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公开(公告)号：US11494714B2
公开(公告)日：2022-11-08
申请号：US16780712
申请日：2020-02-03
申请人： Lyft, Inc.
发明人： Gaurav Gupta , Ehud Milo , Omar Khalid , Amy J. Kim , Jacky Yi Han Lu , Richard Zhao , Robert A. Farmer
摘要： 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：US11887483B2
公开(公告)日：2024-01-30
申请号：US17808238
申请日：2022-06-22
申请人： Lyft, Inc.
发明人： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
摘要： 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
申请人： Lyft, Inc.
发明人： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
摘要： 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
申请人： Lyft, Inc.
发明人： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
摘要： 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：US20240127697A1
公开(公告)日：2024-04-18
申请号：US18396134
申请日：2023-12-26
申请人： Lyft, Inc.
发明人： Saurabh Bajaj , Davide Crapis , Eran Davidov , Omar Khalid , Ehud Milo
摘要： 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：US20200250600A1
公开(公告)日：2020-08-06
申请号：US16780712
申请日：2020-02-03
申请人： Lyft, Inc.
发明人： Gaurav Gupta , Ehud Milo , Omar Khalid , Amy J. Kim , Jacky Yi Han Lu , Richard Zhao , Robert A. Farmer
摘要： 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：US10552773B1
公开(公告)日：2020-02-04
申请号：US16125563
申请日：2018-09-07
申请人： Lyft, Inc.
发明人： Akash Gaurav Shah , Ehud Milo , Omar Khalid , Amy J. Kim , Jacky Yi Han Lu , Richard Zhao , Robert A. Farmer
摘要： 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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