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公开(公告)号：US20250115277A1
公开(公告)日：2025-04-10
申请号：US18983755
申请日：2024-12-17
Applicant: Zoox, Inc.
Inventor： Joseph Funke , Steven Cheng Qian , Kazuhide Okamoto , Jacob Patrick Thalman , Sriram Narayanan , Yunpeng Pan
Abstract: This disclosure describes techniques for autonomous vehicles to determine driving paths and associated trajectories through unstructured or off-route driving environments. When an object is detected within a driving environment, a vehicle may determine a cost-based side association for the object. Various costs may be used in different examples, including costs based on a cost plot and/or motion primitives that may vary for terminal and non-terminal desired destinations (or ending vehicle states). Using tree searches to determine estimated candidate costs, the autonomous vehicle may compare right-side and left-side driving path costs around the object to determine a side association for the object. Based on the side association, the autonomous vehicle may determine an updated planning corridor and/or a trajectory to control the vehicle from a current state to a desired ending vehicle state.
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公开(公告)号：US12252200B2
公开(公告)日：2025-03-18
申请号：US17957756
申请日：2022-09-30
Applicant: Zoox, Inc.
Inventor： Joseph Funke , Liam Gallagher , Marin Kobilarov , Vincent Andreas Laurense , Mark Jonathon McClelland , Sriram Narayanan , Kazuhide Okamoto , Jack Riley , Jeremy Schwartz , Jacob Patrick Thalman , Olivier Amaury Toupet , David Evan Zlotnik
Abstract: Systems and techniques for determining a sideslip vector for a vehicle that may have a direction that is different from that of a heading vector for the vehicle. The sideslip vector in a current vehicle state and sideslip vectors in predicted vehicles states may be used to determine paths for a vehicle through an environment and trajectories for controlling the vehicle through the environment. The sideslip vector may be based on a vehicle position that is the center point of the wheelbase of the vehicle and may include lateral velocity, facilitating the control of four-wheel steered vehicle while maintaining the ability to control two-wheel steered vehicles.
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公开(公告)号：US12208819B1
公开(公告)日：2025-01-28
申请号：US17589528
申请日：2022-01-31
Applicant: Zoox, Inc.
Inventor： Joseph Funke , Steven Cheng Qian , Kazuhide Okamoto , Jacob Patrick Thalman , Sriram Narayanan , Yunpeng Pan
IPC: B60W60/00 , B60W30/09 , B60W30/095
Abstract: This disclosure describes techniques for autonomous vehicles to determine driving paths and associated trajectories through unstructured or off-route driving environments. When an object is detected within a driving environment, a vehicle may determine a cost-based side association for the object. Various costs may be used in different examples, including costs based on a cost plot and/or motion primitives that may vary for terminal and non-terminal desired destinations (or ending vehicle states). Using tree searches to determine estimated candidate costs, the autonomous vehicle may compare right-side and left-side driving path costs around the object to determine a side association for the object. Based on the side association, the autonomous vehicle may determine an updated planning corridor and/or a trajectory to control the vehicle from a current state to a desired ending vehicle state.
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公开(公告)号：US20240174256A1
公开(公告)日：2024-05-30
申请号：US18072015
申请日：2022-11-30
Applicant: Zoox, Inc.
Inventor： Sriram Narayanan , Steven Cheng Qian
IPC: B60W60/00
CPC classification number: B60W60/001 , B60W60/0013 , B60W60/0015 , B60W2520/06
Abstract: Techniques are discussed herein for generating trajectories for controlling motion and/or other behaviors of vehicles in driving environments. In particular, techniques are described herein for using a tree search to determine a trajectory for a vehicle to join a driving route from an initial vehicle state off of the driving route structure. A vehicle computing system may determine various candidate trajectories, including trajectories based on an off-route inertial reference frame, additional trajectories based on the route structure, perturbed trajectories, etc. The set of candidate trajectories may be optimized and/or filtered based on objects in the environment, and the corresponding candidate actions may be used to generate a search tree between the off-route vehicle state and an on-route target state. The costs associated with the candidate actions may be evaluated iteratively to determine a minimum cost traversal of the tree, representing a control trajectory to allow the vehicle to join the driving route structure.
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Patent Agency Ranking
公开(公告)号：US20230192127A1
公开(公告)日：2023-06-22
申请号：US17555004
申请日：2021-12-17
Applicant: Zoox, Inc.
