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    Trajectory prediction based on a decision tree
    1.
    发明授权
    Trajectory prediction based on a decision tree 有权

    公开(公告)号：US12187324B2

    公开(公告)日：2025-01-07

    申请号：US17900658

    申请日：2022-08-31

    Applicant: Zoox, Inc.

    Inventor： Timothy Caldwell ,  Xianan Huang ,  Joseph Lorenzetti ,  Yunpeng Pan ,  Ke Sun ,  Linjun Zhang

    IPC: B60W60/00 ,  B60W10/04 ,  B60W10/18 ,  B60W10/20 ,  B60W30/18

    Abstract: Techniques for determining a vehicle trajectory that causes a vehicle to navigate in an environment relative to one or more objects are described herein. For example, the techniques may include a computing device determining a decision tree having nodes to represent different object intents and/or nodes to represent vehicle actions at a future time. A tree search algorithm can search the decision tree to evaluate potential interactions between the vehicle and the one or more objects over a time period, and output a vehicle trajectory for the vehicle. The vehicle trajectory can be sent to a vehicle computing device for consideration during vehicle planning, which may include simulation.

    Vehicle representation determination
    2.
    发明授权
    Vehicle representation determination 有权

    公开(公告)号：US12162500B1

    公开(公告)日：2024-12-10

    申请号：US17829114

    申请日：2022-05-31

    Applicant: Zoox, Inc.

    Inventor： Joshua Dean Egbert ,  Joseph Funke ,  Xianan Huang ,  Dhanushka Nirmevan Kularatne ,  David Evan Zlotnik

    IPC: B60W50/00 ,  B60W50/02 ,  B60W60/00

    Abstract: Techniques for accurately predicting vehicle state errors for avoiding collisions with objects detected in an environment of a vehicle are discussed herein. A vehicle safety system can implement a model determine a representation of the vehicle usable in a scenario. The model may dynamically determine a size and/or a heading of the vehicle representation based on differences between a candidate trajectory and a current trajectory of the vehicle. The safety system can identify a potential collision between the vehicle and the object based at least in part on an overlap of the vehicle representation and an object representation.

    HIERARCHICAL MULTI-OBJECTIVE OPTIMIZATION IN VEHICLE PATH PLANNING TREE SEARCH
    3.
    发明申请
    HIERARCHICAL MULTI-OBJECTIVE OPTIMIZATION IN VEHICLE PATH PLANNING TREE SEARCH 有权

    公开(公告)号：US20250002041A1

    公开(公告)日：2025-01-02

    申请号：US18217187

    申请日：2023-06-30

    Applicant: Zoox, Inc.

    Inventor： Joseph Lorenzetti ,  Timothy Caldwell ,  Ke Sun ,  Xianan Huang

    IPC: B60W60/00

    Abstract: A hierarchical tree search may determine different costs associated with a same candidate action for different levels of the hierarchy, each of which may be associated with different cost function(s) and respective objective(s), such as safety, progress, comfort, and the like. At each level, the hierarchical tree search may determine an upper and lower bound cost for the candidate action that may be based on the cost function(s) for that level. The hierarchical tree search may mask out for subsequent level(s) any candidate actions at a level of the tree that exceed the lowest upper or lower bound cost of any candidate action at that level by more than a slack amount.

    TRAJECTORY PLANNING BASED ON TREE SEARCH EXPANSION
    5.
    发明申请
    TRAJECTORY PLANNING BASED ON TREE SEARCH EXPANSION 有权

    公开(公告)号：US20250108839A1

    公开(公告)日：2025-04-03

    申请号：US18478813

    申请日：2023-09-29

    Applicant: Zoox, Inc.

    Inventor： Timothy Caldwell ,  Xianan Huang ,  Syed Bilal Mehdi ,  Jeremy Schwartz

    IPC: B60W60/00 ,  G06N5/022

    Abstract: Techniques for determining a vehicle trajectory that causes a vehicle to navigate in an environment relative to one or more objects are described herein. In some cases, the techniques described herein relate to selectively expanding a tree structure (e.g., a decision tree structure) to efficiently search for simulation data that can be used to evaluate vehicle control trajectories. The tree structure may include state nodes representing observed and/or predicted environment states, and action nodes representing candidate actions the vehicle may take. By selectively and incrementally expanding the tree using estimated state transition probabilities to focus on higher likelihood scenarios, more optimal trajectories can be determined without exhaustively evaluating every possible outcome.

    VEHICLE TRAJECTORY CONTROL USING A TREE SEARCH
    8.
    发明申请
    VEHICLE TRAJECTORY CONTROL USING A TREE SEARCH 有权

    公开(公告)号：US20230041975A1

    公开(公告)日：2023-02-09

    申请号：US17394334

    申请日：2021-08-04

    Applicant: Zoox, Inc.

    Inventor： Timothy Caldwell ,  Rasmus Fonseca ,  Arian Houshmand ,  Xianan Huang ,  Marin Kobilarov ,  Lichao Ma ,  Chonhyon Park ,  Cheng Peng ,  Matthew Van Heukelom

    IPC: B60W60/00 ,  G05B13/02

    Abstract: Trajectory generation for controlling motion or other behavior of an autonomous vehicle may include alternately determining a candidate action and predicting a future state based on that candidate action. The technique may include determining a cost associated with the candidate action that may include an estimation of a transition cost from a current or former state to a next state of the vehicle. This cost estimate may be a lower bound cost or an upper bound cost and the tree search may alternately apply the lower bound cost or upper bound cost exclusively or according to a ratio or changing ratio. The prediction of the future state may be based at least in part on a machine-learned model's classification of a dynamic object as being a reactive object or a passive object, which may change how the dynamic object is modeled for the prediction.

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