公开(公告)号：US08954217B1

公开(公告)日：2015-02-10

申请号：US14220653

申请日：2014-03-20

Applicant: Google Inc.

Inventor： Michael Steven Montemerlo ,  Hyman Jack Murveit ,  Christopher Paul Urmson ,  Dmitri A. Dolgov ,  Philip Nemec

IPC: G05D1/00 ,  B60W30/00

CPC classification number: G05D1/0061 ,  B60W30/00 ,  G05D2201/0213

Abstract: Aspects of the disclosure relate generally to determining whether an autonomous vehicle should be driven in an autonomous or semiautonomous mode (where steering, acceleration, and braking are controlled by the vehicle's computer). For example, a computer may maneuver a vehicle in an autonomous or a semiautonomous mode. The computer may continuously receive data from one or more sensors. This data may be processed to identify objects and the characteristics of the objects. The detected objects and their respective characteristics may be compared to a traffic pattern model and detailed map information. If the characteristics of the objects deviate from the traffic pattern model or detailed map information by more than some acceptable deviation threshold value, the computer may generate an alert to inform the driver of the need to take control of the vehicle or the computer may maneuver the vehicle in order to avoid any problems.

Abstract translation: 本公开的方面通常涉及确定自主车辆是否应以自主或半自主模式（其中转向，加速和制动由车辆的计算机控制）驱动。 例如，计算机可以以自主或半自主的方式操纵车辆。 计算机可以连续地从一个或多个传感器接收数据。 可以处理该数据以识别对象和对象的特征。 可以将检测到的对象及其各自的特征与交通模式模型和详细地图信息进行比较。 如果物体的特征偏离交通模式模型或详细地图信息超过一些可接受的偏差阈值，则计算机可以产生警报以通知驾驶员需要控制车辆，或者计算机可以操纵 车辆为了避免任何问题。

公开(公告)号：US20170092131A1

公开(公告)日：2017-03-30

申请号：US15377139

申请日：2016-12-13

Applicant: Google Inc.

Inventor： Nathaniel Fairfield ,  Joshua Seth Herbach ,  Andrew Hughes Chatham ,  Michael Steven Montemerlo

IPC: G08G1/16 ,  B60W30/00 ,  G08G1/00 ,  G05D1/00 ,  G05D1/02

CPC classification number: G08G1/161 ,  B60W30/00 ,  B60W2050/008 ,  G05D1/0088 ,  G05D1/0287 ,  G08G1/0112 ,  G08G1/096725 ,  G08G1/096741 ,  G08G1/096775 ,  G08G1/22

Abstract: Example systems and methods allow for reporting and sharing of information reports relating to driving conditions within a fleet of autonomous vehicles. One example method includes receiving information reports relating to driving conditions from a plurality of autonomous vehicles within a fleet of autonomous vehicles. The method may also include receiving sensor data from a plurality of autonomous vehicles within the fleet of autonomous vehicles. The method may further include validating some of the information reports based at least in part on the sensor data. The method may additionally include combining validated information reports into a driving information map. The method may also include periodically filtering the driving information map to remove outdated information reports. The method may further include providing portions of the driving information map to autonomous vehicles within the fleet of autonomous vehicles.

公开(公告)号：US09081383B1

公开(公告)日：2015-07-14

申请号：US14161295

申请日：2014-01-22

Applicant: Google Inc.

Inventor： Michael Steven Montemerlo ,  John Tisdale ,  Vadim Furman

IPC: G05D1/02 ,  G01C21/00 ,  G01C21/36

CPC classification number: G05D1/0274 ,  B60W30/00 ,  G01C21/005 ,  G01C21/3602 ,  G05D1/0212 ,  G05D1/0246 ,  G05D1/0248 ,  G06K9/00798 ,  G08G1/00 ,  G08G1/164

Abstract: Systems and methods are provided that may optimize basic models of an intersection in a roadway with high intensity image data of the intersection of the roadway. More specifically, parameters that define the basic model of the intersection in the roadway may be adjusted to more accurately define the intersection. For example, by comparing a shape of the intersection predicted by the basic model with extracted curbs and lane boundaries from elevation and intensity maps, the intersection parameters can be optimized to match real intersection-features in the environment. Once the optimal intersection parameters have been found, roadgraph features describing the intersection may be extracted.

Abstract translation: 提供了系统和方法，可以优化巷道交叉口的基本模型，并具有巷道交叉口的高强度图像数据。 更具体地，可以调整定义道路中的交叉路口的基本模型的参数以更准确地定义交叉点。 例如，通过将由基本模型预测的交点的形状与提取的路标和车道边界的高程和强度图进行比较，可以优化交点参数以匹配环境中的实际交叉特征。 一旦找到了最佳的交点参数，就可以提取描述十字路口的路标特征。

公开(公告)号：US08983781B2

公开(公告)日：2015-03-17

申请号：US13623397

申请日：2012-09-20

Applicant: Google Inc.

Inventor： Christopher Paul Urmson ,  Michael Steven Montemerlo ,  Jiajun Zhu

IPC: G01W1/00 ,  G01W1/02 ,  G01W1/10 ,  G01S17/89

Abstract: Aspects of the disclosure relate generally to detecting road weather conditions. Vehicle sensors including a laser, precipitation sensors, and/or camera may be used to detect information such as the brightness of the road, variations in the brightness of the road, brightness of the world, current precipitation, as well as the detected height of the road. Information received from other sources such as networked based weather information (forecasts, radar, precipitation reports, etc.) may also be considered. The combination of the received and detected information may be used to estimate the probability of precipitation such as water, snow or ice in the roadway. This information may then be used to maneuver an autonomous vehicle (for steering, accelerating, or braking) or identify dangerous situations.

