公开(公告)号：US20150379869A1

公开(公告)日：2015-12-31

申请号：US14843705

申请日：2015-09-02

Applicant: Google Inc.

Inventor： David I. Ferguson ,  Bradley Templeton

IPC: G08G1/00

CPC classification number: G06K9/00825 ,  B60W40/00 ,  G08G1/00 ,  G08G1/09623 ,  G08G1/09626 ,  G08G1/096716 ,  G08G1/096725 ,  G08G1/096758 ,  G08G1/096775 ,  G08G1/096791

Abstract: Methods and devices for using a relationship between activities of different traffic signals in a network to improve traffic signal state estimation are disclosed. An example method includes determining that a vehicle is approaching an upcoming traffic signal. The method may further include determining a state of one or more traffic signals other than the upcoming traffic signal. Additionally, the method may also include determining an estimate of a state of the upcoming traffic signal based on a relationship between the state of the one or more traffic signals other than the upcoming traffic signal and the state of the upcoming traffic signal.

Abstract translation: 公开了在网络中使用不同业务信号的活动之间的关系以改善业务信号状态估计的方法和装置。 示例性方法包括确定车辆正在接近即将到来的交通信号。 该方法还可以包括确定除即将到来的业务信号之外的一个或多个业务信号的状态。 另外，该方法还可以包括基于即将到来的业务信号之外的一个或多个业务信号的状态与即将到来的业务信号的状态之间的关系来确定即将到来的业务信号的状态的估计。

公开(公告)号：US09213337B1

公开(公告)日：2015-12-15

申请号：US14341824

申请日：2014-07-27

Applicant: Google Inc.

Inventor： David I. Ferguson

IPC: G05D1/00 ,  G05D1/02

CPC classification number: G05D1/0214 ,  G01S13/86 ,  G01S13/865 ,  G01S13/931 ,  G01S17/023 ,  G01S17/936 ,  G01S2013/936 ,  G05D1/0227 ,  G05D1/027 ,  G05D1/0272 ,  G05D1/0278

Abstract: In an example implementation, an autonomous vehicle is configured to detect closures and lane shifts in a lane of travel. The vehicle is configured to operate in an autonomous mode and determine a presence of an obstacle substantially positioned in a lane of travel of the vehicle using a sensor. The lane of travel has a first side, a second side, and a center, and the obstacle is substantially positioned on the first side. The autonomous vehicle includes a computer system. The computer system determines a lateral distance between the obstacle and the center, compares the lateral distance to a pre-determined threshold, and provides instructions to control the autonomous vehicle based on the comparison.

Abstract translation: 在示例实现中，自主车辆被配置为检测行驶车道中的关闭和车道偏移。 车辆被配置为以自主模式操作并且使用传感器确定基本上位于车辆行驶通道中的障碍物的存在。 行车道具有第一侧，第二侧和中心，并且障碍物基本上位于第一侧。 自主车辆包括计算机系统。 计算机系统确定障碍物与中心之间的横向距离，将横向距离与预定阈值进行比较，并提供基于比较来控制自主车辆的指令。

公开(公告)号：US09558584B1

公开(公告)日：2017-01-31

申请号：US13952853

申请日：2013-07-29

Applicant: Google Inc.

Inventor： Wan-Yen Lo ,  David I. Ferguson

IPC: G06F1/00 ,  G06T15/20

CPC classification number: G06K9/00798 ,  B60R1/00 ,  B60R11/04 ,  B60R2300/301 ,  B60R2300/8093 ,  B60W30/00 ,  G01C21/005 ,  G05D1/0088 ,  G05D1/0238 ,  G05D1/0246 ,  G05D1/0274 ,  G06K9/6267 ,  G06T7/50 ,  G06T7/70 ,  G06T15/20 ,  G06T15/205 ,  G06T17/10 ,  G06T2207/30256

Abstract: An example method may include determining a three-dimensional (3D) location of a plurality of reference points in an environment, receiving a two-dimensional (2D) image of a portion of the environment that contains an object, selecting certain reference points from the plurality of reference points that form a polygon when projected into the 2D image that contains at least a portion of the object, determining an intersection point of a ray directed toward the object and a 3D polygon formed by the selected reference points, and based on the intersection point of the ray directed toward the object and the 3D polygon formed by the selected reference points, determining a 3D location of the object in the environment.

Abstract translation: 示例性方法可以包括确定环境中的多个参考点的三维（3D）位置，接收包含对象的环境的一部分的二维（2D）图像，从 多个参考点，当投影到包含对象的至少一部分的2D图像中时形成多边形，确定朝向对象的射线的交点和由所选择的参考点形成的3D多边形，并且基于 指向对象的射线的交点和由所选择的参考点形成的3D多边形，确定对象在环境中的3D位置。

公开(公告)号：US20150355640A1

公开(公告)日：2015-12-10

申请号：US14828700

申请日：2015-08-18

Applicant: Google Inc.

