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公开(公告)号：US20210049374A1
公开(公告)日：2021-02-18
申请号：US16941162
申请日：2020-07-28
Applicant: Waymo LLC
Inventor： David Harrison Silver , Ivan Bogun , Romain Thibaux
Abstract: 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.
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公开(公告)号：US20230417565A1
公开(公告)日：2023-12-28
申请号：US17849936
申请日：2022-06-27
Applicant: Waymo LLC
Inventor： Alisha Saxena , Cheng Zhou , Romain Thibaux , Ryan De Iaco
CPC classification number: G01C21/3492 , B60W60/0027 , B60W30/18163 , B60W2552/05 , B60W2552/10 , B60W2554/406
Abstract: 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.
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公开(公告)号：US20240135727A1
公开(公告)日：2024-04-25
申请号：US18403316
申请日：2024-01-03
Applicant: WAYMO LLC
Inventor： Romain Thibaux , David Harrison Silver , Congrui Hetang
IPC: G06V20/56 , B60W30/18 , G06F18/214 , G06F18/2413 , G06V10/25
CPC classification number: G06V20/588 , B60W30/181 , B60W30/18154 , G06F18/214 , G06F18/24147 , G06V10/25 , B60W2420/403
Abstract: 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.
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公开(公告)号：US11900697B2
公开(公告)日：2024-02-13
申请号：US17958711
申请日：2022-10-03
Applicant: WAYMO LLC
Inventor： Romain Thibaux , David Harrison Silver , Congrui Hetang
IPC: G06V20/56 , B60W30/18 , G06K9/62 , G06V10/25 , G06F18/214 , G06F18/2413
CPC classification number: G06V20/588 , B60W30/181 , B60W30/18154 , G06F18/214 , G06F18/24147 , G06V10/25 , B60W2420/42
Abstract: 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.
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公开(公告)号：US20230023913A1
公开(公告)日：2023-01-26
申请号：US17958711
申请日：2022-10-03
Applicant: WAYMO LLC
Inventor： Romain Thibaux , David Harrison Silver , Congrui Hetang
Abstract: 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.
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Patent Agency Ranking
公开(公告)号：US11373419B2
公开(公告)日：2022-06-28
申请号：US16941162
申请日：2020-07-28
Applicant: Waymo LLC
Inventor： David Harrison Silver , Ivan Bogun , Romain Thibaux
Abstract: 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.
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公开(公告)号：US11749000B2
公开(公告)日：2023-09-05
申请号：US17131232
申请日：2020-12-22
Applicant: WAYMO LLC
Inventor： Romain Thibaux , David Harrison Silver , Congrui Hetang
IPC: G06K9/00 , B60W30/18 , G06K9/32 , G06K9/62 , G06V20/56 , G06V10/25 , G06F18/214 , G06F18/2413
CPC classification number: G06V20/588 , B60W30/181 , B60W30/18154 , G06F18/214 , G06F18/24147 , G06V10/25 , B60W2420/42
Abstract: 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.
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公开(公告)号：US20220198199A1
公开(公告)日：2022-06-23
申请号：US17131232
申请日：2020-12-22
Applicant: WAYMO LLC
Inventor： Romain Thibaux , David Harrison Silver , Congrui Hetang
Abstract: 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.
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公开(公告)号：US10762360B2
公开(公告)日：2020-09-01
申请号：US16194632
申请日：2018-11-19
Applicant: Waymo LLC
Inventor： David Harrison Silver , Ivan Bogun , Romain Thibaux
Abstract: 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.
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公开(公告)号：US20200160068A1
公开(公告)日：2020-05-21
申请号：US16194632
申请日：2018-11-19
Applicant: Waymo LLC
Inventor： David Harrison Silver , Ivan Bogun , Romain Thibaux
Abstract: 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.
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