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公开(公告)号：US20240241257A1
公开(公告)日：2024-07-18
申请号：US18417356
申请日：2024-01-19
Applicant: Zoox, Inc.
Inventor： Subhasis Das , Chuang Wang , Sabeek Mani Pradhan
CPC classification number: G01S17/89 , G01C21/3492 , G01S19/393 , G06N20/00
Abstract: Techniques for updating data operations in a perception system are discussed herein. A vehicle may use a perception system to capture data about an environment proximate to the vehicle. The perception system may receive image data, lidar data, and/or radar data to determine information about an object in the environment. As different sensors may be associated with different time periods for capturing and/or processing operations, the techniques include updating object data with data from sensors associated with a shorter time period to generate intermediate object data. Such intermediate object data may reduce a delay in updating a position of an object in an environment, which may improve reaction time(s) and/or safety outcomes in systems implementing such perception systems, such as an autonomous vehicle.
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公开(公告)号：US11952001B1
公开(公告)日：2024-04-09
申请号：US17522703
申请日：2021-11-09
Applicant: Zoox, Inc.
Inventor： Chuang Wang , Leonardo Poubel Orenstein , Tod Cameron Semple , James Graham Dolan , Takahiro Baba , Matthew Lotocki
CPC classification number: B60W50/035 , B60W60/0015 , G05B17/02 , G07C5/008 , G07C5/085 , B60W2050/0088
Abstract: Driving simulations may be generated based on driving log data and used to validate autonomous vehicle safety systems. A driving simulation system may receive driving log data from autonomous vehicles and determine events which caused a vehicle to diverge from a planned trajectory. Driving simulations may be generated based on the driving log data, and executed using a simulated vehicle that follows the initial planned trajectory of the autonomous vehicle. The driving simulations may be analyzed to detect potential collisions and near misses, and to determine success conditions for the behaviors of vehicle safety systems. Driving simulations and associated success conditions may be aggregated and used in validation suites for vehicle controllers and/or vehicle safety systems, thereby providing more comprehensive and robust autonomous vehicle validation based on real-world driving scenarios.
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公开(公告)号：US11912301B1
公开(公告)日：2024-02-27
申请号：US17117626
申请日：2020-12-10
Applicant: Zoox, Inc.
Inventor： Noureldin Ehab Hendy , Chuang Wang
CPC classification number: B60W60/0011 , B60W60/00276 , G06N3/08 , B60W2400/00
Abstract: Techniques for analyzing driving scenarios are discussed herein. For example, techniques may include determining a level of exposure associated with scenarios, searching for similar scenarios, and generating new additional scenarios. A driving scenario may be represented as top-down multi-channel data. The top-down multi-channel data may be provided as input to a neural network trained to output a prediction of future events. A multi-dimensional vector representing the scenario can be received as an intermediate output from the neural network and may be stored to represent the scenario. Multi-dimensional vectors representing different scenarios may be stored in a multi-dimensional space, and similar scenarios may be identified by proximity searching of the multi-dimensional space.
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公开(公告)号：US20230242149A1
公开(公告)日：2023-08-03
申请号：US17589504
申请日：2022-01-31
Applicant: Zoox, Inc.
Inventor： Badeea Ferdaous Alferdaous Alazem , Chuang Wang
IPC: B60W60/00 , B60W40/06 , G06V10/764 , G06V20/56 , G01S13/89
CPC classification number: B60W60/0011 , B60W40/06 , G06V10/764 , G06V20/56 , G01S13/89 , B60W2420/52 , B60W2554/20 , B60W2552/00
Abstract: This disclosure describes techniques for using radar cross-section (RCS) data to classify objects detected by autonomous vehicles within driving environments. In some examples, the variance of the RCS data associated with an object may be evaluated to determine signal interference caused by multipath fading. The variance of the RCS data may be used to classify the object and to determine whether the autonomous vehicle can safely drive over the object. For instance, objects such as manhole covers, storm drains, and expansion joints may provide a significant radar signal, but low RCS variance indicating that they can be driven over by the vehicle. Based on the classification of the object, the autonomous vehicle may determine a trajectory around the object or directly over the object.
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公开(公告)号：US11709260B2
公开(公告)日：2023-07-25
申请号：US17245929
申请日：2021-04-30
Applicant: Zoox, Inc.
Inventor： Badeea Ferdaous Alferdaous Alazem , Venkata Subrahmanyam Chandra Sekhar Chebiyyam , Joshua Kriser Cohen , Subasingha Shaminda Subasingha , Samantha Marie Ting , Chuang Wang
IPC: G01S13/931 , G01S13/89 , G01S17/95 , G01S13/86
CPC classification number: G01S13/931 , G01S13/865 , G01S13/89 , G01S17/95
Abstract: Techniques for determining a probability of a false negative associated with a location of an environment are discussed herein. Data from a sensor, such as a radar sensor, can be received that includes point cloud data, which includes first and second data points. The first data point has a first attribute and the second data point has a second attribute. A difference between the first and second attributes is determined such that a frequency distribution may be determined. The frequency distribution may then be used to determine a distribution function, which allows for the determination of a resolution function that is associated with the sensor. The resolution function may then be used to determine a probability of a false negative at a location in an environment. The probability can be used to control a vehicle in a safe and reliable manner.
