公开(公告)号：US20240379004A1

公开(公告)日：2024-11-14

申请号：US18784692

申请日：2024-07-25

Applicant: TUSIMPLE, INC.

Inventor： Panqu WANG

IPC: G08G1/16 ,  G06T7/62 ,  G06T7/70 ,  G06V20/56

Abstract: A system and method for determining car to lane distance is provided. In one aspect, the system includes a camera configured to generate an image, a processor, and a computer-readable memory. The processor is configured to receive the image from the camera, generate a wheel segmentation map representative of one or more wheels detected in the image, and generate a lane segmentation map representative of one or more lanes detected in the image. For at least one of the wheels in the wheel segmentation map, the processor is also configured to determine a distance between the wheel and at least one nearby lane in the lane segmentation map. The processor is further configured to determine a distance between a vehicle in the image and the lane based on the distance between the wheel and the lane.

公开(公告)号：US20240320990A1

公开(公告)日：2024-09-26

申请号：US18598715

申请日：2024-03-07

Applicant: TuSimple, Inc.

Inventor： Rundong GE ,  Long SHA ,  Haiping WU ,  Xiangchen ZHAO ,  Fangjun ZHANG ,  Zilong GUO ,  Hongyuan DU ,  Pengfei CHEN ,  Panqu WANG

IPC: G06V20/56 ,  B60W10/20 ,  G06T7/20 ,  G06V10/54 ,  G06V10/56 ,  G06V10/75 ,  G06V20/58

CPC classification number: G06V20/588 ,  B60W10/20 ,  G06T7/20 ,  G06V10/54 ,  G06V10/56 ,  G06V10/751 ,  G06V20/584

Abstract: 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.

公开(公告)号：US20240203135A1

公开(公告)日：2024-06-20

申请号：US18474812

申请日：2023-09-26

Applicant: TuSimple, Inc.

Inventor： Yizhe ZHAO ,  Lingting GE ,  Panqu WANG

IPC: G06V20/56 ,  B60W60/00 ,  G06T7/12 ,  G06T7/73 ,  G06T15/00 ,  G06V20/70 ,  G08G1/16

CPC classification number: G06V20/588 ,  B60W60/001 ,  G06T7/12 ,  G06T7/74 ,  G06T15/00 ,  G06V20/70 ,  G08G1/167 ,  B60W2420/42 ,  B60W2520/10 ,  B60W2552/10 ,  B60W2552/15 ,  B60W2555/60 ,  B60W2556/40 ,  B60W2710/18 ,  B60W2710/20 ,  G06T2207/30256

Abstract: Techniques are described for autonomous driving operation that includes receiving, by a computer located in a vehicle, an image from a camera located on the vehicle while the vehicle is operating on a road, wherein the image includes a plurality of lanes of the road; for each of the plurality of lanes: obtaining, from a map database stored in the computer, a set of values that describe locations of boundaries of a lane; dividing the lane into a plurality of polygons; rendering the plurality of polygons onto the image; and determining identifiers of lane segments of the lane; determining one or more characteristics of a lane segment on which the vehicle is operating based on an identifier of the lane segment; and causing the vehicle to perform a driving related operation in response to the one or more characteristics of the lane segment on which the vehicle is operating.

公开(公告)号：US20230334871A1

公开(公告)日：2023-10-19

申请号：US18339961

申请日：2023-06-22

Applicant: TUSIMPLE, INC.

Inventor： Panqu WANG

IPC: G06V20/58 ,  G06T7/80 ,  G06T7/62 ,  G06N20/00 ,  G06F16/29

CPC classification number: G06V20/58 ,  G06T7/80 ,  G06T7/62 ,  G06N20/00 ,  G06F16/29

Abstract: A system and method for three-dimensional (3D) object detection is disclosed. A particular embodiment can be configured to: receive image data from a camera associated with a vehicle, the image data representing an image frame; use a machine learning module to determine at least one pixel coordinate of a two-dimensional (2D) bounding box around an object in the image frame; use the machine learning module to determine at least one vertex of a three-dimensional (3D) bounding box around the object; obtain camera calibration information associated with the camera; and determine 3D attributes of the object using the 3D bounding box and the camera calibration information.

公开(公告)号：US20230186616A1

公开(公告)日：2023-06-15

申请号：US18106929

申请日：2023-02-07

Applicant: TuSimple, Inc.

