Patents by Inventor Justin Erickson
Justin Erickson has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11914366Abstract: Blended operator and autonomous control in an autonomous vehicle, including: receiving sensor data from a plurality of sensors of an autonomous vehicle; determining, based on the sensor data, a degree of autonomous control for each control input of a plurality of control inputs; and applying the degree of autonomous control for each control input of the plurality of control inputs.Type: GrantFiled: March 29, 2022Date of Patent: February 27, 2024Assignee: GHOST AUTONOMY INC.Inventors: Aaron Carroll, Mario Delgado, Basheer Tome, Noah Shaw, John Hayes, Volkmar Uhlig, Justin Erickson
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Patent number: 11630830Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: GrantFiled: July 6, 2020Date of Patent: April 18, 2023Assignee: Cloudera Inc.Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Patent number: 11567956Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: GrantFiled: July 6, 2020Date of Patent: January 31, 2023Assignee: Cloudera, Inc.Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Patent number: 11548535Abstract: Automatic disengagement of an autonomous driving mode may include receiving, from a steering torque sensor, torque sensor data indicating an amount of torque applied to a steering system of the autonomous vehicle; determining a predicted torque based on one or more motion attributes of the steering system of the autonomous vehicle; determining a differential between the predicted torque and the amount of torque; and determining, based on the differential, whether to disengage an autonomous driving mode of the autonomous vehicle.Type: GrantFiled: October 24, 2020Date of Patent: January 10, 2023Assignee: GHOST AUTONOMY INC.Inventors: Aaron Carroll, Justin Erickson, Mario Delgado, John Hayes, Volkmar Uhlig
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Publication number: 20220402499Abstract: Detecting operator contact with a steering wheel, including: applying a torque to at least a portion of a steering system of an autonomous vehicle; identifying a measured torque for a steering wheel of the autonomous vehicle; calculating, based on the applied torque, an expected torque for the steering wheel; and determining, based on a difference between the measured torque and the expected torque, whether an operator of the autonomous vehicle is in contact with the steering wheel.Type: ApplicationFiled: March 29, 2022Publication date: December 22, 2022Inventors: AARON CARROLL, MARIO DELGADO, NOAH SHAW, JOHN HAYES, VOLKMAR UHLIG, JUSTIN ERICKSON
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Publication number: 20220404828Abstract: Blended operator and autonomous control in an autonomous vehicle, including: receiving sensor data from a plurality of sensors of an autonomous vehicle; determining, based on the sensor data, a degree of autonomous control for each control input of a plurality of control inputs; and applying the degree of autonomous control for each control input of the plurality of control inputs.Type: ApplicationFiled: March 29, 2022Publication date: December 22, 2022Inventors: AARON CARROLL, MARIO DELGADO, BASHEER TOME, NOAH SHAW, JOHN HAYES, VOLKMAR UHLIG, JUSTIN ERICKSON
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Patent number: 11449947Abstract: Methods, apparatus and systems for managing subrogation cases are described.Type: GrantFiled: April 3, 2020Date of Patent: September 20, 2022Assignee: HEALTH MANAGEMENT SYSTEMS, INC.Inventors: Justin Erickson, Trisha Henry, Ben Schy, Maura McCormick
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Publication number: 20220126877Abstract: Automatic disengagement of an autonomous driving mode may include receiving, from a steering torque sensor, torque sensor data indicating an amount of torque applied to a steering system of the autonomous vehicle; determining a predicted torque based on one or more motion attributes of the steering system of the autonomous vehicle; determining a differential between the predicted torque and the amount of torque; and determining, based on the differential, whether to disengage an autonomous driving mode of the autonomous vehicle.Type: ApplicationFiled: October 24, 2020Publication date: April 28, 2022Inventors: AARON CARROLL, JUSTIN ERICKSON, MARIO DELGADO, JOHN HAYES, VOLKMAR UHLIG
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Publication number: 20200334248Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: ApplicationFiled: July 6, 2020Publication date: October 22, 2020Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Publication number: 20200334247Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: ApplicationFiled: July 6, 2020Publication date: October 22, 2020Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Publication number: 20200320638Abstract: Methods, apparatus and systems for managing subrogation cases are described.Type: ApplicationFiled: April 3, 2020Publication date: October 8, 2020Inventors: Justin ERICKSON, Trisha HENRY, Ben SCHY, Maura MCCORMICK
