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US Patent 10012993 Method and system for risk modeling in autonomous vehicles

Patent 10012993 was granted and assigned to Zendrive on July, 2018 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Zendrive
Zendrive
Current Assignee
Zendrive
Zendrive
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10012993
Date of Patent
July 3, 2018
Patent Application Number
15835284
Date Filed
December 7, 2017
Patent Citations Received
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US Patent 12013703 Systems and methods for evaluating autonomous vehicle software interactions for proposed trips
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US Patent 11345362 Adaptive warnings and emergency braking for distracted drivers
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US Patent 11878720 Method and system for risk modeling in autonomous vehicles
0
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US Patent 11887032 Fleet utilization efficiency for on-demand transportation services
0
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US Patent 10489721 Path segment risk regression system for on-demand transportation services
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US Patent 11048261 Systems and methods for evaluating autonomous vehicle software interactions for proposed trips
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US Patent 11294381 Vehicle motion adaptation systems and methods
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US Patent 11662732 Systems and methods for evaluating autonomous vehicle software interactions for proposed trips
0
...
Patent Primary Examiner
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Behrang Badii
Patent abstract

A method for adaptive risk modeling for an autonomous vehicle, the method comprising: retrieving parameters of an identified driving mission of the autonomous vehicle; in response to the parameters of the identified driving mission, generating values of: a comparative autonomous parameter, a mix model parameter, a surrounding risk parameter, a geographic operation parameter, and a security risk parameter upon evaluating situational inputs associated with the identified driving mission with a comparative autonomous model, a mix model, a sensor-surrounding model, a geography-dependent model, and a security risk model generated using sensor and supplementary data extraction systems associated with the autonomous vehicle; upon generating values, generating a risk analysis with a rule-based algorithm; and contemporaneously with execution of the identified driving mission, implementing a response action associated with control of the autonomous vehicle, based upon the risk analysis.

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