公开(公告)号：US20140142800A1

公开(公告)日：2014-05-22

申请号：US13679849

申请日：2012-11-16

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing ZENG ,  Yilu ZHANG ,  Bakhtiar Brian LITKOUHI ,  Mutasim A. SALMAN

IPC: G06F11/30

CPC classification number: G06F11/3055 ,  G01S7/4026 ,  G01S13/726 ,  G01S13/867 ,  G01S13/931 ,  G01S2007/4039 ,  G01S2013/9375 ,  G05B23/0221

Abstract: A method and system for estimating the state of health of an object sensing fusion system. Target data from a vision system and a radar system, which are used by an object sensing fusion system, are also stored in a context queue. The context queue maintains the vision and radar target data for a sequence of many frames covering a sliding window of time. The target data from the context queue are used to compute matching scores, which are indicative of how well vision targets correlate with radar targets, and vice versa. The matching scores are computed within individual frames of vision and radar data, and across a sequence of multiple frames. The matching scores are used to assess the state of health of the object sensing fusion system. If the fusion system state of health is below a certain threshold, one or more faulty sensors are identified.

Abstract translation: 一种用于估计物体感测融合系统的健康状况的方法和系统。 由对象感测融合系统使用的来自视觉系统和雷达系统的目标数据也存储在上下文队列中。 上下文队列维护覆盖时间滑动窗口的许多帧的序列的视觉和雷达目标数据。 来自上下文队列的目标数据用于计算匹配分数，这表示视觉目标与雷达目标相关的程度如何，反之亦然。 匹配得分是在单独的视觉和雷达数据帧内以及跨多个帧的序列计算的。 匹配分数用于评估物体感知融合系统的健康状况。 如果融合系统的健康状况低于某个阈值，则识别出一个或多个故障传感器。

公开(公告)号：US20170234988A1

公开(公告)日：2017-08-17

申请号：US15042758

申请日：2016-02-12

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Rouhollah JAFARI ,  Shuqing ZENG

IPC: G01S19/47 ,  G01C21/16

CPC classification number: G01S19/47 ,  G01C21/12 ,  G01C21/16 ,  G01C21/165 ,  G01S19/53

Abstract: A system and method for correcting bias and angle misalignment errors in the angle rate and acceleration outputs from a 6-DOF IMU mounted to a vehicle. The method includes providing velocity and estimation attitude data in an inertial frame from, for example, a GNSS/INS, and determining an ideal acceleration estimation and an ideal rate estimation in a vehicle frame using the velocity and attitude data. The method then determines the IMU bias error and misalignment error using the ideal acceleration and rate estimations and the angle rate and acceleration outputs in an IMU body frame from the IMU.

公开(公告)号：US20190018132A1

公开(公告)日：2019-01-17

申请号：US15648795

申请日：2017-07-13

Applicant: GM Global Technology Operations LLC

Inventor： Stephen W. DECKER ,  Jeremy P. GRAY ,  Igal BILIK ,  Shuqing ZENG

IPC: G01S13/93 ,  G01S13/04 ,  G01S13/42 ,  B60Q9/00

Abstract: An ultra-short range radar (USRR) system of a vehicle includes an object detection module configured to, based on radar signals from USRR sensors of the vehicle: identify the presence of an object that is external to the vehicle; determine a location of the object; and determine at least one of a height, a length, and a width of the object. A remedial action module is configured to, based on the location of the object and the at least one dimension of the object, at least one of: selectively actuate an actuator of the vehicle; selectively generate an audible alert via at least one speaker of the vehicle; and selectively generate a visual alert via at least one light emitting device of the vehicle.

公开(公告)号：US20160018524A1

公开(公告)日：2016-01-21

申请号：US14828402

申请日：2015-08-17

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Shuqing ZENG

IPC: G01S17/87 ,  G01S17/93 ,  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：US20220156533A1

公开(公告)日：2022-05-19

申请号：US17098707

申请日：2020-11-16

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Yasen HU ,  Shuqing ZENG

IPC: G06K9/62 ,  G06K9/00 ,  G06K9/68 ,  G01S17/931 ,  G01S17/89

Abstract: A system includes first and second sensors and a controller. The first sensor is of a first type and is configured to sense objects around a vehicle and to capture first data about the objects in a frame. The second sensor is of a second type and is configured to sense the objects around the vehicle and to capture second data about the objects in the frame. The controller is configured to down-sample the first and second data to generate down-sampled first and second data having a lower resolution than the first and second data. The controller is configured to identify a first set of the objects by processing the down-sampled first and second data having the lower resolution. The controller is configured to identify a second set of the objects by selectively processing the first and second data from the frame.

公开(公告)号：US20150293216A1

公开(公告)日：2015-10-15

申请号：US14253090

申请日：2014-04-15

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Kevin A. O'DEA ,  Shuqing ZENG ,  James N. NICKOLAOU ,  Bradley HAMNER

IPC: G01S13/04 ,  G01S17/02 ,  B60W30/02 ,  B60W30/12 ,  B60W30/14

CPC classification number: B60W30/02 ,  B60W30/12 ,  B60W30/14 ,  G01S13/726 ,  G01S13/867 ,  G01S13/87 ,  G01S13/931 ,  G01S2013/9353 ,  G01S2013/9367 ,  G01S2013/9375

Abstract: A system and method for selectively reducing or filtering data provided by one or more vehicle mounted sensors before using that data to detect, track and/or estimate a stationary object located along the side of a road, such as a guardrail or barrier. According to one example, the method reduces the amount of data by consolidating, classifying and pre-sorting data points from several forward looking radar sensors before using those data points to determine if a stationary roadside object is present. If the method determines that a stationary roadside object is present, then the reduced or filtered data points can be applied to a data fitting algorithm in order to estimate the size, shape and/or other parameters of the object. In one example, the output of the present method is provided to automated or autonomous driving systems.

Abstract translation: 一种用于在使用该数据检测，跟踪和/或估计位于诸如护栏或障碍物之类的道路侧面的静止物体之前，选择性地减少或过滤由一个或多个车载传感器提供的数据的系统和方法。 根据一个示例，该方法通过在使用这些数据点来确定是否存在固定的路边对象之前对来自多个前瞻性雷达传感器的数据点进行合并，分类和预排​​序来减少数据量。 如果该方法确定存在固定的路边对象，则减少或过滤的数据点可以应用于数据拟合算法，以估计对象的大小，形状和/或其他参数。 在一个示例中，本方法的输出被提供给自动或自主驾驶系统。