Inventor： David I. Ferguson ,  Donald Jason Burnette

IPC: G05D1/00 ,  G01C21/26

CPC classification number: G05D1/0214 ,  B60W10/04 ,  B60W10/20 ,  B60W30/00 ,  B60W30/143 ,  B60W2710/20 ,  B60W2720/106 ,  G01C21/26 ,  G01C21/32 ,  G01C21/3407 ,  G01S19/42 ,  G01S2013/936 ,  G05D1/00 ,  G05D1/0088 ,  G05D1/0236 ,  G05D1/0246 ,  G05D1/0255 ,  G05D1/0257 ,  G05D1/0276 ,  G05D2201/0213 ,  G06K9/00 ,  G06K9/00798 ,  G06K9/00818

Abstract: Aspects of the present disclosure relate to differentiating between active and inactive construction zones. In one example, this may include identifying a construction object associated with a construction zone. The identified construction object may be used to map the area of the construction zone. Detailed map information may then be used to classify the activity of the construction zone. The area of the construction zone and the classification may be added to the detailed map information. Subsequent to adding the construction zone and the classification to the detailed map information, the construction object (or another construction object) may be identified. The location of the construction object may be used to identify the construction zone and classification from the detailed map information. The classification of the classification may be used to operate a vehicle having an autonomous mode.

Abstract translation: 本公开的方面涉及区分主动和非活动结构区域。 在一个示例中，这可以包括识别与施工区域相关联的施工对象。 所识别的施工对象可用于映射施工区域的区域。 然后可以使用详细的地图信息来对施工区域的活动进行分类。 施工区的区域和分类可以添加到详细的地图信息中。 在将施工区域和分类添加到详细地图信息之后，可以识别施工对象（或另一施工对象）。 施工对象的位置可以用于从详细的地图信息中识别施工区域和分类。 分类的分类可以用于操作具有自主模式的车辆。

公开(公告)号：US09026303B1

公开(公告)日：2015-05-05

申请号：US14480377

申请日：2014-09-08

Applicant: Google Inc.

Inventor： David I. Ferguson ,  Abhijit Ogale

IPC: G05D1/00

CPC classification number: G05D1/00 ,  G05D1/0214 ,  G05D1/0246 ,  G05D2201/0213 ,  G06K9/00805

Abstract: An autonomous vehicle may be configured to detect objects based on known structures of an environment. The vehicle may be configured to obtain image data from a sensor and be configured to operate in an autonomous mode. The image data may include data indicative of a known structure in the environment. The vehicle may include a computer system. The computer system may determine, based on a first portion of the image data, information indicative of an appearance of the known structure. The computer system may determine, based on a second portion of the image data, information indicative of an appearance of an unknown object in the environment. The computer system may also compare the information indicative of the appearance of the known structure with the information indicative of the appearance of the unknown object and provide instructions to control the vehicle in the autonomous mode based on the comparison.

Abstract translation: 自主车辆可以被配置为基于环境的已知结构来检测对象。 车辆可以被配置为从传感器获得图像数据并且被配置为以自主模式操作。 图像数据可以包括指示环境中的已知结构的数据。 车辆可以包括计算机系统。 计算机系统可以基于图像数据的第一部分来确定指示已知结构的外观的信息。 计算机系统可以基于图像数据的第二部分来确定指示环境中的未知对象的外观的信息。 计算机系统还可以将表示已知结构的外观的信息与指示未知对象的外观的信息进行比较，并且基于比较提供以自主模式控制车辆的指令。

公开(公告)号：US08903591B1

公开(公告)日：2014-12-02

申请号：US14164565

申请日：2014-01-27

Applicant: Google Inc.

Inventor： David I. Ferguson ,  Dmitri Dolgov

IPC: G01C22/00 ,  G05D1/02

CPC classification number: G05D1/0212 ,  B62D15/0285 ,  G05D1/0274 ,  G05D2201/0213

Abstract: A vehicle can be controlled in a first autonomous mode of operation by at least navigating the vehicle based on map data. Sensor data can be obtained using one or more sensors of the vehicle. The sensor data can be indicative of an environment of the vehicle. An inadequacy in the map data can be detected by at least comparing the map data to the sensor data. In response to detecting the inadequacy in the map data, the vehicle can be controlled in a second autonomous mode of operation and a user can be prompted to switch to a manual mode of operation. The vehicle can be controlled in the second autonomous mode of operation by at least obtaining additional sensor data using the one or more sensors of the vehicle and navigating the vehicle based on the additional sensor data.

