System and method for vehicle position and velocity estimation based on camera and lidar data

    公开(公告)号:US10552691B2

    公开(公告)日:2020-02-04

    申请号:US15496113

    申请日:2017-04-25

    Applicant: TuSimple

    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.

    Perception simulation for improved autonomous vehicle control

    公开(公告)号:US10481044B2

    公开(公告)日:2019-11-19

    申请号:US15598693

    申请日:2017-05-18

    Applicant: TuSimple

    Abstract: A system and method for real world autonomous vehicle perception simulation are disclosed. A particular embodiment includes: receiving perception data from a plurality of sensors of an autonomous vehicle; configuring the perception simulation operation based on a comparison of the perception data against ground truth data; generating simulated perception data by simulating errors related to the physical constraints of one or more of the plurality of sensors, and by simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors; and providing the simulated perception data to a motion planning system for the autonomous vehicle.

    Large scale distributed simulation for realistic multiple-agent interactive environments

    公开(公告)号:US10474790B2

    公开(公告)日:2019-11-12

    申请号:US15612976

    申请日:2017-06-02

    Applicant: TuSimple

    Abstract: A system and method for large scale distributed simulation for realistic multiple-agent interactive environments are disclosed. A particular embodiment includes: generating a vicinal scenario for each simulated vehicle in an iteration of a simulation, the vicinal scenarios corresponding to different locations, traffic patterns, or environmental conditions being simulated; assigning a processing task to at least one of a plurality of distributed computing devices to generate vehicle trajectories for each of a plurality of simulated vehicles of the simulation based on the vicinal scenario; and updating a state and trajectory of each of the plurality of simulated vehicles based on processed data received from the plurality of distributed computing devices.

    Emergency braking system, emergency braking method and semitrailer

    公开(公告)号:US20190322273A1

    公开(公告)日:2019-10-24

    申请号:US16357726

    申请日:2019-03-19

    Applicant: TuSimple

    Inventor: Nan WU Junfeng LI

    Abstract: The present disclosure provides an emergency braking system, an emergency braking method and a semitrailer, capable of improving the braking effect of the vehicle, thereby achieving improved safety for the vehicle. The system includes: a sensor component configured to collect sensed information on an environment where a semitrailer is located; and a braking controller configured to determine whether there is a risk of collision for the semitrailer based on the sensed information, and if so, calculate a maximum adhesive force that can be provided by a road surface the semitrailer is currently on, determine a first braking pressure corresponding to each wheel based on the maximum adhesive force and axle load information, and transmit to a braking system a first braking instruction carrying the first braking pressure for each wheel.

    COOLING SYSTEM
    137.
    发明申请
    COOLING SYSTEM 审中-公开

    公开(公告)号:US20190289752A1

    公开(公告)日:2019-09-19

    申请号:US16242845

    申请日:2019-01-08

    Applicant: TuSimple

    Inventor: Zhihua Ma

    Abstract: The present disclosure provides a cooling system. The cooling system includes: a first set of fans mounted on an inward-facing side of an air inlet on an outer shell of a case; a second set of fans mounted on an inward-facing side of an air outlet on the outer shell of the case, for generating, in cooperation with the first set of fans, a high-pressure airflow from the air inlet to the air outlet; a first heat sink connected to heat generating component in the case, for absorbing heat from the heat generating component and transferring the absorbed heat to a second heat sink; and the second heat sink mounted on an inward-facing side of the second set of fans and cooled by the high-pressure airflow.

    SYSTEM AND METHOD FOR LATERAL VEHICLE DETECTION

    公开(公告)号:US20190286916A1

    公开(公告)日:2019-09-19

    申请号:US15924249

    申请日:2018-03-18

    Applicant: TuSimple

    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.

    Method and Apparatus for Object Re-identification

    公开(公告)号:US20190279028A1

    公开(公告)日:2019-09-12

    申请号:US16273835

    申请日:2019-02-12

    Applicant: TuSimple

    Abstract: The present disclosure provides a method and an apparatus for object re-identification, capable of solving the problem in the related art associated with inefficiency and low accuracy of object re-identification based on multiple frames of images. The method includes, for each pair of objects: selecting one of a set of images associated with each of the pair of objects, to constitute a pair of current images for the pair of objects; inputting the pair of current images to a preconfigured feature extraction network, to obtain feature information for the pair of current images; determining whether the pair of objects are one and the same object based on the feature information for the pair of current images and feature information for one or more pairs of historical images for the pair of objects by using a preconfigured re-identification network; and outputting a determination result of said determining when the determination result is that the pair of objects are one and the same object or that the pair of objects are not one and the same object, or repeating the above steps using the pair of current images as a pair of historical images for the pair of objects when the determination result is that it is uncertain whether the pair of objects are one and the same object. With the solutions according to the present disclosure, the speed and efficiency of the object re-identification can be improved.

    Deep module and fitting module system and method for motion-based lane detection with multiple sensors

    公开(公告)号:US10373003B2

    公开(公告)日:2019-08-06

    申请号:US15683463

    申请日:2017-08-22

    Applicant: TUSIMPLE

    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; off-line training a lane detection algorithm by using the ground truth, the lane detection algorithm using parameters that express a lane marking in an arc; on-line generating a predicted lane marking; comparing the predicted lane marking against the ground truth; and off-line refining the lane detection algorithm.

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