Lyft, Inc.

Akash Gaurav Shah

Ehud Milo

Omar Khalid

Robert Anthony Farmer

Amy J Kim

Jacky Yi Han Lu

Richard Zhao

Lucas Jon Van Houten

Michael Jonathan DiCarlo

Preet Singh Anand

Desmond Mawuko Torkornoo

Alya Abbott

Andrew Jie Sun

Gaurav Gupta

Linwei Chen

Renee Hei-Kyung Park

Cameron Philip Bruggeman

Emre Arda Sisbot

Carter Robert Ren-Deh Wang

Louis John Zell

Paul Alfred Dickinson

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.

Using geocoded provider models to improve efficiency of a transportation matching system

A micromobility transit vehicle service task management system and related methods are disclosed. In one embodiment, a system determines service tasks to be executed based on a level of availability of one or more micromobility transit vehicles. A value for each of the tasks is determined based on a cost to perform the task and value generated by an increase in availability of the one or more micromobility transit vehicles, for dynamic transportation matching, from execution of the task. The tasks may be prioritized into an order of execution that maximizes a total of the values of the tasks. The determined values of the tasks may be adjusted in the prioritization of the tasks based on the order of execution of the tasks. A navigational task route may be generated based on the prioritized tasks and assigned to a technician device to guide a technician to each of the tasks.

Systems and methods for assigning tasks based on priorities determined for the tasks

Methods and systems for processing telematics data are provided. In one embodiment, a method is provided that includes obtaining telematics information from a first device associated with a vehicle. The telematics information may indicate operations of the vehicle. An anomalous operation of the vehicle may then be determined based on the telematics information. The method may further include determining whether the anomalous operation of the vehicle is a vehicle collision. If the anomalous operation of the vehicle is a vehicle collision, routing information for the vehicle may be received that identifies previous locations of the vehicle. The routing information may then be compared with the telematics information to identify a location of the vehicle collision.

Telematics data processing for collision detection

Efficiency of a transportation matching system using geocoded provider models

Growing community of inventors

Millbrae, CA, United States of America

Akash Gaurav Shah