Inventor： Panqu WANG ,  Pengfei CHEN ,  Zehua HUANG

IPC: G06V10/82 ,  G05D1/02 ,  G06T7/12 ,  G06V10/44 ,  G06V10/26 ,  G06V20/58 ,  G06F18/2137

CPC classification number: G06V10/82 ,  G05D1/0246 ,  G06T7/12 ,  G06V10/44 ,  G06V10/26 ,  G06V20/58 ,  G06F18/2137 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/30261 ,  G05D2201/0213 ,  G06T2207/30252

Abstract: A system method for occluding contour detection using a fully convolutional neural network is disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image by semantic segmentation; learning an array of upscaling filters to upscale the feature map into a final dense feature map of a desired size; applying the array of upscaling filters to the feature map to produce contour information of objects and object instances detected in the input image; and applying the contour information onto the input image.

公开(公告)号：US20220262135A1

公开(公告)日：2022-08-18

申请号：US17739289

申请日：2022-05-09

Applicant: TuSimple, Inc.

Inventor： Panqu WANG ,  Tian LI

IPC: G06V20/58 ,  G06K9/62 ,  G06N3/08 ,  G05D1/00 ,  G05D1/02 ,  G06N3/04 ,  G06V10/40

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.

公开(公告)号：US20200265249A1

公开(公告)日：2020-08-20

申请号：US16868400

申请日：2020-05-06

Applicant: TUSIMPLE, INC.

Inventor： Lingting GE ,  Pengfei CHEN ,  Panqu WANG

IPC: G06K9/00 ,  G06T7/73 ,  G06T7/246 ,  G06N3/04 ,  G06N3/08

Abstract: A system and method for online real-time multi-object tracking is disclosed. A particular embodiment can be configured to: receive image frame data from at least one camera associated with an autonomous vehicle; generate similarity data corresponding to a similarity between object data in a previous image frame compared with object detection results from a current image frame; use the similarity data to generate data association results corresponding to a best matching between the object data in the previous image frame and the object detection results from the current image frame; cause state transitions in finite state machines for each object according to the data association results; and provide as an output object tracking output data corresponding to the states of the finite state machines for each object.

公开(公告)号：US20200126179A1

公开(公告)日：2020-04-23

申请号：US16165951

申请日：2018-10-19

Applicant: TuSimple

Inventor： Zhipeng YAN ,  Pengfei CHEN ,  Panqu WANG

IPC: G06T3/00 ,  G06T5/00 ,  G06T5/20 ,  G05D1/02

Abstract: A system and method for fisheye image processing is disclosed. A particular embodiment 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.

公开(公告)号：US20190087672A1

公开(公告)日：2019-03-21

申请号：US15709832

申请日：2017-09-20

Applicant: TuSimple

Inventor： Yijie WANG ,  Ligeng ZHU ,  Panqu WANG ,  Pengfei CHEN

IPC: G06K9/00 ,  G06K9/62 ,  G06K9/20 ,  G05D1/02

CPC classification number: G06K9/00825 ,  B60Y2200/11 ,  B60Y2200/12 ,  B60Y2200/143 ,  B60Y2200/22 ,  B60Y2200/252 ,  B60Y2200/30 ,  B60Y2200/51 ,  B60Y2200/52 ,  B60Y2200/86 ,  G05D1/0088 ,  G05D1/0246 ,  G05D2201/0201 ,  G05D2201/0204 ,  G05D2201/0208 ,  G05D2201/0213 ,  G06K9/00718 ,  G06K9/00805 ,  G06K9/209 ,  G06K9/6256 ,  G06K9/6288 ,  G06K2209/21

Abstract: A system method for detecting taillight signals of a vehicle using a convolutional neural network is disclosed. A particular embodiment includes: receiving a plurality of images from one or more image-generating devices; generating a frame for each of the plurality of images; generating a ground truth, wherein the ground truth includes a labeled image with one of the following taillight status conditions for a right or left taillight signal of the vehicle: (1) an invisible right or left taillight signal, (2) a visible but not illuminated right or left taillight signal, and (3) a visible and illuminated right or left taillight signal; creating a first dataset including the labeled images corresponding to the plurality of images, the labeled images including one or more of the taillight status conditions of the right or left taillight signal; and creating a second dataset including at least one pair of portions of the plurality of images, wherein the at least one pair of portions of the plurality of the images are in temporal succession.

公开(公告)号：US20180259970A1

公开(公告)日：2018-09-13

申请号：US15693446

申请日：2017-08-31

Applicant: TuSimple

Inventor： Panqu WANG ,  Pengfei CHEN ,  Zehua Huang

IPC: G05D1/02 ,  G06K9/46 ,  G06T7/70 ,  G06K9/66 ,  G06T7/11 ,  G05D1/00 ,  G06N3/04 ,  G06N3/08

Abstract: A system method for occluding contour detection using a fully convolutional neural network is disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image by semantic segmentation; applying a Dense Upsampling Convolution (DUC) operation on the feature map to produce contour information of objects and object instances detected in the input image; and applying the contour information onto the input image.