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公开(公告)号：US20240320987A1
公开(公告)日：2024-09-26
申请号：US18598384
申请日：2024-03-07
Applicant: TuSimple, Inc.
Inventor： Haiping WU , Long SHA , Hongyuan DU , Zilong GUO , Yihe TANG , Tingyu MAO , Pengfei CHEN , Panqu WANG , Rundong GE
CPC classification number: G06V20/584 , G06T7/12 , G06T7/13 , G06T7/50 , G06T7/70 , G06V10/25 , G06T2207/30196 , G06V2201/07
Abstract: Techniques are described for performing an image processing technique on frames of a camera located on or in a vehicle. An example technique includes receiving, by a computer located in a vehicle, a first image frame from a camera located on or in the vehicle; obtaining a first combined set of information by combining a first set of information about an object detected from the first image frame and a second set of information about a set of objects detected from a second image frame, where the set of objects includes the object; obtaining, by using the first combined set of information, a second combined set of information about the object from the first image frame and from the second image frame; and causing the vehicle to perform a driving related operation in response to determining a characteristic of the object using the second combined set of information.
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公开(公告)号：US20240311954A1
公开(公告)日：2024-09-19
申请号：US18437734
申请日：2024-02-09
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng YAN , Pengfei CHEN , Panqu WANG
CPC classification number: G06T3/047 , G05D1/249 , G06T5/20 , G06T5/80 , G06T2207/30252
Abstract: A system and method for fisheye image processing can be configured to: receive fisheye image data from at least one fisheye lens camera associated with an autonomous vehicle, the fisheye image data representing at least one fisheye image frame; partition the fisheye image frame into a plurality of image portions representing portions of the fisheye image frame; warp each of the plurality of image portions to map an arc of a camera projected view into a line corresponding to a mapped target view, the mapped target view being generally orthogonal to a line between a camera center and a center of the arc of the camera projected view; combine the plurality of warped image portions to form a combined resulting fisheye image data set representing recovered or distortion-reduced fisheye image data corresponding to the fisheye image frame; generate auto-calibration data representing a correspondence between pixels in the at least one fisheye image frame and corresponding pixels in the combined resulting fisheye image data set; and provide the combined resulting fisheye image data set as an output for other autonomous vehicle subsystems.
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公开(公告)号：US20230385637A1
公开(公告)日：2023-11-30
申请号：US18233802
申请日：2023-08-14
Applicant: TuSimple, Inc.
Inventor： Panqu WANG , Tian LI
IPC: G06N3/08 , G05D1/00 , G05D1/02 , G06N3/04 , G06V20/58 , G06V10/82 , G06V10/44 , G06F18/214 , G06V10/764 , G06V20/56
CPC classification number: G06N3/08 , G05D1/0088 , G05D1/0246 , G06N3/04 , G06V20/584 , G06V10/82 , G06V10/454 , G06F18/214 , G06V10/764 , G06V20/56 , G05D2201/0213
Abstract: A system and method for taillight signal recognition using a convolutional neural network is disclosed. An example embodiment includes: receiving a plurality of image frames from one or more image-generating devices of an autonomous vehicle; using a single-frame taillight illumination status annotation dataset and a single-frame taillight mask dataset to recognize a taillight illumination status of a proximate vehicle identified in an image frame of the plurality of image frames, the single-frame taillight illumination status annotation dataset including one or more taillight illumination status conditions of a right or left vehicle taillight signal, the single-frame taillight mask dataset including annotations to isolate a taillight region of a vehicle; and using a multi-frame taillight illumination status dataset to recognize a taillight illumination status of the proximate vehicle in multiple image frames of the plurality of image frames, the multiple image frames being in temporal succession.
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公开(公告)号：US20210405185A1
公开(公告)日：2021-12-30
申请号：US17344534
申请日：2021-06-10
Applicant: TuSimple, Inc.
Inventor： Charles A. PRICE , Xiaoling HAN , Lingting GE , Zehua HUANG , Panqu WANG , Chiyu ZHANG , Joshua Miguel RODRIGUEZ , Junjun XIN
IPC: G01S13/931 , G05D1/02 , B60R11/02 , G01S13/86
Abstract: A system and method providing truck-mounted sensors to detect trailer following vehicles and trailer conditions are disclosed. A system of an example embodiment comprises: a vehicle control subsystem installed in an autonomous truck, the vehicle control subsystem comprising a data processor; and a truck-mounted sensor subsystem installed on a portion of a tractor of the autonomous truck to which a trailer is attachable, the truck-mounted sensor subsystem being coupled to the vehicle control subsystem via a data connection, wherein the truck-mounted sensor subsystem is configured to emit electromagnetic waves propagating in a space under the trailer, to generate object data representing objects detected by receiving a reflection of the electromagnetic waves, and to transfer the object data to the vehicle control subsystem.
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公开(公告)号：US20200265244A1
公开(公告)日：2020-08-20
申请号：US16867472
申请日：2020-05-05
Applicant: TUSIMPLE, INC.
