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    • 2. 发明授权
    • Sensor field selection
    • 传感器场选择
    • US08589014B2
    • 2013-11-19
    • US13150385
    • 2011-06-01
    • Nathaniel FairfieldJiajun ZhuDmitri A. Dolgov
    • Nathaniel FairfieldJiajun ZhuDmitri A. Dolgov
    • G05D1/02G01S7/40
    • G05D1/024G05D1/0246G05D1/0255G05D2201/0213
    • Aspects of the present disclosure relate generally to safe and effective use of autonomous vehicles. More specifically, an autonomous vehicle is able to detect objects in its surroundings which are within the sensor fields. In response to detecting objects, the computer may adjust the autonomous vehicle's speed or change direction. In some examples, however, the sensor fields may be changed or become less reliable based on objects or other features in the vehicle's surroundings. As a result, the vehicle's computer may calculate the size and shape of the area of sensor diminution and a new sensor field based on this area of diminution. In response to identifying the area of sensor diminution or the new sensor field, the vehicle's computer may change the control strategies of the vehicle.
    • 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,自主车辆能够检测其周围的传感器场内的物体。 响应于检测对象,计算机可以调节自主车辆的速度或改变方向。 然而,在一些示例中,传感器场可以基于车辆周围的物体或其它特征而改变或变得不可靠。 因此,车辆的计算机可以计算出传感器减小面积的大小和形状,以及基于该减小区域的新的传感器场。 响应于识别传感器减少的区域或新的传感器场,车辆的计算机可以改变车辆的控制策略。
    • 3. 发明申请
    • SENSOR FIELD SELECTION
    • 传感器场选择
    • US20120310466A1
    • 2012-12-06
    • US13150385
    • 2011-06-01
    • Nathaniel FairfieldJiajun ZhuDmitri A. Dolgov
    • Nathaniel FairfieldJiajun ZhuDmitri A. Dolgov
    • G05D1/02
    • G05D1/024G05D1/0246G05D1/0255G05D2201/0213
    • Aspects of the present disclosure relate generally to safe and effective use of autonomous vehicles. More specifically, an autonomous vehicle 301, 501 is able to detect objects in its surroundings which are within the sensor fields 410, 411, 430, 431, 420A-423A, 420B-423B, 570-75, 580. In response to detecting objects, the computer 110 may adjust the autonomous vehicle's speed or change direction. In some examples, however, the sensor fields may be changed or become less reliable based on objects or other features in the vehicle's surroundings. As a result, the vehicle's computer 110 may calculate the size and shape of the area of sensor diminution 620, 720 and a new sensor field based on this area of diminution. In response to identifying the area of sensor diminution or the new sensor field, the vehicle's computer may change the control strategies of the vehicle.
    • 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,自主车辆301,501能够检测其周围的传感器场410,411,430,431,420A-423A,420B-423B,570-75,580内的物体。响应于检测物体 计算机110可以调节自主车辆的速度或改变方向。 然而,在一些示例中,传感器场可以基于车辆周围的物体或其它特征而改变或变得不可靠。 因此,车辆计算机110可以基于该减小区域来计算传感器减小区域620,720的面积和形状以及新的传感器场。 响应于识别传感器减少的区域或新的传感器场,车辆的计算机可以改变车辆的控制策略。
    • 4. 发明申请
    • VEHICLE CONTROL BASED ON PERCEPTION UNCERTAINTY
    • 基于情感不确定性的车辆控制
    • US20130197736A1
    • 2013-08-01
    • US13361083
    • 2012-01-30
    • Jiajun ZhuDmitri A. DolgovDavid I. Ferguson
    • Jiajun ZhuDmitri A. DolgovDavid I. Ferguson
    • G05D1/00
    • G05D1/0088G05D2201/0213
    • Aspects of the disclosure relate generally to maneuvering autonomous vehicles. Specifically, the vehicle may determine the uncertainty in its perception system and use this uncertainty value to make decisions about how to maneuver the vehicle. For example, the perception system may include sensors, object type models, and object motion models, each associated with uncertainties. The sensors may be associated with uncertainties based on the sensor's range, speed, and /or shape of the sensor field. The object type models may be associated with uncertainties, for example, in whether a perceived object is of one type (such as a small car) or another type (such as a bicycle). The object motion models may also be associated with uncertainties, for example, not all objects will move exactly as they are predicted to move. These uncertainties may be used to maneuver the vehicle.
    • 本公开的方面通常涉及操纵自主车辆。 具体来说,车辆可以确定其感知系统的不确定性,并使用该不确定性值来决定如何操纵车辆。 例如,感知系统可以包括传感器,对象类型模型和对象运动模型,每个与不确定性相关联。 传感器可能会根据传感器范围,速度和/或传感器场的形状与不确定性相关联。 对象类型模型可能与不确定性相关联,例如,感知对象是否是一种类型(例如小型轿厢)或另一类型(例如自行车)。 对象运动模型也可能与不确定性相关联,例如,并不是所有的对象将按照预测的移动精确地移动。 这些不确定性可用于操纵车辆。