公开(公告)号：US20160224850A1

公开(公告)日：2016-08-04

申请号：US15094776

申请日：2016-04-08

Applicant: Google Inc.

Inventor： David Harrison Silver ,  Jonathan Baldwin Dowdall ,  David Ian Ferguson

IPC: G06K9/00 ,  G01S13/04 ,  G06K9/62 ,  G01S17/02 ,  G01S17/93 ,  G01S19/13 ,  G05D1/00 ,  G01S13/93

CPC classification number: G06K9/00805 ,  G01S13/04 ,  G01S13/931 ,  G01S17/026 ,  G01S17/936 ,  G01S19/13 ,  G01V11/00 ,  G05D1/0088 ,  G05D1/021 ,  G05D1/0246 ,  G05D2201/0213 ,  G06K9/6215 ,  G06K9/6277 ,  G06K9/628

Abstract: A vehicle is provided that may distinguish between dynamic obstacles and static obstacles. Given a detector for a class of static obstacles or objects, the vehicle may receive sensor data indicative of an environment of the vehicle. When a possible object is detected in a single frame, a location of the object and a time of observation of the object may be compared to previous observations. Based on the object being observed a threshold number of times, in substantially the same location, and within some window of time, the vehicle may accurately detect the presence of the object and reduce any false detections.

Abstract translation: 提供可以区分动态障碍物和静态障碍物的车辆。 给定一类静态障碍物或物体的检测器，车辆可以接收指示车辆环境的传感器数据。 当在单个帧中检测到可能的对象时，可以将对象的位置和对象的观察时间与先前的观察进行比较。 基于所观察到的物体在基本上相同的位置，并且在一些时间窗口内的阈值次数，车辆可以准确地检测物体的存在并减少任何错误检测。

公开(公告)号：US09395192B1

公开(公告)日：2016-07-19

申请号：US14135935

申请日：2013-12-20

Applicant: Google Inc.

Inventor： David Harrison Silver ,  David Ian Ferguson

IPC: G01C21/26

CPC classification number: G01C21/26 ,  G06K9/00798

Abstract: Methods and systems for road boundary and lane tracing are described herein. In an example implementation, a computing system of a vehicle may receive boundary data associated with a road and may determine edge data representative of edges of the boundaries. A given edge may indicate a discontinuity between a boundary and a characteristic of the road. The computing system may modify the edge data based on a position and orientation of respective edges to combine edges positioned substantially in parallel and within a threshold distance to each other. The computing system may adjust boundary data based on the modified edge data so as to extend a given boundary that includes a combined edge and may determine whether extended boundary data substantially matches road data indicated by a map. In addition, the computing system may provide an estimation of projections of boundaries ahead of the vehicle on the road.

Abstract translation: 本文描述了道路边界和车道追踪的方法和系统。 在示例实现中，车辆的计算系统可以接收与道路相关联的边界数据，并且可以确定表示边界边缘的边缘数据。 给定的边缘可以指示边界和道路特征之间的不连续性。 计算系统可以基于相应边缘的位置和取向来修改边缘数据，以组合基本上并行定位并且彼此之间的阈值距离内的边缘。 计算系统可以基于修改的边缘数据来调整边界数据，以便延伸包括组合边缘的给定边界，并且可以确定扩展边界数据是否基本上匹配由地图指示的道路数据。 此外，计算系统可以提供在道路上的车辆前方的边界的预测的估计。

公开(公告)号：US09199641B2

公开(公告)日：2015-12-01

申请号：US14629344

申请日：2015-02-23

Applicant: Google Inc.

Inventor： David Ian Ferguson ,  Dirk Haehnel ,  Ian Mahon

IPC: B60W30/09 ,  G08G1/16 ,  G05D1/00 ,  G05D1/02 ,  G01S17/93 ,  G06K9/00 ,  B25J9/02 ,  B25J9/16 ,  B60W30/08 ,  B60W30/095 ,  B25J19/02

CPC classification number: B60W30/08 ,  B25J9/16 ,  B25J9/1697 ,  B25J19/023 ,  B60W30/09 ,  B60W30/0956 ,  B60W30/18163 ,  B60W40/06 ,  B60W2420/42 ,  G01C21/28 ,  G01C21/3461 ,  G01S7/4808 ,  G01S13/86 ,  G01S13/865 ,  G01S13/867 ,  G01S17/023 ,  G01S17/89 ,  G01S17/936 ,  G01S2013/9346 ,  G01S2013/935 ,  G01S2013/9371 ,  G01S2013/9375 ,  G01S2013/9382 ,  G01S2013/9389 ,  G01S2013/9396 ,  G05D1/0088 ,  G05D1/021 ,  G05D1/0246 ,  G05D1/0251 ,  G05D1/027 ,  G05D2201/0213 ,  G06K9/00664 ,  G06K9/00798 ,  G06K9/00805 ,  G06K9/00818 ,  G08G1/16 ,  G08G1/165 ,  G08G1/166 ,  G08G1/167 ,  Y10S901/47

Abstract: Methods and systems for construction zone object detection are described. A computing device may be configured to receive, from a LIDAR, a 3D point cloud of a road on which a vehicle is travelling. The 3D point cloud may comprise points corresponding to light reflected from objects on the road. Also, the computing device may be configured to determine sets of points in the 3D point cloud representing an area within a threshold distance from a surface of the road. Further, the computing device may be configured to identify construction zone objects in the sets of points. Further, the computing device may be configured to determine a likelihood of existence of a construction zone, based on the identification. Based on the likelihood, the computing device may be configured to modify a control strategy of the vehicle; and control the vehicle based on the modified control strategy.

Abstract translation: 描述了施工区物体检测的方法和系统。 计算设备可以被配置为从LIDAR接收车辆行驶的道路的3D点云。 3D点云可以包括对应于从道路上的物体​​反射的光的点。 此外，计算设备可以被配置为确定3D点云中的点，其表示距离道路表面的阈值距离内的区域。 此外，计算设备可以被配置为识别该组点中的构造区域对象。 此外，计算设备可以被配置为基于识别来确定建筑区域的存在的可能性。 基于可能性，计算设备可以被配置为修改车辆的控制策略; 并根据修改的控制策略控制车辆。

公开(公告)号：US09081385B1

公开(公告)日：2015-07-14

申请号：US13723358

申请日：2012-12-21

Applicant: Google Inc.

Inventor： David Ian Ferguson ,  Turgay Senlet

IPC: G01C22/00 ,  G05D1/02

CPC classification number: G05D1/0246 ,  G06K9/00798

Abstract: Methods and systems for lane boundary detection using images are described. A computing device may be configured to receive, from an image-capture device coupled to a vehicle, an image of a road of travel of the vehicle. The computing device may be configured to identify a pixel in the image based on an intensity of the pixel and a comparison of the intensity of the pixel to respective intensities of neighboring pixels. Based on the intensity of the pixel and the comparison, the computing device may be configured to determine a likelihood that the pixel belongs to a portion of the image depicting a lane marker on the road. Based at least on the likelihood, the computing device may be configured to and provide instructions to control the vehicle.

Abstract translation: 描述使用图像进行车道边界检测的方法和系统。 计算设备可以被配置为从耦合到车辆的图像捕获设备接收车辆行驶道路的图像。 计算设备可以被配置为基于像素的强度和像素的强度与相邻像素的相应强度的比较来识别图像中的像素。 基于像素的强度和比较，计算设备可以被配置为确定像素属于描绘道路上的车道标记的图像的一部分的可能性。 至少基于可能性，计算设备可以被配置为并提供控制车辆的指令。