利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

12 条记录 (耗时 0.015 秒)

    Anchor lane selection method using navigation input in road change scenarios
    1.
    发明授权
    Anchor lane selection method using navigation input in road change scenarios 有权
    在道路变化情景下使用导航输入的锚车道选择方法

    公开(公告)号：US08706417B2

    公开(公告)日：2014-04-22

    申请号：US13561755

    申请日：2012-07-30

    申请人： Shuqing Zeng ,  Bakhtiar Brian Litkouhi ,  Xingping Chen ,  James N. Nickolaou ,  Daniel Gandhi ,  Joel Pazhayampallil

    发明人： Shuqing Zeng ,  Bakhtiar Brian Litkouhi ,  Xingping Chen ,  James N. Nickolaou ,  Daniel Gandhi ,  Joel Pazhayampallil

    IPC分类号： G05D1/00 ,  G08G1/137

    CPC分类号： B60W30/12 ,  B60W2550/22 ,  B60W2550/306 ,  B60W2550/402 ,  G08G1/167

    摘要： A method for selecting an anchor lane for tracking in a vehicle lane tracking system. Digital map data and leading vehicle trajectory data are used to predict lane information ahead of a vehicle. Left and right lane boundary markers are also detected, where available, using a vision system. The lane marker data from the vision system is combined with the lane information from the digital map data and the leading vehicle trajectory data in a lane curvature fusion calculation. The left and right lane marker data from the vision system are also evaluated for conditions such as parallelism and sudden jumps in offsets, while considering the presence of entrance or exit lanes as indicated by the map data. An anchor lane for tracking is selected based on the evaluation of the vision system data, using either the fused curvature calculation or the digital map and leading vehicle trajectory data.

    摘要翻译： 一种用于在车道跟踪系统中选择用于跟踪的锚车道的方法。 数字地图数据和前导车辆轨迹数据用于预测车辆前方的车道信息。 还可以使用视觉系统检测左右车道边界标记。 来自视觉系统的车道标记数据与车道曲线融合计算中的数字地图数据和前车辆轨迹数据的车道信息相结合。 考虑到地图数据所示的入口或出口通道的存在，还可以评估来自视觉系统的左右车道标记数据，例如平行度和偏移突然跳跃等条件。 基于对视觉系统数据的评估，使用融合曲率计算或数字地图和前导车辆轨迹数据来选择用于跟踪的锚定车道。

    ENHANCED DATA ASSOCIATION OF FUSION USING WEIGHTED BAYESIAN FILTERING
    3.
    发明申请
    ENHANCED DATA ASSOCIATION OF FUSION USING WEIGHTED BAYESIAN FILTERING 有权
    使用加权贝叶斯滤波的增强数据协会

    公开(公告)号：US20130236047A1

    公开(公告)日：2013-09-12

    申请号：US13413861

    申请日：2012-03-07

    申请人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

    发明人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

    IPC分类号： G06K9/00

    CPC分类号： G01S13/726 ,  G01S13/867 ,  G01S13/931 ,  G01S2013/9375 ,  G06K9/00805 ,  G06T1/0007

    摘要： A method of associating targets from at least two object detection systems. An initial prior correspondence matrix is generated based on prior target data from a first object detection system and a second object detection system. Targets are identified in a first field-of-view of the first object detection system based on a current time step. Targets are identified in a second field-of-view of the second object detection system based on the current time step. The prior correspondence matrix is adjusted based on respective targets entering and leaving the respective fields-of-view. A posterior correspondence matrix is generated as a function of the adjusted prior correspondence matrix. A correspondence is identified in the posterior correspondence matrix between a respective target of the first object detection system and a respective target of the second object detection system.

    摘要翻译： 将来自至少两个物体检测系统的目标相关联的方法。 基于来自第一对象检测系统和第二对象检测系统的先前目标数据生成初始先前对应矩阵。 基于当前时间步长，在第一对象检测系统的第一视场中识别目标。 基于当前时间步长，在第二对象检测系统的第二视场中识别目标。 基于进入和离开相应视场的各个目标来调整先前的对应矩阵。 作为调整后的对应矩阵的函数产生后向对应矩阵。 在第一对象检测系统的相应目标和第二对象检测系统的相应目标之间的后向对应矩阵中识别对应关系。

