VEHICLE ULTRASONIC SENSORS
    3.
    发明申请

    公开(公告)号:US20250050913A1

    公开(公告)日:2025-02-13

    申请号:US18486809

    申请日:2023-10-13

    Applicant: TuSimple, Inc.

    Abstract: Techniques are described for operating a vehicle using sensor data provided by one or more ultrasonic sensors located on or in the vehicle. An example method includes receiving, by a computer located in a vehicle, data from an ultrasonic sensor located on the vehicle, where the data includes a first set of coordinates of two points associated with a location where an object is detected by the ultrasonic sensor; determining a second set of coordinates associated with a point in between the two points; performing a first determination that the second set of coordinates is associated with a lane or a road on which the vehicle is operating; performing a second determination that the object is movable; and sending, in response to the first determination and the second determination, a message that causes the vehicle to perform a driving related operation while the vehicle is operating on the road.

    OBJECT POSE DETERMINATION SYSTEM AND METHOD

    公开(公告)号:US20250029274A1

    公开(公告)日:2025-01-23

    申请号:US18488657

    申请日:2023-10-17

    Applicant: TuSimple, Inc.

    Abstract: The present disclosure provides methods and systems of sampling-based object pose determination. An example method includes obtaining, for a time frame, sensor data of the object acquired by a plurality of sensors; generating a two-dimensional bounding box of the object in a projection plane based on the sensor data of the time frame; generating a three-dimensional pose model of the object based on the sensor data of the time frame and a model reconstruction algorithm; generating, based on the sensor data, the pose model, and multiple sampling techniques, a plurality of pose hypotheses of the object corresponding to the time frame, generating a hypothesis projection of the object for each of the pose hypotheses by projecting the pose hypothesis onto the projection plane; determining evaluation results by comparing the hypothesis projections with the bounding box; and determining, based on the evaluation results, an object pose for the time frame.

    TRANSFORMER FRAMEWORK FOR TRAJECTORY PREDICTION

    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.

    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.

    DETERMINING POSE FOR DRIVING OPERATIONS

    公开(公告)号:US20250042369A1

    公开(公告)日:2025-02-06

    申请号:US18486874

    申请日:2023-10-13

    Applicant: TuSimple, Inc.

    Abstract: Techniques are described for determining a set of pose information for an object when multiple sets of pose information are determined for a same object from multiple images. An example driving operation method includes obtaining, by a computer located in a vehicle, at least two sets of pose information related to an object located on a road on which the vehicle is operating, where each set of pose information includes characteristic(s) about the object, and where each set of pose information is determined from an image obtained by a camera; determining at least two weighted output vectors; determining, for the object, a set of pose information that are based on a combined weighted output vector that is obtained by combining the at least two weighted output vectors; and causing the vehicle to perform a driving-related operation using the set of pose information for the object.

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