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公开(公告)号：US20190272433A1
公开(公告)日：2019-09-05
申请号：US16416248
申请日：2019-05-19
Applicant: TuSimple
Inventor： Hongkai YU , Zhipeng YAN , Panqu WANG , Pengfei CHEN
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：US20190266420A1
公开(公告)日：2019-08-29
申请号：US15906561
申请日：2018-02-27
Applicant: TuSimple
Inventor： Lingting GE , Pengfei CHEN , Panqu WANG
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：US20190102631A1
公开(公告)日：2019-04-04
申请号：US15959167
申请日：2018-04-20
Applicant: TuSimple
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 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 tasks associated with features of the training image data, the training phase including extracting roadway lane marking 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 roadway lane marking features from the image data, causing the plurality of trained tasks to generate 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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4.发明申请公开(公告)号：US20190065867A1
公开(公告)日：2019-02-28
申请号：US15684791
申请日：2017-08-23
Applicant: TuSimple
Inventor： Zehua HUANG , Panqu WANG , Pengfei CHEN , Tian LI
Abstract: A system and method for using triplet loss for proposal free instance-wise semantic segmentation for lane detection are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on an autonomous vehicle; performing a semantic segmentation operation or other object detection on the received image data to identify and label objects in the image data with object category labels on a per-pixel basis and producing corresponding semantic segmentation prediction data; performing a triplet loss calculation operation using the semantic segmentation prediction data to identify different instances of objects with similar object category labels found in the image data; and determining an appropriate vehicle control action for the autonomous vehicle based on the different instances of objects identified in the image data.
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公开(公告)号：US20180336421A1
公开(公告)日：2018-11-22
申请号：US15598727
申请日：2017-05-18
Applicant: TuSimple
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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Patent Agency Ranking
公开(公告)号：US20180290660A1
公开(公告)日：2018-10-11
申请号：US15482624
申请日：2017-04-07
Applicant: TuSimple
Inventor： Zehua HUANG , Panqu WANG , Pengfei CHEN
Abstract: A system and method for transitioning between an autonomous and manual driving mode based on detection of a driver's capacity to control a vehicle are disclosed. A particular embodiment includes: receiving sensor data related to a vehicle driver's capacity to take manual control of an autonomous vehicle; determining, based on the sensor data, if the driver has the capacity to take manual control of the autonomous vehicle, the determining including prompting the driver to perform an action or provide an input; and outputting a vehicle control transition signal to a vehicle subsystem to cause the vehicle subsystem to take action based on the driver's capacity to take manual control of the autonomous vehicle.
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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：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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公开(公告)号：US20190108384A1
公开(公告)日：2019-04-11
申请号：US15725747
申请日：2017-10-05
Applicant: TuSimple
Inventor： Yijie WANG , Panqu WANG , Pengfei CHEN
CPC classification number: G06K9/0063 , B64C39/024 , B64C2201/123 , B64D47/08 , G06K9/00765 , G06K9/209 , G06K9/3241 , G06K9/4652 , G06K9/6256 , G06K2209/21 , G06T7/11 , G08G1/012
Abstract: A system and method for aerial video traffic analysis are disclosed. A particular embodiment is configured to: receive a captured video image sequence from an unmanned aerial vehicle (UAV); clip the video image sequence by removing unnecessary images; stabilize the video image sequence by choosing a reference image and adjusting other images to the reference image; extract a background image of the video image sequence for vehicle segmentation; perform vehicle segmentation to identify vehicles in the video image sequence on a pixel by pixel basis; determine a centroid, heading, and rectangular shape of each identified vehicle; perform vehicle tracking to detect a same identified vehicle in multiple image frames of the video image sequence; and produce output and visualization of the video image sequence including a combination of the background image and the images of each identified vehicle.
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