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公开(公告)号：US11887483B2
公开(公告)日：2024-01-30
申请号：US17808238
申请日：2022-06-22
Applicant: Lyft, Inc.
Inventor： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
Abstract: The present application discloses an improved transportation matching system, and corresponding methods and computer-readable media. According to disclosed embodiments, a transportation matching system trains a predictive request model to generate a metric predicted to trigger an increase in transportation provider activity within the geographic area for a given time period. Furthermore, the system determines a predicted gap between expected request activity and expected transportation provider activity for the geographic area during a future time period, utilizes the predictive request model and the predicted gap to generate a metric for the geographic area, and generates an interactive map associated with a customized schedule for the geographic area and the future time period based on the generated metric.
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公开(公告)号：US20220358844A1
公开(公告)日：2022-11-10
申请号：US17808238
申请日：2022-06-22
Applicant: Lyft, Inc.
Inventor： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
Abstract: The present application discloses an improved transportation matching system, and corresponding methods and computer-readable media. According to disclosed embodiments, a transportation matching system trains a predictive request model to generate a metric predicted to trigger an increase in transportation provider activity within the geographic area for a given time period. Furthermore, the system determines a predicted gap between expected request activity and expected transportation provider activity for the geographic area during a future time period, utilizes the predictive request model and the predicted gap to generate a metric for the geographic area, and generates an interactive map associated with a customized schedule for the geographic area and the future time period based on the generated metric.
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公开(公告)号：US11386789B1
公开(公告)日：2022-07-12
申请号：US15809618
申请日：2017-11-10
Applicant: Lyft, Inc.
Inventor： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
Abstract: The present application discloses an improved transportation matching system, and corresponding methods and computer-readable media. According to disclosed embodiments, a transportation matching system trains a predictive request model to generate a metric predicted to trigger an increase in transportation provider activity within the geographic area for a given time period. Furthermore, the system determines a predicted gap between expected request activity and expected transportation provider activity for the geographic area during a future time period, utilizes the predictive request model and the predicted gap to generate a metric for the geographic area, and generates an interactive map associated with a customized schedule for the geographic area and the future time period based on the generated metric.
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公开(公告)号：US12249001B2
公开(公告)日：2025-03-11
申请号：US17100147
申请日：2020-11-20
Applicant: Lyft, Inc.
Inventor： Praveen Athmanathan Panneer Selvam , David Elijah Alpern Boehm , Davide Crapis , Ramon Dario Iglesias , Varun Kashyap Krishnan , Derek William Salama , Shashi Kant Sharma , Xiaoling Charlene Zhou
IPC: G06Q50/40 , G06N5/04 , G06N20/00 , G06Q10/0631 , G06Q30/0204 , H04L67/12
Abstract: The present application discloses systems, methods, and computer-readable media that can dynamically control a number of provider devices operating in a prioritized-dispatch mode by determining a range of prioritized-dispatch-mode slots for a target time based on differences between value metrics received by provider devices operating in multiple dispatch modes and sending availability nudges to provider devices based on the range of prioritized-dispatch-mode slots. For instance, the disclosed systems can generate a threshold-noticeable-value difference between historical value metrics received by provider devices while operating in a prioritized-dispatch mode and in a basic-dispatch mode. Based on the threshold-noticeable-value difference, the disclosed systems determine a range of slots for the prioritized-dispatch mode during a target time period for a geographic area. Based on the determined range of slots, the disclosed systems can transmit prioritized-mode-availability indicators to provider devices to indicate varying levels of availability of the prioritized-dispatch mode for the geographic area.
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公开(公告)号：US20220164912A1
公开(公告)日：2022-05-26
申请号：US17100147
申请日：2020-11-20
Applicant: Lyft, Inc.
Inventor： Praveen Athmanathan Panneer Selvam , David Elijah Alpern Boehm , Davide Crapis , Ramon Dario Iglesias , Varun Kashyap Krishnan , Derek William Salama , Shashi Kant Sharma , Xiaoling Charlene Zhou
Abstract: The present application discloses systems, methods, and computer-readable media that can dynamically control a number of provider devices operating in a prioritized-dispatch mode by determining a range of prioritized-dispatch-mode slots for a target time based on differences between value metrics received by provider devices operating in multiple dispatch modes and sending availability nudges to provider devices based on the range of prioritized-dispatch-mode slots. For instance, the disclosed systems can generate a threshold-noticeable-value difference between historical value metrics received by provider devices while operating in a prioritized-dispatch mode and in a basic-dispatch mode. Based on the threshold-noticeable-value difference, the disclosed systems determine a range of slots for the prioritized-dispatch mode during a target time period for a geographic area. Based on the determined range of slots, the disclosed systems can transmit prioritized-mode-availability indicators to provider devices to indicate varying levels of availability of the prioritized-dispatch mode for the geographic area.
