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    UTILIZING ARTIFICIAL NEURAL NETWORKS TO EVALUATE ROUTES BASED ON GENERATED ROUTE TILES
    2.
    发明申请
    UTILIZING ARTIFICIAL NEURAL NETWORKS TO EVALUATE ROUTES BASED ON GENERATED ROUTE TILES 审中-公开

    公开(公告)号：US20190204088A1

    公开(公告)日：2019-07-04

    申请号：US15858775

    申请日：2017-12-29

    Applicant: Lyft, Inc.

    Inventor： Asif Haque ,  James Kevin Murphy ,  Yuanyuan Malek

    IPC: G01C21/30 ,  G06N3/02 ,  G06N5/02

    Abstract: This disclosure covers methods, non-transitory computer readable media, and systems that generate route tiles reflecting both GPS locations and map-matched locations for regions along a route traveled by a client device associated with a transportation vehicle. For example, in some implementations, the disclosed systems use an artificial neural network to analyze the route tiles and determine route-accuracy metrics indicating GPS locations or map-matched locations for particular regions along the route. The disclosed systems can then use the route-accuracy metrics to facilitate transport of requestors by, for example, determining a distance of the route or a location of a client device associated with a transportation vehicle.

    TRAVEL PATH AND LOCATION PREDICTIONS
    3.
    发明申请
    TRAVEL PATH AND LOCATION PREDICTIONS 审中-公开

    公开(公告)号：US20190051174A1

    公开(公告)日：2019-02-14

    申请号：US15675422

    申请日：2017-08-11

    Applicant: Lyft, Inc.

    Inventor： Asif Haque ,  James Kevin Murphy ,  Yuanyuan Pao

    IPC: G08G1/123 ,  G06Q10/02 ,  G06Q50/30

    Abstract: Embodiments provide techniques, including systems and methods, for determining projected locations for providers to better match providers in response to a transport request. Providers may be matched to a requestor based not only on a current location of the provider with respect to a request location, with a projected location of the provider that accounts for timing delays in processing transport requests, communication networks, etc. As such, projecting the projected location of the provider allows the dynamic transportation matching system to be matched more efficiently, reducing delay for the provider and requestor, and improving the efficiency of the system by preventing provider system resources from being taken from other service areas and decreasing provider inefficient rerouting upon matching.

    GEOHASH-RELATED LOCATION PREDICTIONS
    4.
    发明申请
    GEOHASH-RELATED LOCATION PREDICTIONS 审中-公开

    公开(公告)号：US20190037355A1

    公开(公告)日：2019-01-31

    申请号：US16148633

    申请日：2018-10-01

    Applicant: Lyft, Inc.

    Inventor： Yuanyuan Pao ,  Snir Kodesh ,  Jatin Chopra ,  Kevin Fan ,  Charlie Lin ,  Limin Shen ,  Dor Levi ,  Asif Haque ,  Zeynep Erkin Baz

    IPC: H04W4/02 ,  H04W4/44 ,  H04W4/021

    Abstract: Embodiments provide techniques, including systems and methods, for determining an estimated target pickup location for a corresponding transport request at a particular location, such as associated with a particular geohash. A requestor may send a request that is associated with a location that does not reflect the requestor's intent regarding where they would like to be met by the provider (i.e., “picked up”). GPS inaccuracies may cause the request location to inaccurately indicate where the requestor will be; for example, the request location may be inside a building while the requestor is waiting on a curb around a far side of the building. The target pickup location allows for a requestor and a provider to meet more efficiently, reducing delay for the provider and improving the efficiency of the system by preventing provider system resources from being taken from other service areas and decreasing provider downtime upon matching.

    Mapping and determining scenarios for geographic regions
    5.
    发明授权
    Mapping and determining scenarios for geographic regions 有权

    公开(公告)号：US11788846B2

    公开(公告)日：2023-10-17

    申请号：US16588729

    申请日：2019-09-30

    Applicant: Lyft, Inc.

