公开(公告)号：US20120290169A1

公开(公告)日：2012-11-15

申请号：US13104704

申请日：2011-05-10

申请人： Shuqing Zeng ,  James N. Nickolaou ,  David A. Osinski

发明人： Shuqing Zeng ,  James N. Nickolaou ,  David A. Osinski

IPC分类号： G06F7/00 ,  G06F17/10

CPC分类号： G01S13/931 ,  G01S7/4026 ,  G01S7/4972 ,  G01S13/862 ,  G01S13/865 ,  G01S13/867 ,  G01S13/878 ,  G01S2007/403 ,  G01S2007/4091 ,  G01S2013/9375 ,  G01S2013/9389 ,  G08G1/163

摘要： A method and tools for virtually aligning object detection sensors on a vehicle without having to physically adjust the sensors. A sensor misalignment condition is detected during normal driving of a host vehicle by comparing different sensor readings to each other. At a vehicle service facility, the host vehicle is placed in an alignment target fixture, and alignment of all object detection sensors is compared to ground truth to determine alignment calibration parameters. Alignment calibration can be further refined by driving the host vehicle in a controlled environment following a leading vehicle. Final alignment calibration parameters are authorized and stored in system memory, and applications which use object detection data henceforth adjust the sensor readings according to the calibration parameters.

摘要翻译： 一种用于在车辆上虚拟对准物体检测传感器而不必物理地调节传感器的方法和工具。 通过将不同的传感器读数相互比较，在主车辆的正常驾驶期间检测传感器未对准状态。 在车辆服务设施中，主车辆被放置在对准目标夹具中，并且将所有物体检测传感器的对准与地面真实相比较以确定对准校准参数。 通过在主导车辆之后的受控环境中驾驶本车辆，可以进一步改善对准校准。 最终对准校准参数被授权并存储在系统存储器中，并且使用对象检测数据的应用从此根据校准参数调整传感器读数。

公开(公告)号：US08775064B2

公开(公告)日：2014-07-08

申请号：US13104704

申请日：2011-05-10

申请人： Shuqing Zeng ,  James N. Nickolaou ,  David A. Osinski

发明人： Shuqing Zeng ,  James N. Nickolaou ,  David A. Osinski

IPC分类号： G06F7/00 ,  G06F17/10 ,  G01M11/00

CPC分类号： G01S13/931 ,  G01S7/4026 ,  G01S7/4972 ,  G01S13/862 ,  G01S13/865 ,  G01S13/867 ,  G01S13/878 ,  G01S2007/403 ,  G01S2007/4091 ,  G01S2013/9375 ,  G01S2013/9389 ,  G08G1/163

摘要： A method and tools for virtually aligning object detection sensors on a vehicle without having to physically adjust the sensors. A sensor misalignment condition is detected during normal driving of a host vehicle by comparing different sensor readings to each other. At a vehicle service facility, the host vehicle is placed in an alignment target fixture, and alignment of all object detection sensors is compared to ground truth to determine alignment calibration parameters. Alignment calibration can be further refined by driving the host vehicle in a controlled environment following a leading vehicle. Final alignment calibration parameters are authorized and stored in system memory, and applications which use object detection data henceforth adjust the sensor readings according to the calibration parameters.

摘要翻译： 一种用于在车辆上虚拟对准物体检测传感器而不必物理地调节传感器的方法和工具。 通过将不同的传感器读数相互比较，在主车辆的正常驾驶期间检测传感器未对准状态。 在车辆服务设施中，主车辆被放置在对准目标夹具中，并且将所有物体检测传感器的对准与地面真实相比较以确定对准校准参数。 通过在主导车辆之后的受控环境中驾驶本车辆，可以进一步改善对准校准。 最终对准校准参数被授权并存储在系统存储器中，并且使用对象检测数据的应用从此根据校准参数调整传感器读数。

公开(公告)号：US08705797B2

公开(公告)日：2014-04-22

申请号：US13413861

申请日：2012-03-07

申请人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

发明人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

IPC分类号： G06K9/00 ,  H04N5/225

CPC分类号： G01S13/726 ,  G01S13/867 ,  G01S13/931 ,  G01S2013/9375 ,  G06K9/00805 ,  G06T1/0007

摘要： A method of associating targets from at least two object detection systems. An initial prior correspondence matrix is generated based on prior target data from a first object detection system and a second object detection system. Targets are identified in a first field-of-view of the first object detection system based on a current time step. Targets are identified in a second field-of-view of the second object detection system based on the current time step. The prior correspondence matrix is adjusted based on respective targets entering and leaving the respective fields-of-view. A posterior correspondence matrix is generated as a function of the adjusted prior correspondence matrix. A correspondence is identified in the posterior correspondence matrix between a respective target of the first object detection system and a respective target of the second object detection system.

