06K9/00

CPC classification number: H04N17/002 ,  G06K9/00791 ,  G06K9/52 ,  G06T7/80 ,  G06T2207/30264 ,  H04N17/00

Abstract: A method of calibrating multiple vehicle-based image capture devices of a vehicle. An image is captured by at least one image capture device. A reference object is identified in the captured image. The reference object has known world coordinates. Known features of the vehicle are extracted in the captured image. A relative location and orientation of the vehicle in world coordinates is determined relative to the reference object. Each of the multiple image capture devices is calibrated utilizing intrinsic and extrinsic parameters of the at least one image capture device as a function of the relative location and orientation of the vehicle in world coordinates.

Abstract translation: 一种校准车辆的多个基于车辆的图像捕获装置的方法。 图像被至少一个图像捕获设备捕获。 在捕获的图像中识别参考对象。 参考对象具有已知的世界坐标。 在捕获的图像中提取车辆的已知特征。 相对于参考对象确定车辆在世界坐标系中的相对位置和方向。 根据世界坐标中车辆的相对位置和取向，使用至少一个图像捕获装置的固有和非本征参数来校准多个图像捕获装置中的每一个。

公开(公告)号：US09329269B2

公开(公告)日：2016-05-03

申请号：US13777469

申请日：2013-02-26

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing Zeng

IPC: G01P3/36 ,  G01S17/58 ,  G01S17/66 ,  G01S17/87 ,  G01S17/93

CPC classification number: G01S17/58 ,  G01S17/023 ,  G01S17/66 ,  G01S17/875 ,  G01S17/936

Abstract: A system and method for registering range images from objects detected by multiple LiDAR sensors on a vehicle. The method includes aligning frames of data from at least two LiDAR sensors having over-lapping field-of-views in a sensor signal fusion operation so as to track objects detected by the sensors. The method defines a transformation value for at least one of the LiDAR sensors that identifies an orientation angle and position of the sensor and provides target scan points from the objects detected by the sensors where the target scan points for each sensor provide a separate target point map. The method projects the target point map from the at least one sensor to another one of the LiDAR sensors using a current transformation value to overlap the target scan points from the sensors.

Abstract translation: 用于将车辆上由多个LiDAR传感器检测到的物体的距离图像进行记录的系统和方法。 该方法包括在传感器信号融合操作中对来自至少两个具有超研磨视场的LiDAR传感器的数据帧进行对准，以便跟踪由传感器检测到的物体。 该方法定义了至少一个LiDAR传感器的变换值，其识别传感器的取向角度和位置，并且从传感器检测到的物体提供目标扫描点，其中每个传感器的目标扫描点提供单独的目标点图 。 该方法使用当前变换值将目标点映射从至少一个传感器投射到另一个LiDAR传感器，以与来自传感器的目标扫描点重叠。

公开(公告)号：US09250324B2

公开(公告)日：2016-02-02

申请号：US13901123

申请日：2013-05-23

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing Zeng ,  Wende Zhang ,  Mark E. Shields

IPC: G01S13/93 ,  G01S7/40 ,  G01S13/87 ,  G01S7/41 ,  G01S13/00

CPC classification number: G01S13/931 ,  G01S7/40 ,  G01S7/41 ,  G01S13/87 ,  G01S2007/4039 ,  G01S2013/9346 ,  G01S2013/9375

Abstract: A system and method for providing target selection and threat assessment for vehicle collision avoidance purposes that employ probability analysis of radar scan returns. The system determines a travel path of a host vehicle and provides a radar signal transmitted from a sensor on the host vehicle. The system receives multiple scan return points from detected objects, processes the scan return points to generate a distribution signal defining a contour of each detected object, and processes the scan return points to provide a position, a translation velocity and an angular velocity of each detected object. The system selects the objects that may enter the travel path of the host vehicle, and makes a threat assessment of those objects by comparing a number of scan return points that indicate that the object may enter the travel path to the number of the scan points that are received for that object.

