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US Patent 10459444 Autonomous vehicle fleet model training and testing

Patent 10459444 was granted and assigned to Zoox on October, 2019 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
1

Patent attributes

Current Assignee
Zoox
Zoox
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
104594441
Patent Inventor Names
Timothy David Kentley-Klay1
Date of Patent
October 29, 2019
1
Patent Application Number
158036031
Date Filed
November 3, 2017
1
Patent Citations Received
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US Patent 12134483 System and method for automated surface anomaly detection
2
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US Patent 11494669 Clustering, explainability, and automated decisions in computer-based reasoning systems
3
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US Patent 11509710 Method for operating a motor vehicle and motor vehicle
4
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US Patent 11511760 Cross-platform control profiling tool for autonomous vehicle control
5
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US Patent 12117546 Systems and methods of remote object tracking
6
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US Patent 12126917 Dual-stream video management
7
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US Patent 12128919 Dash cam with artificial intelligence safety event detection
8
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US Patent 11479142 Estimated state of charge determination
...
Patent Primary Examiner
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Michael J Zanelli
1
Patent abstract

A method and system of using excess computational resources on autonomous vehicles. Such excess computational resources may be available during periods of low demand, or other periods of idleness (e.g., parking). Where portions of computing resources are available amongst a fleet of vehicles, such excess computing resources may be pooled as a single resource. The excess computational resources may be used, for example, to train and/or test machine-learning models. Performance metrics of such models may be determined using hardware and software on the autonomous vehicle, for example sensors. Models having performance metrics outperforming current models may be considered as validated models. Validated models may be transmitted to a remote computing system for dissemination to a fleet of vehicles.

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