摘要翻译： 将来自至少两个物体检测系统的目标相关联的方法。 基于来自第一对象检测系统和第二对象检测系统的先前目标数据生成初始先前对应矩阵。 基于当前时间步长，在第一对象检测系统的第一视场中识别目标。 基于当前时间步长，在第二对象检测系统的第二视场中识别目标。 基于进入和离开相应视场的各个目标来调整先前的对应矩阵。 作为调整后的对应矩阵的函数产生后向对应矩阵。 在第一对象检测系统的相应目标和第二对象检测系统的相应目标之间的后向对应矩阵中识别对应关系。

公开(公告)号：US20140032108A1

公开(公告)日：2014-01-30

申请号：US13561755

申请日：2012-07-30

申请人： Shuqing Zeng ,  BAKHTIAR BRIAN LITKOUHI ,  XINGPING CHEN ,  JAMES N. NICKOLAOU ,  DANIEL GANDHI ,  JOEL PAZHAYAMPALLIL

发明人： Shuqing Zeng ,  BAKHTIAR BRIAN LITKOUHI ,  XINGPING CHEN ,  JAMES N. NICKOLAOU ,  DANIEL GANDHI ,  JOEL PAZHAYAMPALLIL

IPC分类号： G06K9/62 ,  G01C21/34

CPC分类号： B60W30/12 ,  B60W2550/22 ,  B60W2550/306 ,  B60W2550/402 ,  G08G1/167

摘要： A method for selecting an anchor lane for tracking in a vehicle lane tracking system. Digital map data and leading vehicle trajectory data are used to predict lane information ahead of a vehicle. Left and right lane boundary markers are also detected, where available, using a vision system. The lane marker data from the vision system is combined with the lane information from the digital map data and the leading vehicle trajectory data in a lane curvature fusion calculation. The left and right lane marker data from the vision system are also evaluated for conditions such as parallelism and sudden jumps in offsets, while considering the presence of entrance or exit lanes as indicated by the map data. An anchor lane for tracking is selected based on the evaluation of the vision system data, using either the fused curvature calculation or the digital map and leading vehicle trajectory data.

摘要翻译： 一种用于在车道跟踪系统中选择用于跟踪的锚车道的方法。 数字地图数据和前导车辆轨迹数据用于预测车辆前方的车道信息。 还可以使用视觉系统检测左右车道边界标记。 来自视觉系统的车道标记数据与车道曲线融合计算中的数字地图数据和前车辆轨迹数据的车道信息相结合。 考虑到地图数据所示的入口或出口通道的存在，还可以评估来自视觉系统的左右车道标记数据，例如平行度和偏移突然跳跃等条件。 基于对视觉系统数据的评估，使用融合曲率计算或数字地图和前导车辆轨迹数据来选择用于跟踪的锚定车道。

公开(公告)号：US08706417B2

公开(公告)日：2014-04-22

申请号：US13561755

申请日：2012-07-30

申请人： Shuqing Zeng ,  Bakhtiar Brian Litkouhi ,  Xingping Chen ,  James N. Nickolaou ,  Daniel Gandhi ,  Joel Pazhayampallil

发明人： Shuqing Zeng ,  Bakhtiar Brian Litkouhi ,  Xingping Chen ,  James N. Nickolaou ,  Daniel Gandhi ,  Joel Pazhayampallil

IPC分类号： G05D1/00 ,  G08G1/137

CPC分类号： B60W30/12 ,  B60W2550/22 ,  B60W2550/306 ,  B60W2550/402 ,  G08G1/167

摘要： A method for selecting an anchor lane for tracking in a vehicle lane tracking system. Digital map data and leading vehicle trajectory data are used to predict lane information ahead of a vehicle. Left and right lane boundary markers are also detected, where available, using a vision system. The lane marker data from the vision system is combined with the lane information from the digital map data and the leading vehicle trajectory data in a lane curvature fusion calculation. The left and right lane marker data from the vision system are also evaluated for conditions such as parallelism and sudden jumps in offsets, while considering the presence of entrance or exit lanes as indicated by the map data. An anchor lane for tracking is selected based on the evaluation of the vision system data, using either the fused curvature calculation or the digital map and leading vehicle trajectory data.

