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公开(公告)号：US20210370932A1
公开(公告)日：2021-12-02
申请号：US17401781
申请日：2021-08-13
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng YAN , Mingdong WANG , Siyuan LIU , Xiaodi HOU
Abstract: A system and method for proximate vehicle intention prediction for autonomous vehicles are disclosed. A particular embodiment is configured to: receive perception data associated with a host vehicle; extract features from the perception data to detect a proximate vehicle in the vicinity of the host vehicle; generate a trajectory of the detected proximate vehicle based on the perception data; use a trained intention prediction model to generate a predicted intention of the detected proximate vehicle based on the perception data and the trajectory of the detected proximate vehicle; use the predicted intention of the detected proximate vehicle to generate a predicted trajectory of the detected proximate vehicle; and output the predicted intention and predicted trajectory for the detected proximate vehicle to another subsystem.
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22.发明申请公开(公告)号：US20210033420A1
公开(公告)日：2021-02-04
申请号：US17074468
申请日：2020-10-19
Applicant: TUSIMPLE, INC.
Inventor： Siyuan LIU , Mingdong WANG , Xiaodi HOU
Abstract: A method of lane detection for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs include instructions, which when executed by a computing device, cause the computing device to perform the following steps comprising: generating a ground truth associated with lane markings expressed in god's view; receiving features from at least one of a hit-map image and a fitted lane marking, wherein the hit-map image includes a classification of pixels that hit a lane marking, and the fitted lane marking includes pixels optimized based on the hit-map image; and training a confidence module based on the features and the ground truth, the confidence module configured to determine on-line whether a fitted lane marking is reasonable, using parameters that express a lane marking in an arc.
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公开(公告)号：US20200339145A1
公开(公告)日：2020-10-29
申请号：US16854848
申请日：2020-04-21
Applicant: TuSimple, Inc.
Inventor： Cheng ZHANG , Xiaodi HOU , Sven KRATZ
Abstract: Disclosed are devices, systems and methods for an audio assistant in an autonomous or semi-autonomous vehicle. In one aspect the informational audio assistant receives a first set of data from a vehicle sensor and identifies an object or condition using the data from the vehicle sensor. Audio is generated representative of a perceived danger of an object or condition. A second set of data from the vehicle sensor subsystem is received and the informational audio assistant determines whether an increased danger exists based on a comparison of the first set of data to the second set of data. The informational audio assistant will apply a sound profile to the generated audio based on the increased danger.
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24.发明申请公开(公告)号：US20200160071A1
公开(公告)日：2020-05-21
申请号：US16752637
申请日：2020-01-25
Applicant: TuSimple, Inc.
Inventor： Chenyang LI , Xiaodi HOU , Siyuan LIU
Abstract: A vehicle position and velocity estimation based on camera and LIDAR data are disclosed. A particular embodiment includes: receiving input object data from a subsystem of an autonomous vehicle, the input object data including image data from an image generating device and distance data from a distance measuring device; determining a two-dimensional (2D) position of a proximate object near the autonomous vehicle using the image data received from the image generating device; tracking a three-dimensional (3D) position of the proximate object using the distance data received from the distance measuring device over a plurality of cycles and generating tracking data; determining a 3D position of the proximate object using the 2D position, the distance data received from the distance measuring device, and the tracking data; determining a velocity of the proximate object using the 3D position and the tracking data; and outputting the 3D position and velocity of the proximate object relative to the autonomous vehicle.
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公开(公告)号：US20190318456A1
公开(公告)日：2019-10-17
申请号：US16381707
申请日：2019-04-11
Applicant: TuSimple
Inventor： Pengfei CHEN , Nan YU , Naiyan WANG , Xiaodi HOU
Abstract: Disclosed are devices, systems and methods for processing an image. In one aspect a method includes receiving an image from a sensor array including an x-y array of pixels, each pixel in the x-y array of pixels having a value selected from one of three primary colors, based on a corresponding x-y value in a mask pattern. The method may further include generating a preprocessed image by performing preprocessing on the image. The method may further include performing perception on the preprocessed image to determine one or more outlines of physical objects.
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Patent Agency Ranking
26.发明申请公开(公告)号：US20190163990A1
公开(公告)日：2019-05-30
申请号：US15822689
申请日：2017-11-27
Applicant: TuSimple
Inventor： Xue MEI , Xiaodi HOU , Dazhou GUO , Yujie WEI
IPC: G06K9/00 , B60R11/04 , G07C5/00 , G01S17/42 , G01S17/89 , G01C21/32 , G06T7/10 , G06T7/246 , G06N3/02
Abstract: A system and method for large-scale lane marking detection using multimodal sensor data are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on a vehicle; receiving point cloud data from a distance and intensity measuring device mounted on the vehicle; fusing the image data and the point cloud data to produce a set of lane marking points in three-dimensional (3D) space that correlate to the image data and the point cloud data; and generating a lane marking map from the set of lane marking points.
