Lyft, Inc.

Jatin Chopra

Dor Levi

Mayank Gulati

Asif Haque

Charles Parker Spielman

Snir Kodesh

Limin Shen

Karina Goot

Charlie Lin

Michael Francis Lodick

Zeynep Erkin Baz

Priyanka Madhav Phatak

Yuanyuan Pao

Kevin Fan

Christopher Sholley

Jimmy Young

Jianzhe Luo

Danial Afzal

Romain Clément

Garrett Korda Drayna

Chinmoy Dutta

Ido Avigdor Bright

Cyril Francis Meyer, Iii

David Louis Bergman Quaid

Adam Greenhall

Ryan Chung Leung

Richard Steven Chelminski

Griffin Thomson

Methods and systems for planning and creating transportation routes with multiple modalities are provided. In one embodiment, a method is provided that includes receiving a transportation request that includes a first location and a second location. A transportation proposal may then be generated including a route for transportation between the first location and the second location. The method may then include determining modalities available to provide transportation and determining respective transportation segments for the modalities, and at least a subset of the transportation segments may be combined to form the route for transportation. The transportation proposal, including the route for transportation, may then be transmitted for display on a mobile device.

Transportation route planning and generation

The disclosed computer-implemented method may include using location data from multiple devices improve the accuracy of location estimates for a rideable vehicle and/or provide calibration for location information. In some examples, at the end of a ride the system may record the location of the rider's device to augment the location data from the rideable vehicle. In another example, when a batch of rideable vehicles are delivered to a location, the system may use the location of the operator's device and/or the locations of other rideable vehicles in the batch to increase the accuracy of data for the location of any given rideable vehicle. In some embodiments, the system may detect the number of functioning location sensors to determine the confidence in the location of the vehicle. This confidence information can then be used in network decisions such as matching. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for determining rideable vehicle locations

Embodiments provide techniques, including systems and methods, for assignment and/or reassignment of transport requests received within a request matching time period. For example, transport requests received during a request matching time period, as well as requests determined to be eligible during the request matching time period for reassignment, are associated with a location identifier (e.g., geohash) and are pooled at a dynamic transportation matching system in order for a dynamic assignment and/or reassignment that may reduce a metric (e.g., an overall estimated time of arrival (ETA) for requests) associated with the dynamic transportation matching system.

Dynamic optimized reassignment of providers at a geohash level

Techniques are disclosed for systems and methods to provision a mobile mesh network. A mobile mesh network provisioning system includes a wireless communications module configured to be physically coupled to a fleet vehicle and to form at least a part of a mobile mesh network including a plurality of mobile nodes corresponding to a respective plurality of fleet vehicles, and a logic device configured to communicate with the wireless communications module. The logic device is configured to determine a data route through at least a portion of the mobile mesh network based, at least in part, on a target data destination and a mobile node participation variability associated with the mobile mesh network, and to transmit fleet data associated with the fleet vehicle along the determined data route.

Mobile mesh network provisioning systems and methods

Methods and systems for detecting when users deviate from a provided transportation route and for correcting the transportation route in response to such user deviations is presented. In one embodiment, a method is provided including detecting a changed condition for a transportation route between a first location and a second location. The transportation route may include multiple transportation segments. A first transportation segment designating a first modality may be identified, wherein the changed condition decreases a likelihood that vehicles associated with the first modality will be available to service the first transportation segment. In response, a second transportation segment designating a second modality different from the first modality is generated. The first transportation segment is then replaced with the second transportation segment in the transportation route.

Multi-modal transportation system

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

Methods and systems for analyzing, ranking, and presenting multi-modality transportation proposals are presented. In one embodiment, a method is provided that includes receiving a request for transportation and generating proposals that include routes for transportation an origin location and a destination location of the request. The proposals each include segment(s) corresponding to a portion of a route and at least one modality identifying a type of transportation for the segment(s). Proposal scores may then be calculated for each of the proposals. Proposal scores for a proposal may be calculated based on a disutility measure of the proposal that measures a predicted inconvenience for a user following the route identified by the proposal. The proposals may be ranked based on the proposal scores and the ranking may be transmitted to a mobile device for display on the mobile device.

Transportation proposal filtration, comparison, and inconvenience measurement

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

Growing community of inventors

San Francisco, CA, United States of America

Jatin Chopra