    Inventor： David Tse-Zhou Lu ,  Asif Haque

    IPC: G01C21/32 ,  G05D1/02 ,  G06Q50/30

    CPC classification number: G01C21/32 ,  G05D1/0231 ,  G05D1/0257 ,  G05D1/0291 ,  G06Q50/30 ,  G05D2201/0213

    Abstract: Systems, methods, and non-transitory computer-readable media can determine sensor data captured by at least one sensor of a vehicle while navigating a road segment. A plurality of features describing the road segment can be extracted from the sensor data. A map representation of the road segment can be determined based at least in part on the sensor data and the plurality of features extracted from the sensor data, the map representation being determined as the vehicle navigates the road segment. While the map representation of the road segment is being determined, at least one scenario associated with the road segment can be determined based at least in part on the map representation and the plurality of features extracted from the sensor data.

    ROAD SEGMENT SIMILARITY DETERMINATION
    6.
    发明申请
    ROAD SEGMENT SIMILARITY DETERMINATION 有权

    公开(公告)号：US20220001863A1

    公开(公告)日：2022-01-06

    申请号：US17374654

    申请日：2021-07-13

    Applicant: Lyft, Inc.

    Inventor： Asif Haque ,  Mark Douglas Huyler ,  Gerard Joyce ,  Ying Liu ,  David Tse-Zhou Lu ,  Sameer Qureshi ,  Vinay Shet

    IPC: B60W30/095 ,  B60W30/09 ,  B60W40/06

    Abstract: Systems, methods, and non-transitory computer-readable media can determine a road segment. A set of features associated with the road segment can be determined based at least in part on data captured by one or more sensors of a vehicle. A level of similarity between the road segment and each of a set of road segment types can be determined by comparing the set of features to features associated with each of the set of road segment types. The road segment can be classified as a road segment type based on the level of similarity. Scenario information associated with the road segment can be determined based on the classified road segment type.

    Automatic generation of human-understandable geospatial descriptors
    7.
    发明授权
    Automatic generation of human-understandable geospatial descriptors 有权

    公开(公告)号：US11068788B2

    公开(公告)日：2021-07-20

    申请号：US15829965

    申请日：2017-12-03

    Applicant: Lyft, Inc.

    Inventor： Yuanyuan Malek ,  James Kevin Murphy ,  Asif Haque ,  Ramesh Rangarajan Sarukkai

    IPC: G06N5/02 ,  G06Q50/30 ,  G06N20/00 ,  G06F16/29

    Abstract: A disclosed method may include receiving geographic coordinates of a location at which two parties are to rendezvous, generating a human-understandable geospatial descriptor for the request location, and sending the descriptor to respective devices of the two parties for presentation to the two parties. Generating the human-understandable geospatial descriptor may include identifying a human-visible feature in the vicinity of the request location that is labeled within available map data, selecting, based on a descriptor generation model, a reference expression relative to the identified feature, and applying a grammar-based constructor to the label and the selected reference expression to form the human-understandable geospatial descriptor. The model may be tuned using machine learning. The two parties may include a ride requestor and a ride provider in a ridesharing service. The identified feature may be a point of interest, landmark, street name, intersection, marker, or structure.

    MAPPING AND DETERMINING SCENARIOS FOR GEOGRAPHIC REGIONS
    8.
    发明申请
    MAPPING AND DETERMINING SCENARIOS FOR GEOGRAPHIC REGIONS 有权

    公开(公告)号：US20210095970A1

    公开(公告)日：2021-04-01

    申请号：US16588729

    申请日：2019-09-30

    Applicant: Lyft, Inc.

    Inventor： David Tse-Zhou Lu ,  Asif Haque

    IPC: G01C21/32 ,  G05D1/02 ,  G06Q50/30

    Abstract: Systems, methods, and non-transitory computer-readable media can determine sensor data captured by at least one sensor of a vehicle while navigating a road segment. A plurality of features describing the road segment can be extracted from the sensor data. A map representation of the road segment can be determined based at least in part on the sensor data and the plurality of features extracted from the sensor data, the map representation being determined as the vehicle navigates the road segment. While the map representation of the road segment is being determined, at least one scenario associated with the road segment can be determined based at least in part on the map representation and the plurality of features extracted from the sensor data.

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