Gm Cruise Holdings LLC

Nikola Noxon

Christopher Charles Ward

Curt Harrington

Kunal Mehta

Saranya Konala

Devina Jain

Edward Henry Forscher

Kelan Fitzgerald Stoy

Michael John Mehallow

Travis McCawley

A method is described and includes acquiring sensor data produced by sensors of a plurality of vehicles traversing an area including a location of a user, wherein the vehicles traversing the area comprise a subset of a fleet of vehicles for providing rideshare services; processing the acquired sensor data to determine a category of the user; selecting a vehicle from the fleet of vehicles based on the category of the user, wherein the selected vehicle comprises at least one accommodation corresponding to the category of the user; and dispatching the selected vehicle to a pick-up location designated by the user.

Rideshare service fleet optimization using vehicle sensor data

Methods and systems are provided for detecting and responding to dangerous road users. In some aspects, a process can include steps for receiving sensor data of a detected object from an autonomous vehicle, determining whether the detected object is exhibiting a dangerous attribute, generating output data based on the determining of whether the detected object is exhibiting the dangerous attribute, and updating a machine learning model based on the output data relating to the dangerous attribute.

Dangerous road user detection and response

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San Francisco, CA, United States of America

Nikola Noxon