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公开(公告)号：US11865967B2
公开(公告)日：2024-01-09
申请号：US18149901
申请日：2023-01-04
Applicant: TuSimple, Inc.
Inventor： Yu-Ju Hsu , Xiaoling Han , Yijing Li , Zehua Huang , Lingting Ge , Panqu Wang , Shuhan Yang
CPC classification number: B60Q1/143 , B60Q2300/054 , B60Q2300/42 , G06V20/58
Abstract: A system comprises a headlight mounted on an autonomous vehicle. The headlight is configured to illuminate at least a portion of a road the autonomous vehicle is on. The system further comprises a control device associated with the autonomous vehicle. The processor obtains information about an environment around the autonomous vehicle. The processor determines that at least a portion of the road should be illuminated if the information indicates that an illumination level of the portion of the road is less than a threshold illumination level. The processor adjusts the headlight to illuminate at least the portion of the road in response to determining that at least the portion of the road should be illuminated.
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公开(公告)号：US11830205B2
公开(公告)日：2023-11-28
申请号：US17656415
申请日：2022-03-24
Applicant: TUSIMPLE, INC.
Inventor： Lingting Ge , Pengfei Chen , Panqu Wang
IPC: G06T7/00 , G06T7/277 , G06N3/08 , G06N3/04 , G06T7/246 , G06T7/73 , G06V20/58 , G06V10/764 , G06V10/82 , G06V10/62
CPC classification number: G06T7/277 , G06N3/04 , G06N3/08 , G06T7/248 , G06T7/74 , G06V10/764 , G06V10/82 , G06V20/58 , B60Y2400/3015 , G06T2207/30248 , G06V10/62
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.
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公开(公告)号：US11745736B2
公开(公告)日：2023-09-05
申请号：US17006283
申请日：2020-08-28
Applicant: TuSimple, Inc.
Inventor： Hongkai Yu , Zhipeng Yan , Panqu Wang , Pengfei Chen
IPC: B60W30/095 , G06V10/25 , G06V10/44 , G06V20/56 , G06V20/58 , G06F18/24 , G06F18/214 , G06F18/2413 , G06V10/774 , G06V10/70 , G05D1/02
CPC classification number: B60W30/0956 , G06F18/2155 , G06F18/24 , G06F18/2413 , G06V10/25 , G06V10/44 , G06V10/7753 , G06V10/87 , G06V20/56 , G06V20/58 , G05D1/0221
Abstract: A system and method for vehicle occlusion detection is disclosed. A particular embodiment includes: receiving training image data from a training image data collection system; obtaining ground truth data corresponding to the training image data; performing a training phase to train a plurality of classifiers, a first classifier being trained for processing static images of the training image data, a second classifier being trained for processing image sequences of the training image data; receiving image data from an image data collection system associated with an autonomous vehicle; and performing an operational phase including performing feature extraction on the image data, determining a presence of an extracted feature instance in multiple image frames of the image data by tracing the extracted feature instance back to a previous plurality of N frames relative to a current frame, applying the first trained classifier to the extracted feature instance if the extracted feature instance cannot be determined to be present in multiple image frames of the image data, and applying the second trained classifier to the extracted feature instance if the extracted feature instance can be determined to be present in multiple image frames of the image data.
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公开(公告)号：US11501513B2
公开(公告)日：2022-11-15
申请号：US16855951
申请日：2020-04-22
Applicant: TUSIMPLE, INC.
Inventor： Panqu Wang , Pengfei Chen
Abstract: 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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25.发明授权公开(公告)号：US10962979B2
公开(公告)日：2021-03-30
申请号：US15721797
申请日：2017-09-30
Applicant: TuSimple, Inc.
Inventor： Xiangchen Zhao , Tian Li , Panqu Wang , Pengfei Chen
Abstract: A system and method for multitask processing for autonomous vehicle computation and control includes: receiving training image data from a training image data collection system; performing a training phase to train a plurality of tasks associated with features of the training image data, the training phase including extracting common features from the training image data, causing the plurality of tasks to generate task-specific predictions based on the training image data, determining a bias between the task-specific prediction for each task and corresponding task-specific ground truth data, and adjusting parameters of each of the plurality of tasks to cause the bias to meet a pre-defined confidence level; receiving image data from an image data collection system associated with an autonomous vehicle; and performing an operational phase including extracting common features from the image data, causing the plurality of trained tasks to concurrently generate task-specific predictions based on the image data.
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Patent Agency Ranking
公开(公告)号：US20200175878A1
公开(公告)日：2020-06-04
申请号：US16781907
申请日：2020-02-04
Applicant: TuSimple, Inc.
Inventor： Panqu Wang
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.
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27.发明授权公开(公告)号：US10528851B2
公开(公告)日：2020-01-07
申请号：US15822467
申请日：2017-11-27
Applicant: TuSimple
Inventor： Ligeng Zhu , Panqu Wang , Pengfei Chen
Abstract: A system and method for drivable road surface representation generation using multimodal sensor data are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on a vehicle and receiving three dimensional (3D) point cloud data from a distance measuring device mounted on the vehicle; projecting the 3D point cloud data onto the 2D image data to produce mapped image and point cloud data; performing post-processing operations on the mapped image and point cloud data; and performing a smoothing operation on the processed mapped image and point cloud data to produce a drivable road surface map or representation.
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公开(公告)号：US10387736B2
公开(公告)日：2019-08-20
申请号：US15709832
申请日：2017-09-20
Applicant: TuSimple
Inventor： Yijie Wang , Ligeng Zhu , Panqu Wang , Pengfei Chen
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.
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公开(公告)号：US12242967B2
公开(公告)日：2025-03-04
申请号：US18536677
申请日：2023-12-12
Applicant: TuSimple, Inc.
Inventor： Tian Li , Panqu Wang , Pengfei Chen
IPC: G06N3/00 , G06F18/21 , G06F18/214 , G06F18/2413 , G06N3/045 , G06N3/08 , G06N20/00 , G06V10/44 , G06V10/764 , G06V20/56
Abstract: A system and method for instance-level roadway feature 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; extracting roadway features from the image data, causing a plurality of trained tasks to generate instance-level roadway feature 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 roadway feature detection results; and providing the instance-level roadway feature detection results to an autonomous vehicle subsystem to control operation of the autonomous vehicle.
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公开(公告)号：US12190465B2
公开(公告)日：2025-01-07
申请号：US18437734
申请日：2024-02-09
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng Yan , Pengfei Chen , Panqu Wang
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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