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Patent Agency Ranking
公开(公告)号：US20230142674A1
公开(公告)日：2023-05-11
申请号：US17384430
申请日：2021-07-23
Applicant: Zoox, Inc.
Inventor： Venkata Subrahmanyam Chandra Sekhar Chebiyyam , Subasingha Shaminda Subasingha , Joshua Kriser Cohen , Chuang Wang , Samantha Marie Ting , Badeea Ferdaous Alferdaous Alazem
IPC: G01S7/41 , G01S13/931
CPC classification number: G01S7/41 , G01S13/931
Abstract: Techniques are discussed herein for analyzing radar data to determine that radar noise from one or more target detections potentially conceals additional objects near the target detection. Determining whether an object may be concealed can be based at least in part on a radar noise level based on a target detection, as well as distributions of radar cross sections and/or doppler data associated with particular object types. For a location near a target detection, a radar system may determine estimated noise levels, and compare the estimated noise levels to radar cross section probabilities associated with object types to determine the likelihood that an object of the object type could be concealed at the location. Based on the analysis, the system may determine a vehicle trajectory or otherwise may control a vehicle based on the likelihood that an object may be concealed at the location.
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公开(公告)号：US20230100014A1
公开(公告)日：2023-03-30
申请号：US17966037
申请日：2022-10-14
Applicant: Zoox, Inc.
Inventor： Pengfei Duan , James William Vaisey Philbin , Cooper Stokes Sloan , Sarah Tariq , Feng Tian , Chuang Wang , Kai Zhenyu Wang , Yi Xu
Abstract: Techniques relating to monitoring map consistency are described. In an example, a monitoring component associated with a vehicle can receive sensor data associated with an environment in which the vehicle is positioned. The monitoring component can generate, based at least in part on the sensor data, an estimated map of the environment, wherein the estimated map is encoded with policy information for driving within the environment. The monitoring component can then compare first information associated with a stored map of the environment with second information associated with the estimated map to determine whether the estimated map and the stored map are consistent. Component(s) associated with the vehicle can then control the object based at least in part on results of the comparing.
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公开(公告)号：US11255958B2
公开(公告)日：2022-02-22
申请号：US16288990
申请日：2019-02-28
Applicant: Zoox, Inc.
Inventor： Chuang Wang , Joshua Kriser Cohen
IPC: G01S13/58 , G01S7/02 , G01S13/931
Abstract: Techniques are discussed for determining reflected returns in radar sensor data. In some instances, pairs of radar returns may be compared to one another. For example, a velocity associated with a first radar return may be projected onto a radial direction associated with a second radar return to determine a projected velocity. In some examples, the second radar return may be a reflected return if the magnitude of the projected velocity corresponds to a magnitude of the second radar return. In some instances, a vehicle, such as an autonomous vehicle, may be controlled at the exclusion of information from reflected returns.
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公开(公告)号：US11188082B2
公开(公告)日：2021-11-30
申请号：US16246208
申请日：2019-01-11
Applicant: Zoox, Inc.
Inventor： William Anthony Silva , Chuang Wang
Abstract: Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, based on predicted occluded areas in an environment. An occluded area can represent areas where sensors of the vehicle are unable to sense portions of the environment due to obstruction by another object. A first occluded region for an object is determined at a first time based on a location of the object. A predicted location for the object can be used to determine a predicted occluded region caused by the object at a second time after the first time. Predicted occluded regions can be determined for multiple trajectories for the vehicle to follow and/or at multiple points along such trajectories, and a trajectory can be selected based on associated occlusion scores and/or trajectory scores associated therewith. The vehicle can be controlled to traverse the environment based on the selected trajectory.
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公开(公告)号：US20210096566A1
公开(公告)日：2021-04-01
申请号：US16588529
申请日：2019-09-30
Applicant: Zoox, Inc.
Inventor： Chuang Wang , Joshua Kriser Cohen , James William Vaisey Philbin , Jacob Daniel Boydston , Yuesong Xie , Hang Ren , Yuan Zhang
Abstract: A collision avoidance system may validate, reject, or replace a trajectory generated to control a vehicle. The collision avoidance system may comprise a secondary perception component that may receive sensor data, receive and/or determine a corridor associated with operation of a vehicle, classify a portion of the sensor data associated with the corridor as either ground or an object, determine a position and/or velocity of at least the nearest object, determine a threshold distance associated with the vehicle, and control the vehicle based at least in part on the position and/or velocity of the nearest object and the threshold distance.
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