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1. 发明授权

US08825391B1 Building elevation maps from laser data 有权
标题翻译：从激光数据建立高程图
公开(公告)号：US08825391B1
公开(公告)日：2014-09-02
申请号：US13198199
申请日：2011-08-04
申请人： Christopher Paul Urmson , Andrew Chatham , Hendrik Dahlkamp , Michael Steven Montemerlo , Jiajun Zhu
发明人： Christopher Paul Urmson , Andrew Chatham , Hendrik Dahlkamp , Michael Steven Montemerlo , Jiajun Zhu
IPC分类号： G01C21/00
CPC分类号： G01S17/89 , G01C21/32 , G05D1/024 , G05D1/0274 , G05D2201/0213 , G09B29/12
摘要： Aspects of the present disclosure relate generally to generating elevation maps. More specifically, data points may be collected by a laser moving along a roadway and used to generate an elevation map of the roadway. The collected data points may be projected onto a two dimensional or “2D” grid. The grid may include a plurality of cells, each cell of the grid representing a geolocated second of the roadway. The data points of each cell may be evaluated to identify an elevation for the particular cell. For example, the data points in a particular cell may be filtered in various ways including occlusion, interpolation from neighboring cells, etc. The minimum value of the remaining data points within each cell may then be used as the elevation for the particular cell, and the elevation of a plurality of cells may be used to generate an elevation map of the roadway.
摘要翻译：本公开的方面通常涉及产生高程图。更具体地，可以通过沿着道路移动的激光来收集数据点，并且用于产生道路的高程图。所收集的数据点可以投影到二维或“2D”网格上。网格可以包括多个单元，网格的每个单元表示道路的地理位置的第二。可以评估每个单元的数据点以识别特定单元的高程。例如，特定小区中的数据点可以以各种方式被过滤，包括闭塞，来自相邻小区的内插等。然后可以将每个小区内剩余数据点的最小值用作特定小区的高程，以及可以使用多个单元的高程来产生道路的高程图。

2. 发明授权

US08565958B1 Removing extraneous objects from maps 有权
标题翻译：从地图中移除无关物品
公开(公告)号：US08565958B1
公开(公告)日：2013-10-22
申请号：US13151461
申请日：2011-06-02
申请人： Michael Steven Montemerlo , Donald Jason Burnette , Andrew Chatham , Daniel Trawick Egnor
发明人： Michael Steven Montemerlo , Donald Jason Burnette , Andrew Chatham , Daniel Trawick Egnor
IPC分类号： G01C21/32 , G09B29/00 , G05D1/02
CPC分类号： G05D1/024 , G05D1/0274 , G05D2201/0213 , G09B29/106
摘要： Aspects of the present disclosure relate generally to safe and effective use of autonomous vehicles. More specifically, laser data including locations, intensities, and elevation data may be collected along a roadway in order to generate a 3D map of the roadway. In order to remove extraneous objects such as moving vehicles from the 3D map, a 2D grid of the roadway may be generated. The grid may include a plurality of cells, each representing an area of the roadway. The collected data may be sorted into the grid based on location and then evaluated to identify the lowest elevation of the cell. All data points above some threshold distance above this lowest elevation may be removed. The resulting data points may be used to generate a 3D map of the roadway which excludes the extraneous objects.
摘要翻译：本公开的方面通常涉及安全和有效地使用自主车辆。更具体地，可以沿着道路收集包括位置，强度和高程数据的激光数据，以便生成道路的3D地图。为了从3D地图移除车辆等外来物体，可能会产生道路的二维网格。网格可以包括多个单元，每个单元表示道路的区域。收集的数据可以基于位置被分类到网格中，然后被评估以识别小区的最低海拔。超过这个最低高度的某个阈值距离以上的所有数据点都可以被去除。所得到的数据点可用于生成排除外来物体的道路的3D地图。

3. 发明授权

US08996226B1 Intersection completer 有权
标题翻译：交点完整
公开(公告)号：US08996226B1
公开(公告)日：2015-03-31
申请号：US13181068
申请日：2011-07-12
申请人： Andrew Chatham , Christopher Paul Urmson
发明人： Andrew Chatham , Christopher Paul Urmson
IPC分类号： G08G1/0962 , G01C21/36
CPC分类号： G01C21/3658 , G01C21/32 , G01C21/3602 , G08G1/09626 , G09B29/007
摘要： Aspects of the disclosure relate generally to generating roadgraphs for use by autonomous vehicles. A computer may receive input defining aspects of a roadway including an intersection with another roadway, one or more traffic control features, and one or more locations at which a vehicle is required to observe at least one traffic signal before entering the intersection. A user may identify the intersection, for example, by tracing a perimeter around the intersection. In response, for each particular location of the one or more locations, the computer may identifying a route through the intersection from the particular location and determine, based on the boundary of the intersection and the particular location, a set of the one or more traffic control features must be observed by the vehicle before entering the intersection. This information may then be used to generate a roadgraph.
摘要翻译：本公开的方面通常涉及生成由自主车辆使用的路标。计算机可以接收定义道路的方面的输入，其包括与另一道路，一个或多个交通控制特征以及车辆在进入交叉点之前需要观察至少一个交通信号的一个或多个位置的交叉路口。用户可以标识交叉点，例如通过跟踪交叉路口周围的周边。作为响应，对于一个或多个位置的每个特定位置，计算机可以从特定位置识别通过交叉路口的路线，并且基于交叉点和特定位置的边界来确定一个或多个业务的集合控制功能必须在车辆进入交叉路口前观察。然后可以使用该信息来生成路灯。

