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

IPC: B60W30/095 ,  G06K9/00 ,  B60W30/09 ,  G05D1/02 ,  G06N7/00 ,  G06N5/04 ,  G06K9/62

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.

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

IPC: G01C21/36 ,  G06K9/00

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.

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

IPC: G06K9/00 ,  G01S17/88 ,  G01S17/08 ,  G01S17/66 ,  G01S17/58 ,  G01S7/48 ,  G01S17/931 ,  G01S17/86

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.