Abstract translation: 一种系统和方法，用于为雷达扫描返回的概率分析提供用于车辆碰撞避免目的的目标选择和威胁评估。 该系统确定主车辆的行驶路径并提供从主车辆上的传感器发送的雷达信号。 系统从检测到的对象接收多个扫描返回点，处理扫描返回点以产生限定每个检测对象轮廓的分布信号，并处理扫描返回点以提供每个检测到的对象的位置，平移速度和角速度 目的。 该系统选择可能进入主车辆的行进路径的物体，并且通过将指示物体可以进入行驶路径的扫描返回点的数量与扫描点的数量进行比较来对这些物体进行威胁评估， 被接收为该对象。

公开(公告)号：US09174672B2

公开(公告)日：2015-11-03

申请号：US14065235

申请日：2013-10-28

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing Zeng ,  Nikolai K. Moshchuk ,  Rouhollah Jafari

IPC: B62D15/02 ,  G01S13/93 ,  G05D1/02 ,  B60W10/20 ,  B60W30/09 ,  B60W30/095 ,  B60R21/0134 ,  B62D6/00

CPC classification number: B62D6/00 ,  B60R21/0134 ,  B60W10/20 ,  B60W30/09 ,  B60W30/095 ,  B60W2420/52 ,  B62D15/0265 ,  G01S13/931 ,  G01S2013/9342 ,  G01S2013/9353 ,  G05D1/02 ,  G05D1/024

Abstract: A method for calculating a virtual target path around a target object that includes providing scan points identifying detected objects and separating the scan points into target object scan points and other object scan points. The method identifies a closest scan point from the target object scan points and identifies a path point that is a predetermined safe distance from the closest scan point. The method determines a straight target line adjacent to the target object that goes through the path point, and determines a distance between the target line and each of the other objects and determines whether all of the distances are greater than a predetermined threshold distance. The method identifies curve points for each other object whose distance is less than the predetermined threshold distance, and identifies a curve path that connects the curve points to be the virtual target path using a quadratic polynomial function.

Abstract translation: 一种用于计算目标对象周围的虚拟目标路径的方法，包括提供识别检测到的对象的扫描点并将扫描点分离为目标对象扫描点和其他对象扫描点。 该方法从目标对象扫描点识别最近的扫描点，并识别距离最近的扫描点预定安全距离的路径点。 该方法确定与目标对象相邻的直线目标线，该直线目标线通过路径点，并且确定目标线与每个其它对象之间的距离，并且确定所有距离是否大于预定阈值距离。 该方法识别距离小于预定阈值距离的每个对象的曲线点，并且使用二次多项式函数来识别将曲线点连接成虚拟目标路径的曲线路径。

公开(公告)号：US08712663B1

公开(公告)日：2014-04-29

申请号：US13664681

申请日：2012-10-31

Applicant: GM Global Technology Operations LLC

Inventor： Shuqing Zeng

IPC: B60T8/32

CPC classification number: B60W10/06 ,  B60W10/184 ,  B60W30/143 ,  B60W30/16 ,  B60W40/04 ,  B60W2550/143 ,  B60W2550/302 ,  B60W2550/308 ,  B60W2550/402 ,  B60W2720/103 ,  B60W2720/106 ,  B60W2720/125

Abstract: An exemplary cruise control system includes an application that integrates curvature speed control, speed limit control, and adaptive speed control and generates an optimized speed profile that is used to control the vehicle.

Abstract translation: 示例性巡航控制系统包括集成曲率速度控制，速度限制控制和自适应速度控制的应用，并且生成用于控制车辆的优化速度曲线。

公开(公告)号：US20130242284A1

公开(公告)日：2013-09-19

申请号：US13789412

申请日：2013-03-07

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing Zeng

IPC: G01S17/66

CPC classification number: G01S17/87 ,  G01S17/023 ,  G01S17/66 ,  G01S17/936

Abstract: A system and method for fusing the outputs from multiple LiDAR sensors on a vehicle that includes cueing the fusion process in response to an object being detected by a radar sensor and/or a vision system. The method includes providing object files for objects detected by the LiDAR sensors at a previous sample time, where the object files identify the position, orientation and velocity of the detected objects. The method projects object models in the object files from the previous sample time to provide predicted object models. The method also includes receiving a plurality of scan returns from objects detected in the field-of-view of the sensors at a current sample time and constructing a point cloud from the scan returns. The method then segments the scan points in the point cloud into predicted scan clusters, where each cluster identifies an object detected by the sensors.

Abstract translation: 一种用于将来自车辆上的多个LiDAR传感器的输出进行融合的系统和方法，其包括响应于由雷达传感器和/或视觉系统检测到的物体来引导融合过程。 该方法包括为先前采样时间的LiDAR传感器检测到的物体提供目标文件，其中目标文件识别被检测物体的位置，方位和速度。 该方法从上一个采样时间对象文件中的对象模型进行投影，以提供预测对象模型。 该方法还包括在当前采样时间从传感器的视场中检测到的物体接收多个扫描返回，并从扫描返回构建点云。 然后，该方法将点云中的扫描点分段为预测的扫描簇，其中每个簇识别由传感器检测到的对象。