Inventor： Zehua HUANG , Pengfei CHEN , Panqu WANG
Abstract: A system and method for semantic segmentation using hybrid dilated convolution (HDC) are disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image; performing a convolution operation on the feature map and producing multiple convolution layers; grouping the multiple convolution layers into a plurality of groups; applying different dilation rates for different convolution layers in a single group of the plurality of groups; and applying a same dilation rate setting across all groups of the plurality of groups.
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Patent Agency Ranking
公开(公告)号：US20200160067A1
公开(公告)日：2020-05-21
申请号：US16752632
申请日：2020-01-25
Applicant: TuSimple, Inc.
Inventor： Zehua HUANG , Pengfei CHEN , Panqu WANG , Ke XU
Abstract: A system and method for image localization based on semantic segmentation are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on an autonomous vehicle; performing semantic segmentation or other object detection on the received image data to identify and label objects in the image data and produce semantic label image data; identifying extraneous objects in the semantic label image data; removing the extraneous objects from the semantic label image data; comparing the semantic label image data to a baseline semantic label map; and determining a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map.
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公开(公告)号：US20230266759A1
公开(公告)日：2023-08-24
申请号：US18167993
申请日：2023-02-13
Applicant: TuSimple, Inc.
Inventor： Xiaoling HAN , Chenzhe QIAN , Chiyu ZHANG , Charles A. PRICE , Joshua Miguel RODRIGUEZ , Lei NIE , Lingting GE , Panqu WANG , Pengfei CHEN , Shuhan YANG , Xiangchen ZHAO , Xiaodi HOU , Zehua HUANG
IPC: G05D1/00
CPC classification number: G05D1/0088 , G05D2201/0213
Abstract: A system installed in a vehicle includes a first group of sensing devices configured to allow a first level of autonomous operation of the vehicle; a second group of sensing devices configured to allow a second level of autonomous operation of the vehicle, the second group of sensing devices including primary sensing devices and backup sensing devices; a third group of sensing devices configured to allow the vehicle to perform a safe stop maneuver; and a control element communicatively coupled to the first group of sensing devices, the second group of sensing devices, and the third group of sensing devices. The control element is configured to: receive data from at least one of the first group, the second group, or the third group of sensing devices, and provide a control signal to a sensing device based on categorization information indicating a group to which the sensing device belongs.
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公开(公告)号：US20230182774A1
公开(公告)日：2023-06-15
申请号：US18070102
申请日：2022-11-28
Applicant: TuSimple, Inc.
Inventor： Panqu WANG , Yu WANG , Xiangchen ZHAO , Dongqiangzi YE
CPC classification number: B60W60/0011 , B60W40/04 , G01S17/89 , G01S17/931 , G06V20/58 , G06V20/70 , B60W2300/145 , B60W2420/42 , B60W2420/52 , B60W2556/20
Abstract: Autonomous vehicles can include systems and apparatus for performing signal processing on point cloud data from Light Detection and Ranging (LiDAR) devices located on the autonomous vehicles. A method includes obtaining, by a computer located in an autonomous vehicle, a combined point cloud data that describes a plurality of areas of an environment in which the autonomous vehicle is operating; determining that a first set of points from the combined point cloud data are located within fields of view of cameras located on the autonomous vehicle; assigning one or more labels to a second set of points from the first set of points in response to determining that the second set of points are located within bounding box(es) around object(s) in images obtained from the cameras; and causing the autonomous vehicle to operate based on characteristic(s) of the object(s) determined from the second set of points.
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公开(公告)号：US20210342602A1
公开(公告)日：2021-11-04
申请号：US17377206
申请日：2021-07-15
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng YAN , Lingting GE , Pengfei CHEN , Panqu WANG
Abstract: A system and method for lateral vehicle detection is disclosed. A particular embodiment can be configured to: receive lateral image data from at least one laterally-facing camera associated with an autonomous vehicle; warp the lateral image data based on a line parallel to a side of the autonomous vehicle; perform object extraction on the warped lateral image data to identify extracted objects in the warped lateral image data; and apply bounding boxes around the extracted objects.
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公开(公告)号：US20210216792A1
公开(公告)日：2021-07-15
申请号：US17214828
申请日：2021-03-27
Applicant: TuSimple, Inc.
Inventor： Tian LI , Panqu WANG , Pengfei CHEN
Abstract: A system and method for instance-level lane detection for autonomous vehicle control are disclosed. A particular embodiment includes: receiving image data from an image data collection system associated with an autonomous vehicle; performing an operational phase comprising extracting roadway lane marking features from the image data, causing a plurality of trained tasks to execute concurrently to generate instance-level lane detection results based on the image data, the plurality of trained tasks having been individually trained with different features of training image data received from a training image data collection system and corresponding ground truth data, the training image data and the ground truth data comprising data collected from real-world traffic scenarios; causing the plurality of trained tasks to generate task-specific predictions of feature characteristics based on the image data and to generate corresponding instance-level lane detection results; and providing the instance-level lane detection results to an autonomous vehicle subsystem of the autonomous vehicle.
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