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    Method and apparatus for determining vehicle class based upon audio data
    11.
    发明授权
    Method and apparatus for determining vehicle class based upon audio data 有权

    公开(公告)号：US11423925B2

    公开(公告)日：2022-08-23

    申请号：US17129477

    申请日：2020-12-21

    Applicant: HERE Global B.V.

    Inventor： Leon Stenneth ,  Jeremy Michael Young

    IPC: H04R29/00 ,  G10L25/51 ,  G06N5/04 ,  G06N20/00 ,  G10L25/18

    Abstract: A method, apparatus and computer program product are provided to identify the class of vehicle driving over a road surface based upon audio data collected as the vehicle drives thereover. With respect to predicting a class of a vehicle, audio data is obtained that is created by the vehicle while driving over the road surface. The audio data includes one or more audio frequency features and/or one or more audio amplitude features. The audio data including the one or more audio frequency features and/or the one or more audio amplitude features is provided to a machine learning model and the class of the vehicle that created the audio data is predicted utilizing the machine learning model. A method, apparatus and computer program product are also provided for training the machine learning model to predict the class of the vehicle driving over the road surface.

    METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR GENERATING A TRANSITION VARIABILITY INDEX RELATED TO AUTONOMOUS DRIVING
    12.
    发明申请
    METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR GENERATING A TRANSITION VARIABILITY INDEX RELATED TO AUTONOMOUS DRIVING 有权

    公开(公告)号：US20220063673A1

    公开(公告)日：2022-03-03

    申请号：US17122497

    申请日：2020-12-15

    Applicant: HERE GLOBAL B.V.

    Inventor： Leon Stenneth ,  Jerome Beaurepaire ,  Jeremy Michael Young

    IPC: B60W60/00 ,  B60W50/00 ,  G05D1/00

    Abstract: A method, apparatus and computer program product are provided for generating a transition variability index related to autonomous driving. In this regard, a first transition variability index is calculated. The first transition variability index is indicative of a first degree of variability in relation to transition of vehicles from respective autonomous levels while traveling proximate a first spatial reference point. Furthermore, a second transition variability index is generated. The second transition variability index is indicative of a second degree of variability in relation to transition of vehicles from respective autonomous levels while traveling along proximate a second spatial reference point. Updating of transition data associated with one of the first and second spatial reference points relative to another one of the first and second spatial reference points is then prioritized based on a comparison between the first transition variability index and the second transition variability index.

    METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR VEHICLE LOCALIZATION VIA AMPLITUDE AUDIO FEATURES
    14.
    发明申请
    METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR VEHICLE LOCALIZATION VIA AMPLITUDE AUDIO FEATURES 有权

    公开(公告)号：US20210349939A1

    公开(公告)日：2021-11-11

    申请号：US16868171

    申请日：2020-05-06

    Applicant: HERE Global B.V.

    Inventor： Jeremy Michael Young ,  Leon Stenneth

    IPC: G06F16/635 ,  G06F16/638 ,  G06F16/687 ,  G06F16/68 ,  B60W60/00 ,  H04W4/029

    Abstract: A method, apparatus and computer program product are provided for vehicle localization via amplitude audio features. In this regard, an amplitude audio signature of audio data received from one or more audio sensors of a vehicle is determined. Location data associated with the vehicle is also determined. Based on the location data for the vehicle, at least a portion of an audio feature map is selected. The audio feature map stores amplitude audio signatures associated with road noise in relation to respective locations. Furthermore, the amplitude audio signature of the audio data is compared with the amplitude audio signatures of the audio feature map. Based on the comparison between the amplitude audio signature of the audio data and the amplitude audio signatures of the audio feature map, a location of the vehicle is refined to generate updated location data for the vehicle.

    Apparatus and methods for providing routes for vehicles using spare tires
    15.
    发明授权
    Apparatus and methods for providing routes for vehicles using spare tires 有权

    公开(公告)号：US12276518B2

    公开(公告)日：2025-04-15

    申请号：US18085357

    申请日：2022-12-20

    Applicant: HERE GLOBAL B.V.

    Inventor： Jerome Beaurepaire ,  Leon Stenneth ,  Jeremy Michael Young

    IPC: G01C21/36 ,  G01C21/34 ,  G06N20/00

    Abstract: An apparatus, method and computer program product are provided for predicting tire temperature levels. In one example, the apparatus receives input data indicating attributes of the target vehicle and attributes of target routes for the target vehicle. The apparatus causes a machine learning model to generate output data as a function of the input data, where the output data indicate a subset of the target routes of which the target vehicle can successfully traverse while using the at least one spare tire. The machine learning model is trained to generate the output data as a function of the input data based on training data, where the training data indicate events in which vehicles used spare tires to traverse routes. The training data indicate attributes of the vehicles and attributes of the routes.

    Method and apparatus for prediciting a map object based upon audio data
    17.
    发明授权
    Method and apparatus for prediciting a map object based upon audio data 有权

    公开(公告)号：US11885637B2

    公开(公告)日：2024-01-30

    申请号：US17129440

    申请日：2020-12-21

    Applicant: HERE Global B.V.

    Inventor： Leon Stenneth ,  Jeremy Michael Young

    IPC: G01C21/00 ,  G06N20/00 ,  G01C21/30 ,  G01C21/36 ,  H04R3/00

    CPC classification number: G01C21/3822 ,  G01C21/30 ,  G01C21/3691 ,  G01C21/3848 ,  G06N20/00 ,  H04R3/005

    Abstract: A method, apparatus and computer program product are provided to predict a map object based at least in part on audio data. With respect to predicting a map object, audio data created by a vehicle while driving over a road surface is obtained. The audio data includes one or more audio amplitude features, one or more audio frequency features or a combination of audio amplitude features and audio frequency features. The audio data including the one or more audio amplitude features is provided to a machine learning model and the map object that created the audio data while the vehicle interacted therewith is predicted utilizing the machine learning model. A method, apparatus and computer program product are also provided for training the machine learning model to predict the map object based at least in part on audio data.

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