Patents by Inventor Romain Thibaux
Romain Thibaux 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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Publication number: 20240135727Abstract: The technology relates to approaches for determining appropriate stopping locations at intersections for vehicles operating in a self-driving mode. While many intersections have stop lines painted on the roadway, many others have no such lines. Even if a stop line is present, the physical location may not match what is in store map data, which may be out of date due to construction or line repainting. Aspects of the technology employ a neural network that utilizes input training data and detected sensor data to perform classification, localization and uncertain estimation processes. Based on these processes, the system is able to evaluate distribution information for possible stop locations. The vehicle uses such information to determine an optimal stop point, which may or may not correspond to a stop line in the map data. This information is also used to update the existing map data, which can be shared with other vehicles.Type: ApplicationFiled: January 3, 2024Publication date: April 25, 2024Inventors: Romain Thibaux, David Harrison Silver, Congrui Hetang
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Patent number: 11900697Abstract: The technology relates to approaches for determining appropriate stopping locations at intersections for vehicles operating in a self-driving mode. While many intersections have stop lines painted on the roadway, many others have no such lines. Even if a stop line is present, the physical location may not match what is in store map data, which may be out of date due to construction or line repainting. Aspects of the technology employ a neural network that utilizes input training data and detected sensor data to perform classification, localization and uncertain estimation processes. Based on these processes, the system is able to evaluate distribution information for possible stop locations. The vehicle uses such information to determine an optimal stop point, which may or may not correspond to a stop line in the map data. This information is also used to update the existing map data, which can be shared with other vehicles.Type: GrantFiled: October 3, 2022Date of Patent: February 13, 2024Assignee: Waymo LLCInventors: Romain Thibaux, David Harrison Silver, Congrui Hetang
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Publication number: 20230417565Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, one or more processors of one or more first systems of the autonomous vehicles may receive a signal indicating a predicted traffic stack for a lane in which the autonomous vehicle is currently traveling. In response to the received signal, costs of edges of a roadgraph between the autonomous vehicle and a location of the predicted traffic stack may be adjusted in order to encourage the autonomous vehicle to change lanes in response to the predicted traffic stack. A route may be generated to a destination based on at least one of the adjusted costs. The route may be provided to one or more second systems of the autonomous vehicle in order to control the autonomous vehicle according to the route.Type: ApplicationFiled: June 27, 2022Publication date: December 28, 2023Inventors: Alisha Saxena, Cheng Zhou, Romain Thibaux, Ryan De Iaco
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Patent number: 11749000Abstract: The technology relates to approaches for determining appropriate stopping locations at intersections for vehicles operating in a self-driving mode. While many intersections have stop lines painted on the roadway, many others have no such lines. Even if a stop line is present, the physical location may not match what is in store map data, which may be out of date due to construction or line repainting. Aspects of the technology employ a neural network that utilizes input training data and detected sensor data to perform classification, localization and uncertain estimation processes. Based on these processes, the system is able to evaluate distribution information for possible stop locations. The vehicle uses such information to determine an optimal stop point, which may or may not correspond to a stop line in the map data. This information is also used to update the existing map data, which can be shared with other vehicles.Type: GrantFiled: December 22, 2020Date of Patent: September 5, 2023Assignee: Waymo LLCInventors: Romain Thibaux, David Harrison Silver, Congrui Hetang
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Publication number: 20230023913Abstract: The technology relates to approaches for determining appropriate stopping locations at intersections for vehicles operating in a self-driving mode. While many intersections have stop lines painted on the roadway, many others have no such lines. Even if a stop line is present, the physical location may not match what is in store map data, which may be out of date due to construction or line repainting. Aspects of the technology employ a neural network that utilizes input training data and detected sensor data to perform classification, localization and uncertain estimation processes. Based on these processes, the system is able to evaluate distribution information for possible stop locations. The vehicle uses such information to determine an optimal stop point, which may or may not correspond to a stop line in the map data. This information is also used to update the existing map data, which can be shared with other vehicles.Type: ApplicationFiled: October 3, 2022Publication date: January 26, 2023Inventors: Romain Thibaux, David Harrison Silver, Congrui Hetang
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Patent number: 11373419Abstract: Aspects of the disclosure relate to detecting unmapped drivable road surfaces. In one instance, sensor data captured by a sensor of an autonomous vehicle may be projected onto a grid having a plurality of cells. The plurality of cells may be classified by generating a label for each of the plurality of cells. Each label may identifies whether or not a corresponding cell contains a drivable surface. Ones of the plurality of cells may be clustered based on the labels to form a cluster of cells. An area of the cluster of cells may be compared to a map. Whether the area of the cluster of cells is an unmapped drivable road surface may be determined based on the comparison.Type: GrantFiled: July 28, 2020Date of Patent: June 28, 2022Assignee: Waymo LLCInventors: David Harrison Silver, Ivan Bogun, Romain Thibaux
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Publication number: 20220198199Abstract: The technology relates to approaches for determining appropriate stopping locations at intersections for vehicles operating in a self-driving mode. While many intersections have stop lines painted on the roadway, many others have no such lines. Even if a stop line is present, the physical location may not match what is in store map data, which may be out of date due to construction or line repainting. Aspects of the technology employ a neural network that utilizes input training data and detected sensor data to perform classification, localization and uncertain estimation processes. Based on these processes, the system is able to evaluate distribution information for possible stop locations. The vehicle uses such information to determine an optimal stop point, which may or may not correspond to a stop line in the map data. This information is also used to update the existing map data, which can be shared with other vehicles.Type: ApplicationFiled: December 22, 2020Publication date: June 23, 2022Inventors: Romain Thibaux, David Harrison Silver, Congrui Hetang