Inventor： Joseph Funke , Steven Cheng Qian , Kazuhide Okamoto , Jacob Patrick Thalman , Sriram Narayanan , Liam Gallagher
CPC classification number: B60W60/0011 , B60W50/00 , B60W2520/10 , B60W2520/12 , B60W2520/06 , B60W2510/20 , B60W2050/0026 , B60W2050/006
Abstract: Techniques are described herein for generating trajectories for autonomous vehicles using velocity-based steering limits. A planning component of an autonomous vehicle can receive steering limits determined based on safety requirements and/or kinematic models of the vehicle. Discontinuous and discrete steering limit values may be converted into a continuous steering limit function for use during on-vehicle trajectory generation and/or optimization operations. When the vehicle is traversing a driving environment, the planning component may use steering limit functions to determine a set of situation-specific steering limits associated with the particular vehicle state and/or driving conditions. The planning component may execute loss functions, including steering angle and/or steering rate costs, to determine a vehicle trajectory based on the steering limits applicable to the current vehicle state.
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公开(公告)号：US20240109585A1
公开(公告)日：2024-04-04
申请号：US17957756
申请日：2022-09-30
Applicant: Zoox, Inc.
Inventor： Joseph Funke , Liam Gallagher , Marin Kobilarov , Vincent Andreas Laurense , Mark Jonathon McClelland , Sriram Narayanan , Kazuhide Okamoto , Jack Riley , Jeremy Schwartz , Jacob Patrick Thalman , Olivier Amaury Toupet , David Evan Zlotnik
IPC: B62D7/15
CPC classification number: B62D7/159
Abstract: Systems and techniques for determining a sideslip vector for a vehicle that may have a direction that is different from that of a heading vector for the vehicle. The sideslip vector in a current vehicle state and sideslip vectors in predicted vehicles states may be used to determine paths for a vehicle through an environment and trajectories for controlling the vehicle through the environment. The sideslip vector may be based on a vehicle position that is the center point of the wheelbase of the vehicle and may include lateral velocity, facilitating the control of four-wheel steered vehicle while maintaining the ability to control two-wheel steered vehicles.
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公开(公告)号：US11780464B2
公开(公告)日：2023-10-10
申请号：US17555004
申请日：2021-12-17
Applicant: Zoox, Inc.
Inventor： Joseph Funke , Steven Cheng Qian , Kazuhide Okamoto , Jacob Patrick Thalman , Sriram Narayanan , Liam Gallagher
CPC classification number: B60W60/0011 , B60W50/00 , B60W2050/006 , B60W2050/0026 , B60W2510/20 , B60W2520/06 , B60W2520/10 , B60W2520/12
Abstract: Techniques are described herein for generating trajectories for autonomous vehicles using velocity-based steering limits. A planning component of an autonomous vehicle can receive steering limits determined based on safety requirements and/or kinematic models of the vehicle. Discontinuous and discrete steering limit values may be converted into a continuous steering limit function for use during on-vehicle trajectory generation and/or optimization operations. When the vehicle is traversing a driving environment, the planning component may use steering limit functions to determine a set of situation-specific steering limits associated with the particular vehicle state and/or driving conditions. The planning component may execute loss functions, including steering angle and/or steering rate costs, to determine a vehicle trajectory based on the steering limits applicable to the current vehicle state.
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公开(公告)号：US11999380B1
公开(公告)日：2024-06-04
申请号：US17554693
申请日：2021-12-17
Applicant: Zoox, Inc.
Inventor： Joseph Funke , Steven Cheng Qian , Kazuhide Okamoto , Jacob Patrick Thalman , Sriram Narayanan
IPC: B60W60/00
CPC classification number: B60W60/0011 , B60W2520/06 , B60W2520/10 , B60W2520/12
Abstract: Techniques are discussed for generating and optimizing trajectories for controlling autonomous vehicles in performing on-route and off-route actions within a driving environment. A planning component of an autonomous vehicle can receive or generate time-discretized (or temporal) trajectories for the autonomous vehicle to traverse an environment. Trajectories can be optimized, for example, based on the lateral and longitudinal dynamics of the vehicle, using loss functions and/or costs. In some examples, the temporal optimization of a trajectory may include resampling a previous trajectory based on the differences in the time sequences of the temporal trajectories, to ensure temporal consistency of trajectories across planning cycles. Constraints also may be applied during temporal optimization in some examples, to control or restrict driving maneuvers that are not supported by the autonomous vehicle.
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9.发明公开公开(公告)号：US20240174239A1
公开(公告)日：2024-05-30
申请号：US18072056
申请日：2022-11-30
Applicant: Zoox, Inc.
Inventor： Sriram Narayanan , Liam Gallagher , Marin Kobilarov
CPC classification number: B60W50/0097 , B60W60/001 , B60W2520/20
Abstract: Techniques are discussed for generating and optimizing trajectories for autonomous vehicles using route-relative numerical integration relative to a reference path. A planner component of an autonomous vehicle, for example, can receive or generate a reference path corresponding to a route through an environment. The current vehicle state, sideslip, and vehicle dynamics can be represented in a system of equations, such that the planner component can substantially simultaneously solve for subsequent trajectory states in a single convergence operation. In various examples, the subsequent trajectory states can be used to evaluate and determine candidate trajectories to control the autonomous vehicle to traverse the environment.
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