公开(公告)号：US20250035463A1

公开(公告)日：2025-01-30

申请号：US18359017

申请日：2023-07-26

Applicant: GM Global Technology Operations LLC

Inventor： Bo Yu ,  Gui Chen ,  Fan Bai ,  Shuqing Zeng ,  Joon Hwang ,  Mason David Gemar

IPC: G01C21/00 ,  B60W60/00

Abstract: A method for crowd-sourcing lane line map data for a vehicle includes receiving a plurality of observations. The method also includes classifying the plurality of observations into a plurality of observation categories. Each of the plurality of observation categories includes at least one of the plurality of observations. The method also includes determining a plurality of aligned point clouds based at least in part on the plurality of observations. One of the plurality of aligned point clouds corresponds to each of the plurality of observation categories. The method also includes determining a plurality of lane line maps based at least in part on the plurality of aligned point clouds. One of the plurality of lane line maps corresponds to each of the plurality of aligned point clouds. The method also includes updating a map database based at least in part on the plurality of lane line maps.

公开(公告)号：US12125379B2

公开(公告)日：2024-10-22

申请号：US17725814

申请日：2022-04-21

Applicant: GM Global Technology Operations LLC

Inventor： Wei Tong ,  Shige Wang ,  Shuqing Zeng ,  Sourav Dey ,  Xiaofeng Frank Song ,  Upali P. Mudalige ,  Praveen Choudhury

IPC: G08G1/01

CPC classification number: G08G1/0145 ,  G08G1/0133 ,  G08G1/0141

Abstract: A method for validating an autonomous vehicle performance using nearby traffic patterns includes receiving remote vehicle data. The remote vehicle data includes at least one remote-vehicle motion parameter about a movement of a plurality of remote vehicles during a predetermined time interval. The method further includes determining a traffic pattern of the plurality of remote vehicles using the at least one remote-vehicle motion parameter. The method includes determining a similarity between the traffic pattern of the plurality of remote vehicles and movements of the host vehicle. Further, the method includes determining whether the similarity between the traffic pattern of the plurality of remote vehicles and movements of the host vehicle is less than a predetermined threshold. Also, the method includes commanding the host vehicle to adjust the movements thereof to match the traffic pattern of the plurality of remote vehicles.

公开(公告)号：US11989947B2

公开(公告)日：2024-05-21

申请号：US17367847

申请日：2021-07-06

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing Zeng ,  Jordan B. Chipka ,  Thanura R. Elvitigala

IPC: G06V20/58 ,  B60R11/04 ,  G06N3/08 ,  G06T3/40 ,  G06V10/25

CPC classification number: G06V20/58 ,  B60R11/04 ,  G06N3/08 ,  G06T3/40 ,  G06V10/25

Abstract: A perception system is adapted to receive visual data from a camera and includes a controller having a processor and tangible, non-transitory memory on which instructions are recorded. A subsampling module, an object detection module and an attention module are each selectively executable by the controller. The controller is configured to sample an input image from the visual data to generate a rescaled whole image frame, via the subsampling module. The controller is configured to extract feature data from the rescaled whole image frame, via the object detection module. A region of interest in the rescaled whole image frame is identified, based on an output of the attention module. The controller is configured to generate a first image based on the rescaled whole image frame and a second image based on the region of interest, the second image having a higher resolution than the first image.

公开(公告)号：US20240140475A1

公开(公告)日：2024-05-02

申请号：US18050642

申请日：2022-10-28

Applicant: GM Global Technology Operations LLC

Inventor： Shuqing Zeng ,  Wei Tong ,  Heng Zhou ,  Upali P. Mudalige ,  Reza Zarringhalam

IPC: B60W60/00 ,  G06V20/56

CPC classification number: B60W60/001 ,  G06V20/588 ,  B60W2520/10 ,  B60W2520/12 ,  B60W2520/14 ,  B60W2552/53 ,  B60W2554/4041 ,  B60W2554/4045

Abstract: A method for determining a lane centerline includes detecting a remote vehicle ahead of a host vehicle includes determining a trajectory of the remote vehicle that is ahead of the host vehicle, extracting features of the trajectory of the remote vehicle that is ahead of the host vehicle to generate a trajectory feature vector, and classifying the trajectory of the remote vehicle that is ahead of the host vehicle using the trajectory feature vector to determine whether the trajectory of the remote vehicle includes a lane change. The method further includes determining a centerline of the current lane using the trajectory of the remote vehicle that does not include the lane change and commanding the host vehicle to move autonomously along the centerline of the current lane to maintain the host vehicle in the current lane.