4. 发明授权

US08195394B1 Object detection and classification for autonomous vehicles 有权
标题翻译：自主车辆的物体检测和分类
公开(公告)号：US08195394B1
公开(公告)日：2012-06-05
申请号：US13181999
申请日：2011-07-13
申请人： Jiajun Zhu , Michael Steven Montemerlo , Christopher Paul Urmson , Andrew Chatham
发明人： Jiajun Zhu , Michael Steven Montemerlo , Christopher Paul Urmson , Andrew Chatham
IPC分类号： G06K9/00
CPC分类号： G06K9/00805 , G01C21/26 , G08G1/09626 , G08G1/096725 , G08G1/096741 , G08G1/096775
摘要： Aspects of the disclosure relate generally to safe and effective use of autonomous vehicles. More specifically, objects detected in a vehicle's surroundings may be detected by the vehicle's various sensors and identified based on their relative location in a roadgraph. The roadgraph may include a graph network of information such as roads, lanes, intersections, and the connections between these features. The roadgraph may also include the boundaries of areas, including for example, crosswalks or bicycle lanes. In one example, an object detected in a location corresponding to a crosswalk area of the roadgraph may be identified as a person. In another example, an object detected in a location corresponding to a bicycle area of the roadgraph and identified as a bicycle. By identifying the type of object in this way, an autonomous vehicle may be better prepared to react to or simply avoid the object.
摘要翻译：本公开的方面一般涉及安全和有效地使用自主车辆。更具体地，可以由车辆的各种传感器检测在车辆周围检测到的物体，并且基于它们在路标图中的相对位置来识别。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。道路图也可以包括区域的边界，包括例如人行横道或自行车道。在一个示例中，在与路灯图的人行横道区域相对应的位置中检测到的对象可以被识别为人。在另一示例中，在与路灯图的自行车区域相对应的位置中检测到的物体，并被识别为自行车。通过以这种方式识别对象的类型，自主车辆可以更好地准备反应或者简单地避开物体。

5. 发明授权

US08874372B1 Object detection and classification for autonomous vehicles 有权
标题翻译：自主车辆的物体检测和分类
公开(公告)号：US08874372B1
公开(公告)日：2014-10-28
申请号：US13440555
申请日：2012-04-05
申请人： Jiajun Zhu , Michael Steven Montemerlo , Christopher Paul Urmson , Andrew Chatham
发明人： Jiajun Zhu , Michael Steven Montemerlo , Christopher Paul Urmson , Andrew Chatham
IPC分类号： G06K9/00
CPC分类号： G06K9/00805 , G01C21/26 , G08G1/09626 , G08G1/096725 , G08G1/096741 , G08G1/096775
摘要： Aspects of the disclosure relate generally to safe and effective use of autonomous vehicles. More specifically, objects detected in a vehicle's surroundings may be detected by the vehicle's various sensors and identified based on their relative location in a roadgraph. The roadgraph may include a graph network of information such as roads, lanes, intersections, and the connections between these features. The roadgraph may also include the boundaries of areas, including for example, crosswalks or bicycle lanes. In one example, an object detected in a location corresponding to a crosswalk area of the roadgraph may be identified as a person. In another example, an object detected in a location corresponding to a bicycle area of the roadgraph and identified as a bicycle. By identifying the type of object in this way, an autonomous vehicle may be better prepared to react to or simply avoid the object.
摘要翻译：本公开的方面一般涉及安全和有效地使用自主车辆。更具体地，可以由车辆的各种传感器检测在车辆周围检测到的物体，并且基于它们在路标图中的相对位置来识别。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。道路图也可以包括区域的边界，包括例如人行横道或自行车道。在一个示例中，在与路灯图的人行横道区域相对应的位置中检测到的对象可以被识别为人。在另一示例中，在与路灯图的自行车区域相对应的位置中检测到的物体，并被识别为自行车。通过以这种方式识别对象的类型，自主车辆可以更好地准备反应或者简单地避开物体。

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