摘要翻译： 一种用于在车道跟踪系统中选择用于跟踪的锚车道的方法。 数字地图数据和前导车辆轨迹数据用于预测车辆前方的车道信息。 还可以使用视觉系统检测左右车道边界标记。 来自视觉系统的车道标记数据与车道曲线融合计算中的数字地图数据和前车辆轨迹数据的车道信息相结合。 考虑到地图数据所示的入口或出口通道的存在，还可以评估来自视觉系统的左右车道标记数据，例如平行度和偏移突然跳跃等条件。 基于对视觉系统数据的评估，使用融合曲率计算或数字地图和前导车辆轨迹数据来选择用于跟踪的锚定车道。

公开(公告)号：US20130236047A1

公开(公告)日：2013-09-12

申请号：US13413861

申请日：2012-03-07

申请人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

发明人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

IPC分类号： G06K9/00

CPC分类号： G01S13/726 ,  G01S13/867 ,  G01S13/931 ,  G01S2013/9375 ,  G06K9/00805 ,  G06T1/0007

摘要： A method of associating targets from at least two object detection systems. An initial prior correspondence matrix is generated based on prior target data from a first object detection system and a second object detection system. Targets are identified in a first field-of-view of the first object detection system based on a current time step. Targets are identified in a second field-of-view of the second object detection system based on the current time step. The prior correspondence matrix is adjusted based on respective targets entering and leaving the respective fields-of-view. A posterior correspondence matrix is generated as a function of the adjusted prior correspondence matrix. A correspondence is identified in the posterior correspondence matrix between a respective target of the first object detection system and a respective target of the second object detection system.

摘要翻译： 将来自至少两个物体检测系统的目标相关联的方法。 基于来自第一对象检测系统和第二对象检测系统的先前目标数据生成初始先前对应矩阵。 基于当前时间步长，在第一对象检测系统的第一视场中识别目标。 基于当前时间步长，在第二对象检测系统的第二视场中识别目标。 基于进入和离开相应视场的各个目标来调整先前的对应矩阵。 作为调整后的对应矩阵的函数产生后向对应矩阵。 在第一对象检测系统的相应目标和第二对象检测系统的相应目标之间的后向对应矩阵中识别对应关系。

公开(公告)号：US09228833B2

公开(公告)日：2016-01-05

申请号：US13535538

申请日：2012-06-28

申请人： Shuqing Zeng

发明人： Shuqing Zeng

IPC分类号： G01C11/06 ,  H04N13/02 ,  H04N13/00 ,  G06K9/00

CPC分类号： G01C11/06 ,  G06K9/00791 ,  H04N13/106 ,  H04N2013/0092

摘要： A method for tracking a target object utilizing a binocular system includes capturing first and second images, the first image captured from a first camera device and the second image captured from a second camera device. A plurality of image patches are applied to the first and second images and a plurality of detection costs each associated with respective ones of the image patches applied to the first and second images is determined. A plurality of matching costs each corresponding to respective ones of selected matching pairs of image patches between the first and second images is determined. At least one cost flow path is determined from a source vertex of the first image to a sink vertex of the second image based on the detection costs and the matching costs and the target object is tracked based on the at least one cost flow path.

摘要翻译： 利用双目系统跟踪目标对象的方法包括捕获第一和第二图像，从第一相机装置捕获的第一图像和从第二相机装置捕获的第二图像。 多个图像补丁被应用于第一和第二图像，并且确定与应用于第一和第二图像的各个图像补丁相关联的多个检测成本。 确定每个对应于第一和第二图像之间的所选择的匹配对的匹配对中的各个匹配成本的多个匹配成本。 基于检测成本和匹配成本，从第一图像的源顶点到第二图像的汇点顶点确定至少一个成本流路径，并且基于至少一个成本流路径跟踪目标对象。

