知搜-全球专利检索

  1. 登录
  2. 注册

搜索结果

8 条记录 (耗时 0.018 秒)

    CORRIDOR/HOMOTOPY SCORING AND VALIDATION
    2.
    发明公开
    CORRIDOR/HOMOTOPY SCORING AND VALIDATION 审中-公开

    公开(公告)号：US20240025452A1

    公开(公告)日：2024-01-25

    申请号：US17814503

    申请日：2022-07-22

    申请人： Motional AD LLC

    发明人： Scott Drew Pendleton ,  Hans Andersen ,  Juraj Kabzan ,  Titus Chua

    IPC分类号： B60W60/00 ,  B60W40/04

    CPC分类号： B60W60/0027 ,  B60W60/0013 ,  B60W40/04 ,  B60W60/0015 ,  B60W60/0011

    摘要： Provided are methods and systems for corridor/homotopy scoring and validation. A method for operating an autonomous vehicle, is provided. The method includes obtaining sensor data associated with an environment in which an autonomous vehicle is operating and determining, by the at least one processor, a set of agents in the environment based on the sensor data. The method includes determining, by the at least one processor, a plurality of sets of navigation options for the autonomous vehicle, wherein each set of navigation options includes a first navigation option and a second navigation option, and wherein at least one set of navigation options is associated with at least one agent of the set of agents. The method includes selecting a plurality of navigation options from the plurality of sets of navigation options and generating a corridor for the autonomous vehicle based on the plurality of selected navigation options.

    Planning with dynamic state a trajectory of an autonomous vehicle
    3.
    发明授权
    Planning with dynamic state a trajectory of an autonomous vehicle 有权

    公开(公告)号：US12060083B2

    公开(公告)日：2024-08-13

    申请号：US17239155

    申请日：2021-04-23

    申请人： MOTIONAL AD LLC

    发明人： Scott Drew Pendleton ,  Hans Andersen

    IPC分类号： B60W60/00 ,  B60W30/09

    CPC分类号： B60W60/0027 ,  B60W30/09 ,  B60W60/0016 ,  B60W2554/4029 ,  B60W2554/408 ,  B60W2554/80

    摘要： This disclosure describes an autonomous vehicle configured to obtain sensor data associated with objects proximate a projected route of the autonomous vehicle, determine static constraints that limit a trajectory of the autonomous vehicle along the projected route based on non-temporal risks associated with a first subset of the f objects, predict a position and speed of the autonomous vehicle as a function of time along the projected route based on the static constraints, identify temporal risks associated with a second subset of the objects based on the predicted position and speed of the autonomous vehicle, determine dynamic constraints that further limit the trajectory of the autonomous vehicle along the projected route to help the autonomous vehicle avoid the temporal risks associated with the second subset of the objects, and adjust the trajectory of the autonomous vehicle in accordance with the static constraints and the dynamic constraints.

    TURN SIGNAL ASSIGNMENT FOR COMPLEX MANEUVERS
    5.
    发明公开
    TURN SIGNAL ASSIGNMENT FOR COMPLEX MANEUVERS 审中-公开

    公开(公告)号：US20240131984A1

    公开(公告)日：2024-04-25

    申请号：US17990551

    申请日：2022-11-18

    申请人： Motional AD LLC

    发明人： Scott Drew Pendleton ,  Titus Chua

    IPC分类号： B60Q1/50 ,  B60Q1/34

    CPC分类号： B60Q1/507 ,  B60Q1/346 ,  B60Q2800/10

    摘要： Provided are methods for turn signal assignment in complex maneuvers, which can include receiving position information associated with a position of a vehicle. Some methods described also include determining, hierarchically and based at least on the position information, whether to activate a turn signal of a vehicle prior to activation of the turn signal based on a turn of the vehicle at a roadway intersection. Some methods described also include determining a time to activate the turn signal prior to the turn of the vehicle at the roadway intersection. Some methods described also include transmitting a control signal to activate the turn signal at the determined time. Systems and computer program products are also provided.

    PATH GENERATION BASED ON PREDICTED ACTIONS
    6.
    发明公开
    PATH GENERATION BASED ON PREDICTED ACTIONS 审中-公开

    公开(公告)号：US20240025444A1

    公开(公告)日：2024-01-25

    申请号：US17814509

    申请日：2022-07-22

    申请人： Motional AD LLC

    发明人： Sammy Omari ,  Kevin C. Gall ,  Juraj Kabzan ,  Hans Andersen ,  Bence Cserna ,  Scott Drew Pendleton

    IPC分类号： B60W60/00 ,  G06V20/58 ,  G06V20/70

    CPC分类号： B60W60/0015 ,  G06V20/58 ,  G06V20/70 ,  G06V2201/08 ,  G06V10/82

    摘要： Provided are methods and systems for semantic behavior filtering for prediction improvement. A method for operating an autonomous vehicle is provided. The method includes obtaining, by at least one processor, semantic image data associated with an environment in which an autonomous vehicle is operating. The method includes determining, by the at least one processor a set of agents in the environment based on the semantic image data. The method includes determining, by the at least one processor, a set of secondary agents from the set of agents based on a relative location of a respective secondary agent to a respective object and a set of object semantic behavior data associated with the respective object. The method includes determining, from the set of agents, a set of primary agents other than secondary agents. The method includes generating a path for the autonomous vehicle based on the set of primary agents.

    PATH GENERATION BASED ON PREDICTED ACTIONS
    7.
    发明公开
    PATH GENERATION BASED ON PREDICTED ACTIONS 审中-公开

    公开(公告)号：US20240025395A1

    公开(公告)日：2024-01-25

    申请号：US17814505

    申请日：2022-07-22

    申请人： Motional AD LLC

    发明人： Sammy Omari ,  Kevin C. Gall ,  Juraj Kabzan ,  Hans Andersen ,  Bence Cserna ,  Scott Drew Pendleton

    IPC分类号： B60W30/09 ,  G06V20/58 ,  B60W60/00 ,  B60W30/095

    CPC分类号： B60W30/09 ,  G06V20/58 ,  B60W60/0015 ,  B60W30/0956 ,  B60W30/0953 ,  B60W60/0027 ,  B60W10/20

    摘要： Provided are methods and systems for semantic behavior filtering for prediction improvement. A method for operating an autonomous vehicle is provided. The method includes obtaining, by at least one processor, semantic image data associated with an environment in which an autonomous vehicle is operating. The method includes determining, by the at least one processor, at least one agent in the environment. The method includes determining a predicted action for the at least one agent. The method includes determining an agent predicted path for the at least one agent. The method includes determining a vehicle path of the autonomous vehicle. The method includes determining a predicted collision of the at least one agent and the autonomous vehicle. The method includes simulating actions to avoid the predicted collision. The method includes categorizing the predicted collision as a primary predicted collision based on the simulating actions.