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公开(公告)号：US20190050428A1
公开(公告)日：2019-02-14
申请号：US15672217
申请日：2017-08-08
Applicant: TuSimple
Inventor： Xiaodi HOU , Siyuan LIU , Kai ZHOU
CPC classification number: G06F16/58 , G06F16/583 , G06F17/241 , G06Q30/0283
Abstract: A system and method for implementing an image annotation platform are disclosed. A particular embodiment includes: registering a plurality of labelers to which annotation tasks are assigned; assigning annotation tasks to the plurality of labelers; determining if the annotation tasks can be closed or re-assigned to the plurality of labelers; aggregating annotations provided by the plurality of labelers as a result of the closed annotation tasks; evaluating a level of performance of the plurality of labelers in providing the annotations; and calculating payments for the plurality of labelers based on the quantity and quality of the annotations provided by the plurality of labelers.
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公开(公告)号：US20240182081A1
公开(公告)日：2024-06-06
申请号：US18440738
申请日：2024-02-13
Applicant: TUSIMPLE, INC.
Inventor： Yiqian GAN , Yijie WANG , Xiaodi HOU , Lingting GE
CPC classification number: B60W60/0027 , G06T3/40 , G06T7/62 , G06T7/73 , G06V20/58 , G08G1/165 , G08G1/166 , B60W2420/403 , B60W2554/20 , B60W2554/4042 , B60W2554/4043 , B60W2554/4044 , G06T2207/30261
Abstract: Autonomous vehicles must accommodate various road configurations such as straight roads, curved roads, controlled intersections, uncontrolled intersections, and many others. Autonomous driving systems must make decisions about the speed and distance of traffic and about obstacles including obstacles that obstruct the view of the autonomous vehicle's sensors. For example, at intersections, the autonomous driving system must identify vehicles in the path of the autonomous vehicle or potentially in the path based on a planned path, estimate the distance to those vehicles, and estimate the speeds of those vehicles. Then, based on those and the road configuration and environmental conditions, the autonomous driving system must decide whether it is safe to proceed along the planned path or not, and when it is safe to proceed.
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公开(公告)号：US20240040269A1
公开(公告)日：2024-02-01
申请号：US18356905
申请日：2023-07-21
Applicant: TUSIMPLE, INC.
Inventor： Jianqiu CAO , Tristan NGUYEN , Xiaoling HAN , Xiaodi HOU
IPC: H04N23/90 , B60W60/00 , H04N13/239 , G06T7/593 , G06T7/292
CPC classification number: H04N23/90 , B60W60/001 , H04N13/239 , G06T7/593 , G06T7/292 , B60W2420/42 , B60W2420/40 , B60W2420/52 , B60W2554/4042 , G06T2207/30252
Abstract: Embodiments are disclosed for providing full and redundant sensor coverage for an environment surrounding a vehicle. An example vehicle includes a plurality of first cameras and a plurality of second cameras. The first cameras are associated with a first field-of-view (FOV) having a first horizontal aspect, and the second cameras are associated with a second FOV having a second horizontal aspect. The first cameras and the second cameras are located at different angular locations on the vehicle along a horizontal plane. Horizontal aspects of two FOVs of any two consecutive cameras located along the horizontal plane overlap in the horizontal plane by at least a predetermined degree. Another example vehicle includes a controller for controlling autonomous driving operation of the vehicle and a sensor network that includes at least six sensors. Directional beams corresponding to the sensors cover a surrounding region of the vehicle relevant to the autonomous driving operation.
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公开(公告)号：US20230399006A1
公开(公告)日：2023-12-14
申请号：US18363541
申请日：2023-08-01
Applicant: TUSIMPLE, INC. , Beijing Tusen Zhitu Technology Co., Ltd.
Inventor： Lingting GE , Yijie WANG , Yiqian GAN , Jianan HAO , Xiaodi HOU
IPC: B60W50/14 , G06T7/73 , G01S17/931 , B60W10/20 , G01S7/00 , G01S17/89 , G05D1/00 , G05D1/02 , G06V10/774 , G06V10/776 , G06V10/80 , G06V20/56 , G06V20/64
CPC classification number: B60W50/14 , G06T7/74 , G01S17/931 , B60W10/20 , G01S7/003 , G01S17/89 , G05D1/0094 , G05D1/0248 , G06V10/774 , G06V10/776 , G06V10/806 , G06V20/56 , G06V20/647 , B60W2420/42 , B60W2420/52 , G06T2207/30244 , G06T2210/12
Abstract: Disclosed are methods and devices related to autonomous driving. In one aspect, a method is disclosed. The method includes determining three-dimensional bounding indicators for one or more first objects in road target information captured by a light detection and ranging (LIDAR) sensor; determining camera bounding indicators for one or more second objects in road image information captured by a camera sensor; processing the road image information to generate a camera matrix; determining projected bounding indicators from the camera matrix and the three-dimensional bounding indicators; determining, from the projected bounding indicators and the camera bounding indicators, associations between the one or more first objects and the one or more second objects to generate combined target information; and applying, by the autonomous driving system, the combined target information to produce a vehicle control signal.
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