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    LOCALIZATION ADAPTATION BASED ON WEATHER ESTIMATION
    12.
    发明申请
    LOCALIZATION ADAPTATION BASED ON WEATHER ESTIMATION 有权

    公开(公告)号：US20220011116A1

    公开(公告)日：2022-01-13

    申请号：US16922052

    申请日：2020-07-07

    Applicant: Waymo LLC

    Inventor： Samuel Panzer ,  Michael Montemerlo ,  Michael James

    IPC: G01C21/30 ,  G05D1/02 ,  G01S13/89 ,  B60W60/00

    Abstract: Aspects of the disclosure provide for localizing a vehicle. In one instance, a weather condition in which the vehicle is currently driving may be identified. A plurality of sensor inputs including intensity information, elevation information, and radar sensor information may be received. For each of the plurality of sensor inputs, an alignment score is determined by comparing the intensity information, elevation information, and radar sensor information to a corresponding pre-stored image for each of the intensity information, the elevation information, and the radar sensor information. A set of weights for the plurality of sensor inputs may be determined based on the identified weather condition. The alignment scores may then be combined using the set of weights in order to localize the vehicle.

    Speed and Route Planning in View of Weather
    13.
    发明申请
    Speed and Route Planning in View of Weather 有权

    公开(公告)号：US20210293573A1

    公开(公告)日：2021-09-23

    申请号：US17207663

    申请日：2021-03-20

    Applicant: Waymo LLC

    Inventor： Boris Sofman ,  Benjamin Pitzer ,  Michael James

    IPC: G01C21/36 ,  G01C21/34

    Abstract: An example method involves identifying one or more potential route segments that collectively connect at least two geographical points, receiving spatiotemporal weather information that predicts future weather conditions along each of the potential segments, and, for each potential segment, evaluating a partial cost function that comprises a summation of a set of segment-weighted cost factors, where at least one segment-weighted cost factor comprises an adverse weather risk factor based on the future weather conditions along the potential segment. The method also involves selecting, based on a minimization of a total cost function, a set of selected segments and corresponding segment target speeds for the vehicle to utilize while traversing between the at least two geographical points so as to avoid adverse weather conditions, the total cost function being the sum of partial cost functions associated with a set of segments that collectively connect the at least two geographical points.

    Redundant Hardware System For Autonomous Vehicles
    14.
    发明申请
    Redundant Hardware System For Autonomous Vehicles 审中-公开

    公开(公告)号：US20200180653A1

    公开(公告)日：2020-06-11

    申请号：US16215713

    申请日：2018-12-11

    Applicant: Waymo LLC

    Inventor： Emily Chi ,  Ryan Joseph Andrade ,  Andreas Wendel ,  Michael James ,  Christian Lauterbach ,  Etai Bruhis ,  Christopher Kennedy Ludwick ,  Alexander Zbrozek ,  Pieter Kapsenberg ,  Zhuyuan Liu ,  Daniel Rosenband

    IPC: B60W50/029 ,  G05D1/00 ,  B60W10/04 ,  B60W10/20 ,  B60W50/02

    Abstract: The technology relates to partially redundant equipment architectures for vehicles able to operate in an autonomous driving mode. Aspects of the technology employ fallback configurations, such as two or more fallback sensor configurations that provide some minimum amount of field of view (FOV) around the vehicle. For instance, different sensor arrangements are logically associated with different operating domains of the vehicle. Fallback configurations for computing resources and/or power resources are also provided. Each fallback configuration may have different reasons for being triggered, and may result in different types of fallback modes of operation. Triggering conditions may relate, e.g., to a type of failure, fault or other reduction in component capability, the current driving mode, environmental conditions in the vicinity of vehicle or along a planned route, or other factors. Fallback modes may involve altering a previously planned trajectory, altering vehicle speed, and/or altering a destination of the vehicle.

    ROAD CONDITION DEEP LEARNING MODEL
    17.
    发明公开
    ROAD CONDITION DEEP LEARNING MODEL 审中-公开

    公开(公告)号：US20230409971A1

    公开(公告)日：2023-12-21

    申请号：US18238741

    申请日：2023-08-28

    Applicant: Waymo LLC

    Inventor： Xin Zhou ,  Roshni Cooper ,  Michael James

    IPC: G06N20/00 ,  B60W40/06 ,  B60W60/00 ,  G05D1/02 ,  G06N3/08

    CPC classification number: G06N20/00 ,  B60W40/06 ,  B60W60/0015 ,  G05D1/0231 ,  G05D1/0255 ,  G05D1/0257 ,  G06N3/08 ,  G05D2201/0213 ,  B60W2555/20 ,  B60W2420/52 ,  B60W2420/42 ,  B60W2420/54

    Abstract: The technology relates to using on-board sensor data, off-board information and a deep learning model to classify road wetness and/or to perform a regression analysis on road wetness based on a set of input information. Such information includes on-board and/or off-board signals obtained from one or more sources including on-board perception sensors, other on-board modules, external weather measurement, external weather services, etc. The ground truth includes measurements of water film thickness and/or ice coverage on road surfaces. The ground truth, on-board and off-board signals are used to build the model. The constructed model can be deployed in autonomous vehicles for classifying/regressing the road wetness with on-board and/or off-board signals as the input, without referring to the ground truth. The model can be applied in a variety of ways to enhance autonomous vehicle operation, for instance by altering current driving actions, modifying planned routes or trajectories, activating on-board cleaning systems, etc.

    Localization adaptation based on weather estimation
    18.
    发明授权
    Localization adaptation based on weather estimation 有权

    公开(公告)号：US11761769B2

    公开(公告)日：2023-09-19

    申请号：US17708477

    申请日：2022-03-30

    Applicant: Waymo LLC

    Inventor： Samuel Panzer ,  Michael Montemerlo ,  Michael James

    IPC: G01C21/30 ,  G05D1/02 ,  B60W60/00 ,  G01S13/89

    CPC classification number: G01C21/30 ,  B60W60/001 ,  G01S13/89 ,  G05D1/0274 ,  B60W2555/20

    Abstract: Aspects of the disclosure provide for localizing a vehicle. In one instance, a weather condition in which the vehicle is currently driving may be identified. A plurality of sensor inputs including intensity information, elevation information, and radar sensor information may be received. For each of the plurality of sensor inputs, an alignment score is determined by comparing the intensity information, elevation information, and radar sensor information to a corresponding pre-stored image for each of the intensity information, the elevation information, and the radar sensor information. A set of weights for the plurality of sensor inputs may be determined based on the identified weather condition. The alignment scores may then be combined using the set of weights in order to localize the vehicle.

    PUDDLE OCCUPANCY GRID FOR AUTONOMOUS VEHICLES
    20.
    发明申请
    PUDDLE OCCUPANCY GRID FOR AUTONOMOUS VEHICLES 有权

    公开(公告)号：US20220185313A1

    公开(公告)日：2022-06-16

    申请号：US17118758

    申请日：2020-12-11

    Applicant: WAYMO LLC

    Inventor： Yuchi Wang ,  Michael James ,  Robert Chen ,  Derrick Dominic

    IPC: B60W60/00 ,  G06K9/62 ,  G06K9/00

    Abstract: Aspects of the disclosure relate to generating a puddle occupancy grid including a plurality of cells. For instance, a first probability value for a puddle being located at a first location generated using sensor data from a first sensor may be received. A second probability value for a puddle being located at a second location generating using sensor data from a second sensor different from the first sensor may be received. A first cell may be identified from the plurality of cells using the first location. The first cell may also be identified using the second location. A value for the cell may be generated using the first probability value and the second probability value.

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