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1.发明授权公开(公告)号：US12169854B2
公开(公告)日：2024-12-17
申请号：US16820528
申请日：2020-03-16
Applicant: Lyft, Inc.
Inventor： Alya Abbott , Devjit Chakravarti , Alexander Wesley Contryman , Michael Jonathan DiCarlo , Julien van Hout , James Kevin Murphy , Renee Hei-Kyung Park , Ashivni Shekhawat , Zhan Zhang
IPC: G06Q30/0282 , G01C21/34 , G01C21/36 , G06Q50/40
Abstract: This disclosure describes a vehicle-motion-analysis system that can align axes for a provider device and a corresponding transportation vehicle based on the provider device's location and motion data as a basis for generating driving-event scores for particular driving events. In particular, the disclosed systems can generate axes-rotation parameters that align axes of a provider device with axes of a transportation vehicle. In addition, the disclosed systems can identify motion paths, motion patterns, or other driving behaviors that occur during particular driving events. Further, the disclosed systems can generate driving-event scores for such driving events and can customize a graphical user interface based on the driving-event scores to reflect a provider rating and/or a location rating.
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2.发明申请公开(公告)号：US20210287262A1
公开(公告)日：2021-09-16
申请号：US16820528
申请日：2020-03-16
Applicant: Lyft, Inc.
Inventor： Alya Abbott , Devjit Chakravarti , Alexander Wesley Contryman , Michael Jonathan DiCarlo , Julien van Hout , James Kevin Murphy , Renee Hei-kyung Park , Ashivni Shekhawat , Zhan Zhang
Abstract: This disclosure describes a vehicle-motion-analysis system that can align axes for a provider device and a corresponding transportation vehicle based on the provider device's location and motion data as a basis for generating driving-event scores for particular driving events. In particular, the disclosed systems can generate axes-rotation parameters that align axes of a provider device with axes of a transportation vehicle. In addition, the disclosed systems can identify motion paths, motion patterns, or other driving behaviors that occur during particular driving events. Further, the disclosed systems can generate driving-event scores for such driving events and can customize a graphical user interface based on the driving-event scores to reflect a provider rating and/or a location rating.
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公开(公告)号：US11763411B1
公开(公告)日：2023-09-19
申请号：US18059071
申请日：2022-11-28
Applicant: Lyft, Inc.
Inventor： Ricky Chachra , Tzu-Hsin Chiao , Ashivni Shekhawat , Christopher Sholley , Jerome Hong-Phat Thai , Adriel Frederick
Abstract: This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamically adjust the multiplier with machine learners to maintain a target estimated time of arrival for a provider device to fulfill a request received from a requestor device. In some embodiments, the methods, non-transitory computer readable media, and systems generate a multiplier report comprising a representation of a geographic area and an indication of the multiplier to facilitate inflow and outflow of provider devices within and without the geographic area.
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Patent Agency Ranking
公开(公告)号：US20200286106A1
公开(公告)日：2020-09-10
申请号：US16291964
申请日：2019-03-04
Applicant: Lyft, Inc.
Inventor： Guillaume Arnaud Candeli , Tzu-Hsin Chiao , Adriel Frederick , Varun Ramakrishna Pattabhiraman , Shaswat Pratap Shah , Ashivni Shekhawat , Yanqiao Wang , Irena Stephanie Vezich , Vijay Tupil Narasiman , Keshave Puranmalka
Abstract: This disclosure describes a transportation matching system that utilizes a combination of an offline transportation optimization model and an online transportation optimization model to generate transportation metric functions for predicted and received transportation requests based on optimization parameters. The disclosed systems utilize an offline transportation optimization model to predict transportation requests and to generate corresponding transportation metric functions for given locations over particular time intervals. The disclosed systems further utilize an online transportation optimization model to receive transportation requests and generate transportation metric functions for the received requests based at least in part on the predicted transportation requests and corresponding metric functions.
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公开(公告)号：US20240428362A1
公开(公告)日：2024-12-26
申请号：US18829595
申请日：2024-09-10
Applicant: Lyft, Inc.
Inventor： Ricky Chachra , Tzu-Hsin Chiao , Ashivni Shekhawat , Christopher Sholley , Jerome Hong-Phat Thai , Adriel Frederick
Abstract: This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamically adjust the multiplier with machine learners to maintain a target estimated time of arrival for a provider device to fulfill a request received from a requestor device. In some embodiments, the methods, non-transitory computer readable media, and systems generate a multiplier report comprising a representation of a geographic area and an indication of the multiplier to facilitate inflow and outflow of provider devices within and without the geographic area.
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公开(公告)号：US12094024B1
公开(公告)日：2024-09-17
申请号：US18469127
申请日：2023-09-18
Applicant: Lyft, Inc.
Inventor： Ricky Chachra , Tzu-Hsin Chiao , Ashivni Shekhawat , Christopher Sholley , Jerome Hong-Phat Thai , Adriel Frederick
Abstract: This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamically adjust the multiplier with machine learners to maintain a target estimated time of arrival for a provider device to fulfill a request received from a requestor device. In some embodiments, the methods, non-transitory computer readable media, and systems generate a multiplier report comprising a representation of a geographic area and an indication of the multiplier to facilitate inflow and outflow of provider devices within and without the geographic area.
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公开(公告)号：US11514546B2
公开(公告)日：2022-11-29
申请号：US16921698
申请日：2020-07-06
Applicant: Lyft, Inc.
Inventor： Ricky Chachra , Tzu-Hsin Chiao , Ashivni Shekhawat , Christopher Sholley , Jerome Hong-Phat Thai , Adriel Frederick
Abstract: This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamically adjust the multiplier with machine learners to maintain a target estimated time of arrival for a provider device to fulfill a request received from a requestor device. In some embodiments, the methods, non-transitory computer readable media, and systems generate a multiplier report comprising a representation of a geographic area and an indication of the multiplier to facilitate inflow and outflow of provider devices within and without the geographic area.
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公开(公告)号：US10706487B1
公开(公告)日：2020-07-07
申请号：US15810028
申请日：2017-11-11
Applicant: Lyft, Inc.
Inventor： Ricky Chachra , Tzu-Hsin Chiao , Ashivni Shekhawat , Christopher Sholley , Jerome Hong-Phat Thai , Adriel Frederick
Abstract: This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamically adjust the multiplier with machine learners to maintain a target estimated time of arrival for a provider device to fulfill a request received from a requestor device. In some embodiments, the methods, non-transitory computer readable media, and systems generate a multiplier report comprising a representation of a geographic area and an indication of the multiplier to facilitate inflow and outflow of provider devices within and without the geographic area.
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