公开(公告)号：US08725342B2

公开(公告)日：2014-05-13

申请号：US13944877

申请日：2013-07-18

Applicant: Google Inc.

Inventor： David I. Ferguson ,  Dmitri Dolgov

IPC: G01C22/00 ,  G06K9/00 ,  B60Q1/22

CPC classification number: G05D1/0212 ,  B60W30/12 ,  B60W50/029 ,  B60W2550/14 ,  B60W2550/306 ,  B60W2550/308 ,  G05D1/0289 ,  G06K9/00798 ,  G06K9/00805

Abstract: Methods and devices for controlling a vehicle in an autonomous mode are disclosed. In one aspect, an example method is disclosed that includes obtaining lane information that provides an estimated location of a lane of a road on which a vehicle is traveling. The example method further includes determining that the lane information has become unavailable or unreliable and, in response, using a sensor to monitor a first distance and a second distance between the vehicle and a neighboring vehicle, determining first and second relative positions of the neighboring vehicle based on the first and second distances, respectively, and, based on the first and second relative positions, determining an estimated path of the neighboring vehicle. The example method further includes, based on the estimated path, determining an updated estimated location of the lane, and controlling the vehicle based on the updated estimated location of the lane.

Abstract translation: 公开了以自主模式控制车辆的方法和装置。 一方面，公开了一种示例性方法，其包括获取提供车辆行驶的道路的车道的估计位置的车道信息。 示例性方法还包括确定车道信息变得不可用或不可靠，并且作为响应，使用传感器监测车辆和相邻车辆之间的第一距离和第二距离，确定相邻车辆的第一和第二相对位置 分别基于第一和第二距离，并且基于第一和第二相对位置确定相邻车辆的估计路径。 该示例方法还包括：基于估计的路径，确定车道的更新的估计位置，以及基于车道的更新的估计位置来控制车辆。

公开(公告)号：US20170278400A1

公开(公告)日：2017-09-28

申请号：US15468574

申请日：2017-03-24

Applicant: Google Inc.

Inventor： David I. Ferguson

IPC: G08G1/16

CPC classification number: G08G1/166

Abstract: A method and apparatus are provided for determining whether a driving environment has changed relative to previously stored information about the driving environment. The apparatus may include an autonomous driving computer system configured to detect one or more vehicles in the driving environment, and determine corresponding trajectories for those detected vehicles. The autonomous driving computer system may then compare the determined trajectories to an expected trajectory of a hypothetical vehicle in the driving environment. Based on the comparison, the autonomous driving computer system may determine whether the driving environment has changed and/or a probability that the driving environment has changed, relative to the previously stored information about the driving environment.

公开(公告)号：US09654738B1

公开(公告)日：2017-05-16

申请号：US13960969

申请日：2013-08-07

Applicant: Google Inc.

Inventor： David I. Ferguson ,  Abhijit S. Ogale

IPC: H04N7/18 ,  B60R1/00 ,  G06K9/00

CPC classification number: H04N7/18 ,  G06K9/00805 ,  G06K9/00825

Abstract: The invention relates to collecting different images using different camera parameters. As an example, a single camera may capture two different types of images: a dark exposure for light emitting objects and a normal exposure for passive objects. The camera may first capture an image. This first image may be processed to determine the ideal camera settings for capturing the average intensity of the environment. Fixed offset values may be added to these ideal camera settings and the dark exposure may be captured. The ideal camera settings are then used to capture a normal exposure, which in turn may be processed to determine new ideal camera settings. Again, the fixed offset values may be added to the new ideal camera settings and a dark exposure is captured. This process may repeat continuously and periodically, and the resulting images may be processed to identify emissive and passive objects.

公开(公告)号：US09633564B2

公开(公告)日：2017-04-25

申请号：US13628905

申请日：2012-09-27

Applicant: Google Inc.

Inventor： David I. Ferguson

IPC: G08G1/00 ,  G08G1/16

CPC classification number: G08G1/166

Abstract: A method and apparatus are provided for determining whether a driving environment has changed relative to previously stored information about the driving environment. The apparatus may include an autonomous driving computer system configured to detect one or more vehicles in the driving environment, and determine corresponding trajectories for those detected vehicles. The autonomous driving computer system may then compare the determined trajectories to an expected trajectory of a hypothetical vehicle in the driving environment. Based on the comparison, the autonomous driving computer system may determine whether the driving environment has changed and/or a probability that the driving environment has changed, relative to the previously stored information about the driving environment.