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US Patent 10935974 Manual control re-engagement in an autonomous vehicle

Patent 10935974 was granted and assigned to State Farm on March, 2021 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
State Farm
State Farm
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Current Assignee
State Farm
State Farm
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
109359740
Patent Inventor Names
Aaron Williams0
Brian Mark Fields0
Kristopher Keith Gaudin0
Leo Nelson Chan0
Date of Patent
March 2, 2021
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Patent Application Number
159576370
Date Filed
April 19, 2018
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Patent Citations
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US Patent 10289113 Autonomous occupant attention-based control
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US Patent 10241509 Autonomous vehicle control assessment and selection
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Patent Citations Received
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US Patent 11518401 Vehicular driving assist with driver monitoring
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US Patent 11529956 Apparatus and method for controlling driving in vehicle
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US Patent 11541889 Apparatus and method for providing driving path in vehicle
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US Patent 11550317 Apparatus and method for controlling to enable autonomous system in vehicle
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US Patent 11548525 Apparatus and method for providing notification of control authority transition in vehicle
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US Patent 11548509 Apparatus and method for controlling lane change in vehicle
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US Patent 11554788 Apparatus for displaying driving state of vehicle, system including the same and method thereof
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US Patent 11565713 Vehicle control system, vehicle control method, and vehicle control program
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Patent Primary Examiner
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Shelley Chen
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Patent abstract

Vehicles may have the capability to navigate according to various levels of autonomous capabilities, the vehicle having a different set of autonomous competencies at each level. In certain situations, the vehicle may shift from one level of autonomous capability to another. The shift may require more or less driving responsibility from a human operator. Sensors inside the vehicle collect human operator parameters to determine an alertness level of the human operator. An alertness level is determined based on the human operator parameters and other data including historical data or human operator-specific data. Notifications are presented to the user based on the determined alertness level that are more or less intrusive based on the alertness level of the human operator and on the urgency of an impending change to autonomous capabilities. Notifications may be tailored to specific human operators based on human operator preference and historical performance.

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