    METHOD AND SYSTEM FOR COLLISION ASSESSMENT FOR VEHICLES
    4.
    发明申请
    METHOD AND SYSTEM FOR COLLISION ASSESSMENT FOR VEHICLES 有权
    车辆碰撞评估方法与系统

    公开(公告)号：US20110307175A1

    公开(公告)日：2011-12-15

    申请号：US12816209

    申请日：2010-06-15

    申请人： DANIEL GANDHI ,  CHAD T. ZAGORSKI

    发明人： DANIEL GANDHI ,  CHAD T. ZAGORSKI

    IPC分类号： G08G1/16

    CPC分类号： G08G1/166 ,  G06F17/10 ,  G06G7/78 ,  G08G9/02

    摘要： Methods and systems are provided for assessing a target proximate a vehicle. A location and a velocity of the target are obtained. The location and the velocity of the target are mapped onto a polar coordinate system via a processor. A likelihood that the vehicle and the target will collide is determined using the mapping.

    摘要翻译： 提供了用于评估车辆附近的目标的方法和系统。 获得目标的位置和速度。 目标的位置和速度经由处理器映射到极坐标系上。 使用映射确定车辆和目标将发生碰撞的可能性。

    Vehicle localization
    5.
    发明授权
    Vehicle localization 有权
    车辆定位

    公开(公告)号：US09453737B2

    公开(公告)日：2016-09-27

    申请号：US13284500

    申请日：2011-10-28

    申请人： James N. Nickolaou ,  Daniel Gandhi ,  Dmitriy Feldman

    发明人： James N. Nickolaou ,  Daniel Gandhi ,  Dmitriy Feldman

    IPC分类号： G01S3/80 ,  G01C21/30 ,  G01S19/48 ,  G01S5/02

    CPC分类号： G01C21/30 ,  G01S5/0252 ,  G01S19/48

    摘要： Methods, systems, and vehicles are provided for localizing a vehicle. A sensor is configured to detect an object disposed in a generally upward direction from the vehicle while the vehicle is travelling. A processor is coupled to the sensor. The processor is configured to correlate the object with information from a map database, thereby generating a correlation, and determine a geographic location of the vehicle based on the correlation.

    摘要翻译： 提供了用于本地化车辆的方法，系统和车辆。 传感器被配置为在车辆行驶时检测从车辆大致向上的方向设置的物体。 处理器耦合到传感器。 处理器被配置为将对象与来自地图数据库的信息相关联，从而生成相关性，并且基于相关性来确定车辆的地理位置。

    Enhanced data association of fusion using weighted Bayesian filtering
    10.
    发明授权
    Enhanced data association of fusion using weighted Bayesian filtering 有权
    使用加权贝叶斯滤波增强融合数据关联

    公开(公告)号：US08705797B2

    公开(公告)日：2014-04-22

    申请号：US13413861

    申请日：2012-03-07

    申请人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

    发明人： Shuqing Zeng ,  Lufeng Shi ,  Daniel Gandhi ,  James N. Nickolaou

    IPC分类号： G06K9/00 ,  H04N5/225

    CPC分类号： G01S13/726 ,  G01S13/867 ,  G01S13/931 ,  G01S2013/9375 ,  G06K9/00805 ,  G06T1/0007

    摘要： A method of associating targets from at least two object detection systems. An initial prior correspondence matrix is generated based on prior target data from a first object detection system and a second object detection system. Targets are identified in a first field-of-view of the first object detection system based on a current time step. Targets are identified in a second field-of-view of the second object detection system based on the current time step. The prior correspondence matrix is adjusted based on respective targets entering and leaving the respective fields-of-view. A posterior correspondence matrix is generated as a function of the adjusted prior correspondence matrix. A correspondence is identified in the posterior correspondence matrix between a respective target of the first object detection system and a respective target of the second object detection system.

    摘要翻译： 将来自至少两个物体检测系统的目标相关联的方法。 基于来自第一对象检测系统和第二对象检测系统的先前目标数据生成初始先前对应矩阵。 基于当前时间步长，在第一对象检测系统的第一视场中识别目标。 基于当前时间步长，在第二对象检测系统的第二视场中识别目标。 基于进入和离开相应视场的各个目标来调整先前的对应矩阵。 作为调整后的对应矩阵的函数产生后向对应矩阵。 在第一对象检测系统的相应目标和第二对象检测系统的相应目标之间的后向对应矩阵中识别对应关系。