Lyft, Inc.

Charlie Lin

Limin Shen

Dor Levi

Jatin Chopra

Asif Haque

Snir Kodesh

Zeynep Erkin Baz

Kevin Fan

Yuanyuan Pao

Thaddeus Insuk Hwang

Yuanyuan Malek

The present application discloses an improved transportation matching system, and corresponding methods and computer-readable media. According to disclosed embodiments, a transportation matching system receives a session indicator and device-based location. The system utilizes the received request and device-based location to identify and analyze historical transportation matching system information. The system then generates a confidence score based on this information that indicates a level of confidence that the device-based location is a pickup location associated with the request. If the generated confidence score exceeds a predetermined threshold, the system provides display components to a requestor computing device that enable confirmation of the transportation request with a single user interaction.

Optimizing pickup locations for transportation requests based on context information utilizing a continued touch gesture

Optimizing pickup locations for transportation requests based on a confidence score for a context information

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.

Geohash-related location predictions

Optimizing pickup locations for transportation requests based on context information

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San Francisco, CA, United States of America

Charlie Lin