公开(公告)号：US20140324268A1

公开(公告)日：2014-10-30

申请号：US14324470

申请日：2014-07-07

Applicant: Google Inc.

Inventor： Michael Steven Montemerlo ,  Dmitri A. Dolgov ,  Christopher Paul Urmson

IPC: G05D1/02

CPC classification number: G06K9/00201 ,  B60R1/00 ,  B60R2300/30 ,  B60W30/08 ,  B60W30/186 ,  B60W2050/0292 ,  B60W2530/14 ,  B60W2550/22 ,  B62D6/00 ,  G01C21/3617 ,  G05D1/0055 ,  G05D1/0088 ,  G05D1/021 ,  G05D1/0214 ,  G05D1/024 ,  G05D1/0246 ,  G05D1/0257 ,  G05D1/0274 ,  G05D1/0276 ,  G05D1/0278 ,  G05D2201/0213 ,  G06K9/00791 ,  G06K9/00798 ,  G06K9/00805 ,  G06K9/3241 ,  G06T7/0044 ,  G06T7/0057 ,  G06T7/20 ,  G06T7/223 ,  G06T7/231 ,  G06T2207/10004 ,  G06T2207/10028 ,  G06T2207/30236 ,  G06T2207/30252 ,  G06T2207/30261

Abstract: A roadgraph may include a graph network of information such as roads, lanes, intersections, and the connections between these features. The roadgraph may also include one or more zones associated with particular rules. The zones may include locations where driving is typically challenging such as merges, construction zones, or other obstacles. In one example, the rules may require an autonomous vehicle to alert a driver that the vehicle is approaching a zone. The vehicle may thus require a driver to take control of steering, acceleration, deceleration, etc. In another example, the zones may be designated by a driver and may be broadcast to other nearby vehicles, for example using a radio link or other network such that other vehicles may be able to observer the same rule at the same location or at least notify the other vehicle's drivers that another driver felt the location was unsafe for autonomous driving.

Abstract translation: 道路图可以包括信息的图形网络，例如道路，车道，交叉路口以及这些特征之间的连接。 道路图也可以包括与特定规则相关联的一个或多个区域。 这些区域可以包括驾驶通常是具有挑战性的位置，例如合并，建筑区域或其他障碍物。 在一个示例中，规则可能需要自主车辆来警告驾驶员车辆正在接近区域。 因此，车辆可能需要驾驶员来控制转向，加速，减速等。在另一示例中，区域可以由驾驶员指定，并且可以广播到其他附近的车辆，例如使用无线电链路或其他网络 其他车辆可能能够在相同的位置观察相同的规则，或者至少通知另一车辆的司机，另一司机认为该位置对于自主驾驶是不安全的。

公开(公告)号：US08825264B2

公开(公告)日：2014-09-02

申请号：US13932090

申请日：2013-07-01

Applicant: Google Inc.

Inventor： Michael Steven Montemerlo ,  Dmitri A. Dolgov ,  Christopher Paul Urmson

IPC: G05D1/02

CPC classification number: G06K9/00201 ,  B60R1/00 ,  B60R2300/30 ,  B60W30/08 ,  B60W30/186 ,  B60W2050/0292 ,  B60W2530/14 ,  B60W2550/22 ,  B62D6/00 ,  G01C21/3617 ,  G05D1/0055 ,  G05D1/0088 ,  G05D1/021 ,  G05D1/0214 ,  G05D1/024 ,  G05D1/0246 ,  G05D1/0257 ,  G05D1/0274 ,  G05D1/0276 ,  G05D1/0278 ,  G05D2201/0213 ,  G06K9/00791 ,  G06K9/00798 ,  G06K9/00805 ,  G06K9/3241 ,  G06T7/0044 ,  G06T7/0057 ,  G06T7/20 ,  G06T7/223 ,  G06T7/231 ,  G06T2207/10004 ,  G06T2207/10028 ,  G06T2207/30236 ,  G06T2207/30252 ,  G06T2207/30261

Abstract: A roadgraph may include a graph network of information such as roads, lanes, intersections, and the connections between these features. The roadgraph may also include one or more zones associated with particular rules. The zones may include locations where driving is typically challenging such as merges, construction zones, or other obstacles. In one example, the rules may require an autonomous vehicle to alert a driver that the vehicle is approaching a zone. The vehicle may thus require a driver to take control of steering, acceleration, deceleration, etc. In another example, the zones may be designated by a driver and may be broadcast to other nearby vehicles, for example using a radio link or other network such that other vehicles may be able to observer the same rule at the same location or at least notify the other vehicle's drivers that another driver felt the location was unsafe for autonomous driving.

Abstract translation: 道路图可以包括信息的图形网络，例如道路，车道，交叉路口以及这些特征之间的连接。 道路图也可以包括与特定规则相关联的一个或多个区域。 这些区域可以包括驾驶通常是具有挑战性的位置，例如合并，建筑区域或其他障碍物。 在一个示例中，规则可能需要自主车辆来警告驾驶员车辆正在接近区域。 因此，车辆可能需要驾驶员来控制转向，加速，减速等。在另一个示例中，区域可以由驾驶员指定，并且可以广播到其他附近的车辆，例如使用无线电链路或其他网络 其他车辆可能能够在相同的位置观察相同的规则，或者至少通知另一车辆的司机，另一司机认为该位置对于自主驾驶是不安全的。