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公开(公告)号：US20210271898A1
公开(公告)日：2021-09-02
申请号：US16916087
申请日：2020-06-29
Applicant: Honda Motor Co., Ltd.
Inventor： Yi-Ting Chen , Nakul Agarwal , Behzad Dariush , Ahmed Taha
IPC: G06K9/00 , G06F16/735 , G06F16/738 , G06F16/783 , G06F16/787 , G06N3/02
Abstract: A system and method for performing intersection scenario retrieval that includes receiving a video stream of a surrounding environment of an ego vehicle. The system and method also include analyzing the video stream to trim the video stream into video clips of an intersection scene associated with the travel of the ego vehicle. The system and method additionally include annotating the ego vehicle, dynamic objects, and their motion paths that are included within the intersection scene with action units that describe an intersection scenario. The system and method further include retrieving at least one intersection scenario based on a query of an electronic dataset that stores a combination of action units to operably control a presentation of at least one intersection scenario video clip that includes the at least one intersection scenario.
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Patent Agency Ranking
公开(公告)号：US11042156B2
公开(公告)日：2021-06-22
申请号：US15978858
申请日：2018-05-14
Applicant: Honda Motor Co., Ltd.
Inventor： Yi-Ting Chen , Teruhisa Misu , Vasili Ramanishka
Abstract: A system and method for learning and executing naturalistic driving behavior that include classifying a driving maneuver as a goal-oriented action or a stimulus-driven action based on data associated with a trip of a vehicle. The system and method also include determining a cause associated with the driving maneuver classified as a stimulus-driven action and determining an attention capturing traffic related object associated with the driving maneuver. The system and method additionally include building a naturalistic driving behavior data set that includes at least one of: an annotation of the driving maneuver based on a classification of the driving maneuver, an annotation of the cause, and an annotation of the attention capturing traffic object. The system and method further include controlling the vehicle to be autonomously driven based on the naturalistic driving behavior data set.
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33.发明申请公开(公告)号：US20200039520A1
公开(公告)日：2020-02-06
申请号：US16055798
申请日：2018-08-06
Applicant: Honda Motor Co., Ltd.
Inventor： Teruhisa Misu , Yi-Ting Chen
Abstract: A system and method for learning naturalistic driving behavior based on vehicle dynamic data that include receiving vehicle dynamic data and image data and analyzing the vehicle dynamic data and the image data to detect a plurality of behavioral events. The system and method also include classifying at least one behavioral event as a stimulus-driven action and building a naturalistic driving behavior data set that includes annotations that are based on the at least one behavioral event that is classified as the stimulus-driven action. The system and method further include controlling a vehicle to be autonomously driven based on the naturalistic driving behavior data set.
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公开(公告)号：US20190287254A1
公开(公告)日：2019-09-19
申请号：US15923592
申请日：2018-03-16
Applicant: HONDA MOTOR CO., LTD.
Inventor： Athmanarayanan Lakshmi Narayanan , Yi-Ting Chen
Abstract: A system, computer-readable medium, and method for improving semantic mapping and traffic participant detection for an autonomous vehicle are provided. The methods and systems may include obtain a two-dimensional image, obtain a three-dimensional point cloud comprising a plurality of points, perform semantic segmentation on the image to map objects with a discrete pixel color, and overlaying the semantic segmentation on the image to generate a updated image, generate superpixel clusters from the semantic segmentation to group like pixels together, project the point cloud onto the updated image comprising the superpixel clusters, and remove points determined to be noise/errors from the point cloud based on determining noisy points within each superpixel cluster.
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公开(公告)号：US10282860B2
公开(公告)日：2019-05-07
申请号：US15601638
申请日：2017-05-22
Applicant: HONDA MOTOR CO., LTD.
Inventor： Yan Lu , Jiawei Huang , Yi-Ting Chen , Bernd Heisele
Abstract: The present disclosure relates to methods and systems for monocular localization in urban environments. The method may generate an image from a camera at a pose. The method may receive a pre-generated map, and determine features from the generated image based on edge detection. The method may predict a pose of the camera based on at least the pre-generated map, and determine features from the predicted camera pose. Further, the method may determine a Chamfer distance based upon the determined features from the image and the predicted camera pose, optimize the determined Chamfer distance based upon odometry information and epipolar geometry. Upon optimization, the method may determine an estimated camera pose.
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公开(公告)号：US10078790B2
公开(公告)日：2018-09-18
申请号：US15435096
申请日：2017-02-16
Applicant: HONDA MOTOR CO., LTD.
Inventor： Chien-Yi Wang , Yi-Ting Chen , Behzad Dariush
CPC classification number: G06K9/00812 , B60R11/04 , G01S17/89 , G06K9/00805 , G06K9/6218 , G06K9/6248 , G06K9/6256 , G06K9/6273 , G06K9/6277 , G06K9/628 , G06T7/73 , G06T2207/10028 , G06T2207/20081 , G06T2207/30264 , G06T2210/12 , G08G1/143 , G08G1/147
Abstract: A parking map generated based on determining a plurality of object clusters by associating pixels from an image with points from a point cloud. At least a portion of the plurality of object clusters can be classified into one of a plurality of object classifications including at least a vehicle object classification. A bounding box for one or more of the plurality of object clusters classified as the vehicle object classification can be generated. The bounding box can be included as a parking space on a parking map based on a location associated with the image and/or point cloud.
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