公开(公告)号：US09140792B2

公开(公告)日：2015-09-22

申请号：US13151064

申请日：2011-06-01

申请人： Shuqing Zeng

发明人： Shuqing Zeng

IPC分类号： G01C21/32 ,  G01S17/02 ,  G01S17/42 ,  G01S19/46 ,  G01S19/45

CPC分类号： G01S17/023 ,  G01C21/32 ,  G01S17/026 ,  G01S17/42 ,  G01S19/45 ,  G01S19/46

摘要： A method and system may determine the estimated location of a vehicle, measure a location of an object relative to the vehicle using a sensor associated with the vehicle, and determine an updated vehicle location using the measured relative object location in conjunction with previously stored object locations. The estimated vehicle location may be determined using a system different from that associated with the sensor, for example a GPS system. The object location may be measured relative to a sub-map corresponding to the location of the vehicle.

摘要翻译： 方法和系统可以确定车辆的估计位置，使用与车辆相关联的传感器测量对象相对于车辆的位置，并且使用所测量的相对对象位置结合先前存储的对象位置来确定更新的车辆位置 。 可以使用与传感器（例如GPS系统）相关联的系统不同的系统来确定估计的车辆位置。 可以相对于对应于车辆位置的子地图来测量物体位置。

公开(公告)号：US08392074B2

公开(公告)日：2013-03-05

申请号：US12605049

申请日：2009-10-23

申请人： Shuqing Zeng ,  Sanjeev M. Naik

发明人： Shuqing Zeng ,  Sanjeev M. Naik

IPC分类号： G06F19/00

CPC分类号： B60J3/0204

摘要： A system and method for controlling a vehicle sun visor that uses commonly existing onboard sensors and systems to provide all necessary inputs. The method uses GPS and solar almanac data to determine the location of the sun relative to the vehicle, driver side view mirror angle data to determine the position of the driver's eyes within the vehicle, and an existing outside light metering device to determine whether the sun is actually shining on the vehicle, and uses this information to calculate the optimum position of the sun visor. If a forward-looking camera is available on the vehicle, camera images can be used to improve the estimate of the sun position relative to the vehicle.

摘要翻译： 一种用于控制车辆遮阳板的系统和方法，其使用通常存在的车载传感器和系统来提供所有必要的输入。 该方法使用GPS和太阳年历数据来确定太阳相对于车辆的位置，驾驶员侧视角角度数据以确定驾驶员在车内的位置，以及现有的外部光计量装置，以确定太阳 实际上照亮车辆，并使用这些信息来计算遮阳板的最佳位置。 如果在车上可以使用前视摄像机，则摄像机图像可用于改善相对于车辆的太阳位置的估计。

公开(公告)号：US08260539B2

公开(公告)日：2012-09-04

申请号：US12778766

申请日：2010-05-12

申请人： Shuqing Zeng

发明人： Shuqing Zeng

IPC分类号： G06F17/10

CPC分类号： G01S17/42 ,  B60W30/0956 ,  G01S7/4808 ,  G01S17/89 ,  G01S17/936 ,  G08G1/165 ,  G08G1/166

摘要： A method and system for detecting and tracking objects near a vehicle using a three dimensional laser rangefinder. The method receives points from the laser rangefinder, where the points represent locations in space where the rangefinder senses that some object exists. An algorithm first estimates the location of a ground plane, based on a previous ground plane location, data from onboard sensors, and an eigenvector calculation applied to the point data. Next, a plan view occupancy map and elevation map are computed for stationary objects, based on point data in relation to the ground plane. Finally, dynamic objects are detected and tracked, sensing objects which are moving, such as other vehicles, pedestrians, and animals. The output of the method is a set of stationary and dynamic objects, including their shape, range, and velocity. This output can be used by downstream applications, such as collision avoidance or semi-autonomous driving systems.

摘要翻译： 一种使用三维激光测距仪来检测和跟踪车辆附近的物体的方法和系统。 该方法从激光测距仪接收点，其中点表示测距仪感测到某物体存在的空间中的位置。 算法首先基于先前的接地平面位置，来自板上传感器的数据以及应用于点数据的特征向量计算来估计接地平面的位置。 接下来，基于与地平面相关的点数据，针对静止物体计算平面图占用地图和仰角图。 最后，检测和跟踪动态对象，感测正在移动的物体，例如其他车辆，行人和动物。 该方法的输出是一组静态和动态对象，包括它们的形状，范围和速度。 该输出可以被下游应用使用，例如避碰或半自主驾驶系统。