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Patent Agency Ranking
公开(公告)号：US20200082315A1
公开(公告)日：2020-03-12
申请号：US16125551
申请日：2018-09-07
Applicant: Lyft, Inc.
Inventor： Davide Crapis , Michael Yoshizawa , Gaurav Gupta , Ehud Milo , Akshay Balwally , Cameron Philip Bruggeman , Benjamin Owen Dear , Benedict Kuester , Lei Tang , Jia Yan
Abstract: This disclosure describes a transportation matching system that manages the allocation of transportation providers by training and utilizing multiple machine-learning models to identify, allocate, and serve specific transportation providers with customized opportunities to relocate the transportation providers between geocoded areas in a geocoded region. For instance, the transportation matching system trains and utilizes an incremental provider model, a provider allocation model, and personalized provider behavioral models as well as a customized provider interface generator to satisfy anticipated transportation requests and improve transportation matching within a geocoded region.
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公开(公告)号：US20200082314A1
公开(公告)日：2020-03-12
申请号：US16125540
申请日：2018-09-07
Applicant: Lyft, Inc.
Inventor： Davide Crapis , Michael Yoshizawa , Gaurav Gupta , Ehud Milo , Akshay Balwally , Jia Yan
Abstract: This disclosure describes a transportation matching system that manages the allocation of transportation providers by training and utilizing multiple machine-learning models to identify, allocate, and serve specific transportation providers with customized opportunities to relocate the transportation providers between geocoded areas in a geocoded region. For instance, the transportation matching system trains and utilizes an incremental provider model, a provider allocation model, and personalized provider behavioral models as well as a customized provider interface generator to satisfy anticipated transportation requests and improve transportation matching within a geocoded region.
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公开(公告)号：US12056646B1
公开(公告)日：2024-08-06
申请号：US17069276
申请日：2020-10-13
Applicant: Lyft, Inc.
Inventor： Hao Yi Ong , Davide Crapis , Su Wang , Kevin Hsing-Chiang Fan
IPC: G06Q10/0637 , G06F16/28 , G06F30/20 , G06Q10/0635 , G06Q10/0639 , G06Q50/40 , G06F111/08 , G06Q10/067 , G06Q30/0204
CPC classification number: G06Q10/06375 , G06F16/285 , G06F30/20 , G06Q10/0635 , G06Q10/06393 , G06Q50/40 , G06F2111/08 , G06Q10/067 , G06Q30/0204
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that validate the performance of a dispatch model, such as a directive-based model, utilized for facilitating transportation matching services. For example, the disclosed systems can generate critical situations clusters composed of groups of critical transportation provider performance scenarios. From the critical situation clusters, the disclosed systems can sample one or more critical transportation provider situations that present a risk of degradation for the transportation matching services. Accordingly, the disclosed systems can measure a performance of the dispatch model by employing a simulation model that utilizes the dispatch model to propagate the critical transportation provider situations through time.
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公开(公告)号：US20240127697A1
公开(公告)日：2024-04-18
申请号：US18396134
申请日：2023-12-26
Applicant: Lyft, Inc.
Inventor： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
Abstract: The present application discloses an improved transportation matching system, and corresponding methods and computer-readable media. According to disclosed embodiments, a transportation matching system trains a predictive request model to generate a metric predicted to trigger an increase in transportation provider activity within the geographic area for a given time period. Furthermore, the system determines a predicted gap between expected request activity and expected transportation provider activity for the geographic area during a future time period, utilizes the predictive request model and the predicted gap to generate a metric for the geographic area, and generates an interactive map associated with a customized schedule for the geographic area and the future time period based on the generated metric.
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公开(公告)号：US20200082313A1
公开(公告)日：2020-03-12
申请号：US16125527
申请日：2018-09-07
Applicant: Lyft, Inc.
Inventor： Davide Crapis , Michael Yoshizawa , Gaurav Gupta , Ehud Milo , Akshay Balwally , Jia Yan
Abstract: This disclosure describes a transportation matching system that manages the allocation of transportation providers by training and utilizing multiple machine-learning models to identify, allocate, and serve specific transportation providers with customized opportunities to relocate the transportation providers between geocoded areas in a geocoded region. For instance, the transportation matching system trains and utilizes an incremental provider model, a provider allocation model, and personalized provider behavioral models as well as a customized provider interface generator to satisfy anticipated transportation requests and improve transportation matching within a geocoded region.
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