Lyft, Inc.

Jimmy Young

Alex Collier Mazure

Mohammad Ali Motie Share

Jatin Chopra

Kevin Wang

Man Geen Harold Li

Mu Xia

Chinmoy Dutta

Christopher Sholley

Ido Avigdor Bright

Jianzhe Luo

Bao Kham Chau

Adam Greenhall

Danial Afzal

Ryan Chung Leung

Humboldt Jayme Ramirez

The present application discloses an improved wait time optimization system, and corresponding methods and computer-readable media. According to disclosed embodiments, the wait time optimization system generates a customized wait time period for a provider computing device that has arrived at a pickup location associated with a matched transportation request. Upon the expiration of the customized wait time period, the wait time optimization system selectively enables a cancellation option for the provider computing device that enables a user of the provider computing device to cancel the transportation request, thereby releasing the provider computing device for a new transportation request match.

Optimizing provider computing device wait time periods associated with transportation requests

The present disclosure relates to systems, non-transitory computer-readable media, and methods for intelligently determining to assess (or not assess) a cancellation penalty and notifying a requestor device of such a penalty in response to either a requestor's selection to cancel a single transportation request for a requestor or a requestor's selection to cancel a shared-transportation request associated with multiple requestors. For example, the disclosed systems can generate conversion probabilities for a requestor reflecting if a cancellation penalty is assessed—and if the cancellation penalty is not assessed—for a cancellation of a transportation request for transport of a lone requestor. Based on the conversion probabilities, the disclosed systems customize a cancellation notice for a requestor device to either include or exclude the cancellation penalty. Additionally, or alternatively, in certain implementations, the disclosed systems generate a transportation efficiency metric for modifying a projected transportation route for a shared transportation to account for a cancellation of a shared-transportation request. Based on the transportation efficiency metric, the disclosed systems customize a cancellation notice for a requestor device to either include or exclude the cancellation penalty.

Intelligently customizing a cancellation notice for cancellation of a transportation request based on transportation features

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 session information from a requestor computing device in response to one or more session events. The system utilizes the received session information to determine a likelihood that the associated session on the requestor computing device will result in a transportation request. If the determined likelihood is above a threshold amount, the system generates an upfront dispatch that matches the associated session to a provider computing device. The system then reserves the provider computing device and generates a predicted dispatch for the reserved provider computing device.

Session-based transportation dispatch

The present disclosure relates assigning ride requests to providers based on the probability that a provider will accept the request. For example, one or more embodiments identify a first provider to assign the ride request. The system then generates a probability of acceptance for that provider. The system then determines an estimated time-to-arrival for the first provider and an alternate estimated time-to-arrival associated with a re-assigned provider. Based on the acceptance probability, the estimated time-to-arrival, and the alternate estimated time-to-arrival, the system then determines an expected time-to-arrival associated with the first provider. The system assigns ride requests to providers based on optimizing the expected time-to-arrival across multiple potential providers for a ride request.

Assigning rides based on probability of provider acceptance

Growing community of inventors

San Francisco, CA, United States of America

Jimmy Young