中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

11 records (took 0.016 seconds)

    GENERATIVE ARTIFICIAL INTELLIGENCE BASED TRAJECTORY SIMULATION
    1.
    发明申请
    GENERATIVE ARTIFICIAL INTELLIGENCE BASED TRAJECTORY SIMULATION 有权

    公开(公告)号：US20250166364A1

    公开(公告)日：2025-05-22

    申请号：US18518222

    申请日：2023-11-22

    Applicant: TuSimple, Inc.

    Inventor： Hao XIAO ,  Yiqian GAN ,  Xin YE ,  Dongqiangzi YE ,  JingHao MIAO ,  Lingting GE

    IPC: G06V10/82 ,  G06V20/58

    Abstract: Devices, systems, and methods a method for simulating a trajectory of an object are described. An example method includes obtaining a context feature representation corresponding to context information, wherein the context information comprises information describing an environment of the object; obtaining a control feature representation corresponding to control information, wherein the control information comprises information that the simulated trajectory needs to satisfy; determining a latent variable using an input encoder based on the context feature representation and the control feature representation; and determining the simulated trajectory by inputting the latent variable, the context feature representation, and the control feature representation into a decoder.

    CAMERA ORIENTATION ESTIMATION
    2.
    发明申请
    CAMERA ORIENTATION ESTIMATION 有权

    公开(公告)号：US20210125370A1

    公开(公告)日：2021-04-29

    申请号：US16663242

    申请日：2019-10-24

    Applicant: TUSIMPLE, INC.

    Inventor： Yijie WANG ,  Lingting GE ,  Yiqian GAN ,  Xiaodi HOU

    IPC: G06T7/73 ,  G06T7/33

    Abstract: Techniques are described to estimate orientation of one or more cameras located on a vehicle. The orientation estimation technique can include obtaining an image from a camera located on a vehicle while the vehicle is being driven on a road, determining, from a terrain map, a location of a landmark located at a distance from a location of the vehicle on the road, determining, in the image, pixel locations of the landmark, selecting one pixel location from the determined pixel locations; and calculating values that describe an orientation of the camera using at least an intrinsic matrix and a previously known extrinsic matrix of the camera, where the intrinsic matrix is characterized based on at least the one pixel location and the location of the landmark.

    AUTONOMOUS DRIVING CRASH PREVENTION
    3.
    发明申请
    AUTONOMOUS DRIVING CRASH PREVENTION 有权

    公开(公告)号：US20210403050A1

    公开(公告)日：2021-12-30

    申请号：US17359007

    申请日：2021-06-25

    Applicant: TUSIMPLE, INC.

    Inventor： Yiqian GAN ,  Yijie WANG ,  Xiaodi HOU ,  Lingting GE

    IPC: B60W60/00 ,  G08G1/16 ,  G06K9/00 ,  G06T7/73 ,  G06T7/62 ,  G06T3/40

    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.

    HUMAN DRIVING BEHAVIOR MODELING SYSTEM USING MACHINE LEARNING
    4.
    发明申请
    HUMAN DRIVING BEHAVIOR MODELING SYSTEM USING MACHINE LEARNING 审中-公开

    公开(公告)号：US20190164007A1

    公开(公告)日：2019-05-30

    申请号：US16120247

    申请日：2018-09-01

    Applicant: TuSimple

    Inventor： Liu LIU ,  Yiqian GAN

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

    Abstract: A human driving behavior modeling system using machine learning is disclosed. A particular embodiment can be configured to: obtain training image data from a plurality of real world image sources and perform object extraction on the training image data to detect a plurality of vehicle objects in the training image data; categorize the detected plurality of vehicle objects into behavior categories based on vehicle objects performing similar maneuvers at similar locations of interest; train a machine learning module to model particular human driving behaviors based on use of the training image data from one or more corresponding behavior categories; and generate a plurality of simulated dynamic vehicles that each model one or more of the particular human driving behaviors trained into the machine learning module based on the training image data.

    TRANSFORMER FRAMEWORK FOR TRAJECTORY PREDICTION
    5.
    发明申请
    TRANSFORMER FRAMEWORK FOR TRAJECTORY PREDICTION 有权

    公开(公告)号：US20250085115A1

    公开(公告)日：2025-03-13

    申请号：US18501362

    申请日：2023-11-03

    Applicant: TuSimple, Inc.

    Inventor： Hao XIAO ,  Yiqian GAN ,  Ethan ZHANG ,  Xin YE ,  Yizhe ZHAO ,  Zhe HUANG ,  Lingting GE ,  Robert August ROSSI, JR.

    IPC: G01C21/30

    Abstract: A computer-implemented method of trajectory prediction includes obtaining a first cross-attention between a vectorized representation of a road map near a vehicle and information obtained from a rasterized representation of an environment near the vehicle by processing through a first cross-attention stage; obtaining a second cross-attention between a vectorized representation of a vehicle history and information obtained from the rasterized representation by processing through a second cross-attention stage; operating a scene encoder on the first cross-attention and the second cross-attention; operating a trajectory decoder on an output of the scene encoder; obtaining one or more trajectory predictions by performing one or more queries on the trajectory decoder.

    CAMERA ORIENTATION ESTIMATION
    9.
    发明公开
    CAMERA ORIENTATION ESTIMATION 审中-公开

    公开(公告)号：US20230334696A1

    公开(公告)日：2023-10-19

    申请号：US18339940

    申请日：2023-06-22

    Applicant: TUSIMPLE, INC.

    Inventor： Yijie WANG ,  Lingting GE ,  Yiqian GAN ,  Xiaodi HOU

    IPC: G06T7/73 ,  G06T7/33

    CPC classification number: G06T7/74 ,  G06T7/337 ,  G06T2207/30184 ,  G06T2207/30252

    Abstract: Techniques are described to estimate orientation of one or more cameras located on a vehicle. The orientation estimation technique can include obtaining an image from a camera located on a vehicle while the vehicle is being driven on a road, determining, from a terrain map, a location of a landmark located at a distance from a location of the vehicle on the road, determining, in the image, pixel locations of the landmark, selecting one pixel location from the determined pixel locations; and calculating values that describe an orientation of the camera using at least an intrinsic matrix and a previously known extrinsic matrix of the camera, where the intrinsic matrix is characterized based on at least the one pixel location and the location of the landmark.

    CAMERA ORIENTATION ESTIMATION
    10.
    发明申请
    CAMERA ORIENTATION ESTIMATION 有权

    公开(公告)号：US20220076446A1

    公开(公告)日：2022-03-10

    申请号：US17531447

    申请日：2021-11-19

    Applicant: TUSIMPLE, INC.

    Inventor： Yijie WANG ,  Lingting GE ,  Yiqian GAN ,  Xiaodi HOU

    IPC: G06T7/73 ,  G06T7/33

    Abstract: Techniques are described to estimate orientation of one or more cameras located on a vehicle. The orientation estimation technique can include obtaining an image from a camera located on a vehicle while the vehicle is being driven on a road, determining, from a terrain map, a location of a landmark located at a distance from a location of the vehicle on the road, determining, in the image, pixel locations of the landmark, selecting one pixel location from the determined pixel locations; and calculating values that describe an orientation of the camera using at least an intrinsic matrix and a previously known extrinsic matrix of the camera, where the intrinsic matrix is characterized based on at least the one pixel location and the location of the landmark.

Patent Agency Ranking