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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
申请人： TuSimple, Inc.
发明人： Haiping WU , Long SHA , Hongyuan DU , Zilong GUO , Yihe TANG , Tingyu MAO , Pengfei CHEN , Panqu WANG , Rundong GE
CPC分类号： G06V20/584 , G06T7/12 , G06T7/13 , G06T7/50 , G06T7/70 , G06V10/25 , G06T2207/30196 , G06V2201/07
摘要： 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
申请人： TUSIMPLE, INC.
发明人： Zhipeng YAN , Pengfei CHEN , Panqu WANG
CPC分类号： G06T3/047 , G05D1/249 , G06T5/20 , G06T5/80 , G06T2207/30252
摘要： 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
申请人： TuSimple, Inc.
发明人： Panqu WANG , Tian LI
IPC分类号： G06N3/08 , G05D1/00 , G05D1/02 , G06N3/04 , G06V20/58 , G06V10/82 , G06V10/44 , G06F18/214 , G06V10/764 , G06V20/56
CPC分类号： G06N3/08 , G05D1/0088 , G05D1/0246 , G06N3/04 , G06V20/584 , G06V10/82 , G06V10/454 , G06F18/214 , G06V10/764 , G06V20/56 , G05D2201/0213
摘要： 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
申请人： TuSimple, Inc.
发明人： Charles A. PRICE , Xiaoling HAN , Lingting GE , Zehua HUANG , Panqu WANG , Chiyu ZHANG , Joshua Miguel RODRIGUEZ , Junjun XIN
IPC分类号： G01S13/931 , G05D1/02 , B60R11/02 , G01S13/86
摘要： 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
申请人： TUSIMPLE, INC.
发明人： Zehua HUANG , Pengfei CHEN , Panqu WANG
摘要： 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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公开(公告)号：US20200160067A1
公开(公告)日：2020-05-21
申请号：US16752632
申请日：2020-01-25
申请人： TuSimple, Inc.
发明人： Zehua HUANG , Pengfei CHEN , Panqu WANG , Ke XU
摘要： 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：US20190286916A1
公开(公告)日：2019-09-19
申请号：US15924249
申请日：2018-03-18
申请人： TuSimple
发明人： Zhipeng YAN , Lingting GE , Pengfei CHEN , Panqu WANG
摘要： 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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8.发明申请公开(公告)号：US20180365835A1
公开(公告)日：2018-12-20
申请号：US15623323
申请日：2017-06-14
申请人： TuSimple
发明人： Zhipeng YAN , Zehua HUANG , Pengfei CHEN , Panqu WANG
摘要： A system and method for actively selecting and labeling images for semantic segmentation are disclosed. A particular embodiment includes: receiving image data from an image generating device; 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; determining the quality of the semantic label image data based on prediction probabilities associated with regions or portions of the image; and identifying a region or portion of the image for manual labeling if an associated prediction probability is below a pre-determined threshold.
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公开(公告)号：US20180260651A1
公开(公告)日：2018-09-13
申请号：US15917331
申请日：2018-03-09
申请人： TuSimple
发明人： Panqu WANG , Pengfei CHEN
摘要： A system and method for vehicle wheel detection is disclosed. A particular embodiment can be configured to: receive training image data from a training image data collection system; obtain ground truth data corresponding to the training image data; perform a training phase to train one or more classifiers for processing images of the training image data to detect vehicle wheel objects in the images of the training image data; receive operational image data from an image data collection system associated with an autonomous vehicle; and perform an operational phase including applying the trained one or more classifiers to extract vehicle wheel objects from the operational image data and produce vehicle wheel object data.
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公开(公告)号：US20240320990A1
公开(公告)日：2024-09-26
申请号：US18598715
申请日：2024-03-07
申请人： TuSimple, Inc.
发明人： Rundong GE , Long SHA , Haiping WU , Xiangchen ZHAO , Fangjun ZHANG , Zilong GUO , Hongyuan DU , Pengfei CHEN , Panqu WANG
CPC分类号： G06V20/588 , B60W10/20 , G06T7/20 , G06V10/54 , G06V10/56 , G06V10/751 , G06V20/584
摘要： Techniques are described for performing an image processing 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 and a second image from a camera; determining a first set of characteristics about a first set of pixels in the first image and a second set of characteristics about a second set of pixels in the second image; obtaining a motion information for each pixel in the second set by comparing the second set of characteristics with the first set of characteristics; generating, using the motion information for each pixel in the second set, a combined set of characteristics; determining attributes of a road using at least some of the combined set of characteristics; and causing the vehicle to perform a driving related operation in response to the determining the attributes of the road.
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