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Publication number: 20210049374Abstract: Aspects of the disclosure relate to detecting unmapped drivable road surfaces. In one instance, sensor data captured by a sensor of an autonomous vehicle may be projected onto a grid having a plurality of cells. The plurality of cells may be classified by generating a label for each of the plurality of cells. Each label may identifies whether or not a corresponding cell contains a drivable surface. Ones of the plurality of cells may be clustered based on the labels to form a cluster of cells. An area of the cluster of cells may be compared to a map. Whether the area of the cluster of cells is an unmapped drivable road surface may be determined based on the comparison.Type: ApplicationFiled: July 28, 2020Publication date: February 18, 2021Inventors: David Harrison Silver, Ivan Bogun, Romain Thibaux
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Patent number: 10762360Abstract: Aspects of the disclosure relate to detecting unmapped drivable road surfaces. In one instance, sensor data captured by a sensor of an autonomous vehicle may be projected onto a grid having a plurality of cells. The plurality of cells may be classified by generating a label for each of the plurality of cells. Each label may identifies whether or not a corresponding cell contains a drivable surface. Ones of the plurality of cells may be clustered based on the labels to form a cluster of cells. An area of the cluster of cells may be compared to a map. Whether the area of the cluster of cells is an unmapped drivable road surface may be determined based on the comparison.Type: GrantFiled: November 19, 2018Date of Patent: September 1, 2020Assignee: Waymo LLCInventors: David Harrison Silver, Ivan Bogun, Romain Thibaux
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Publication number: 20200160068Abstract: Aspects of the disclosure relate to detecting unmapped drivable road surfaces. In one instance, sensor data captured by a sensor of an autonomous vehicle may be projected onto a grid having a plurality of cells. The plurality of cells may be classified by generating a label for each of the plurality of cells. Each label may identifies whether or not a corresponding cell contains a drivable surface. Ones of the plurality of cells may be clustered based on the labels to form a cluster of cells. An area of the cluster of cells may be compared to a map. Whether the area of the cluster of cells is an unmapped drivable road surface may be determined based on the comparison.Type: ApplicationFiled: November 19, 2018Publication date: May 21, 2020Inventors: David Harrison Silver, Ivan Bogun, Romain Thibaux
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Patent number: 9508102Abstract: Techniques to track interactions with content on a social network. In one embodiment, references are embedded within content to be presented to a user. At least one identifying reference from among the references is received in response to an interaction by the user with the content. The identifying reference is stored in a memory caching system as a record of the interaction. The references may comprise a key and a type. The key may be associated with the content and the type may be associated with components in the content. The interaction may involve selection by the user of a component within a story.Type: GrantFiled: July 25, 2012Date of Patent: November 29, 2016Assignee: FACEBOOK, INC.Inventors: Romain Thibaux, Eric Seo
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Publication number: 20140033074Abstract: Techniques to track interactions with content on a social network. In one embodiment, references are embedded within content to be presented to a user. At least one identifying reference from among the references is received in response to an interaction by the user with the content. The identifying reference is stored in a memory caching system as a record of the interaction. The references may comprise a key and a type. The key may be associated with the content and the type may be associated with components in the content. The interaction may involve selection by the user of a component within a story.Type: ApplicationFiled: July 25, 2012Publication date: January 30, 2014Applicant: Facebook, Inc.Inventors: Romain Thibaux, Eric Seo
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Patent number: 8510312Abstract: A system identifies metadata associated with a document by capturing text of a document and comparing the text of the document with a collection of metadata records. Sets of matches between the text of the document and at least one record in the collection of metadata records may be identified, where each set of matches corresponds to a metadata record in the collection of metadata records. Metadata records corresponding to each set of matches may be scored. At least one of the metadata records may be identified based on the scores of the metadata records. The at least one identified metadata record may be associated with the document.Type: GrantFiled: September 28, 2007Date of Patent: August 13, 2013Assignee: Google Inc.Inventors: Romain Thibaux, Luc Vincent, Christopher Richard Uhlik, Raghavan Manmatha, Xuefu Wang
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Patent number: 7529974Abstract: Systems and methods establish groups among numerous indications of failure in order to infer a cause of failure common to each group. In one implementation, a system computes the groups such that each group has the maximum likelihood of resulting from a common failure. Indications of failure are grouped by probability, even when a group's inferred cause of failure is not directly observable in the system. In one implementation, related matrices provide a system for receiving numerous health indications from each of numerous autonomous systems connected with the Internet. A correlational matrix links input (failure symptoms) and output (known or unknown root causes) through probability-based hypothetical groupings of the failure indications. The matrices are iteratively refined according to self-consistency and parsimony metrics to provide most likely groupings of indicators and most likely causes of failure.Type: GrantFiled: November 30, 2006Date of Patent: May 5, 2009Assignee: Microsoft CorporationInventors: Romain Thibaux, Emre Kiciman, David A. Maltz
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Publication number: 20080133288Abstract: Systems and methods establish groups among numerous indications of failure in order to infer a cause of failure common to each group. In one implementation, a system computes the groups such that each group has the maximum likelihood of resulting from a common failure. Indications of failure are grouped by probability, even when a group's inferred cause of failure is not directly observable in the system. In one implementation, related matrices provide a system for receiving numerous health indications from each of numerous autonomous systems connected with the Internet. A correlational matrix links input (failure symptoms) and output (known or unknown root causes) through probability-based hypothetical groupings of the failure indications. The matrices are iteratively refined according to self-consistency and parsimony metrics to provide most likely groupings of indicators and most likely causes of failure.Type: ApplicationFiled: November 30, 2006Publication date: June 5, 2008Applicant: Microsoft CorporationInventors: Romain Thibaux, Emre Kiciman, David A. Maltz