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Patent number: 10706059Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: GrantFiled: October 12, 2016Date of Patent: July 7, 2020Assignee: Cloudera, Inc.Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Patent number: 9990399Abstract: A low latency query engine for APACHE HADOOP™ that provides real-time or near real-time, ad hoc query capability, while completing batch-processing of MapReduce. In one embodiment, the low latency query engine comprises a daemon that is installed on data nodes in a HADOOP™ cluster for handling query requests and all internal requests related to query execution. In a further embodiment, the low latency query engine comprises a daemon for providing name service and metadata distribution. The low latency query engine receives a query request via client, turns the request into collections of plan fragments and coordinates parallel and optimized execution of the plan fragments on remote daemons to generate results at a much faster speed than existing batch-oriented processing frameworks.Type: GrantFiled: May 13, 2016Date of Patent: June 5, 2018Assignee: Cloudera, Inc.Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Publication number: 20170132283Abstract: A low latency query engine for APACHE HADOOP™ that provides real-time or near real-time, ad hoc query capability, while completing batch-processing of MapReduce. In one embodiment, the low latency query engine comprises a daemon that is installed on data nodes in a HADOOP™ cluster for handling query requests and all internal requests related to query execution. In a further embodiment, the low latency query engine comprises a daemon for providing name service and metadata distribution. The low latency query engine receives a query request via client, turns the request into collections of plan fragments and coordinates parallel and optimized execution of the plan fragments on remote daemons to generate results at a much faster speed than existing batch-oriented processing frameworks.Type: ApplicationFiled: May 13, 2016Publication date: May 11, 2017Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Publication number: 20170032003Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: ApplicationFiled: October 12, 2016Publication date: February 2, 2017Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Patent number: 9477731Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: GrantFiled: October 1, 2013Date of Patent: October 25, 2016Assignee: Cloudera, Inc.Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Patent number: 9342557Abstract: A low latency query engine for APACHE HADOOP™ that provides real-time or near real-time, ad hoc query capability, while completing batch-processing of MapReduce. In one embodiment, the low latency query engine comprises a daemon that is installed on data nodes in a HADOOP™ cluster for handling query requests and all internal requests related to query execution. In a further embodiment, the low latency query engine comprises a daemon for providing name service and metadata distribution. The low latency query engine receives a query request via client, turns the request into collections of plan fragments and coordinates parallel and optimized execution of the plan fragments on remote daemons to generate results at a much faster speed than existing batch-oriented processing frameworks.Type: GrantFiled: March 13, 2013Date of Patent: May 17, 2016Assignee: Cloudera, Inc.Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Publication number: 20150095308Abstract: A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.Type: ApplicationFiled: October 1, 2013Publication date: April 2, 2015Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm
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Publication number: 20140280032Abstract: A low latency query engine for Apache Hadoop that provides real-time or near real-time, ad hoc query capability, while completing batch-processing of MapReduce. In one embodiment, the low latency query engine comprises a daemon that is installed on data nodes in a Hadoop cluster for handling query requests and all internal requests related to query execution. In a further embodiment, the low latency query engine comprises a daemon for providing name service and metadata distribution. The low latency query engine receives a query request via client, turns the request into collections of plan fragments and coordinates parallel and optimized execution of the plan fragments on remote daemons to generate results at a much faster speed than existing batch-oriented processing frameworks.Type: ApplicationFiled: March 13, 2013Publication date: September 18, 2014Inventors: Marcel Kornacker, Justin Erickson, Nong Li, Lenni Kuff, Henry Noel Robinson, Alan Choi, Alex Behm