公开(公告)号：US20240104382A1

公开(公告)日：2024-03-28

申请号：US18536677

申请日：2023-12-12

Applicant: TuSimple, Inc.

Inventor： Tian LI ,  Panqu WANG ,  Pengfei CHEN

IPC: G06N3/08 ,  G06F18/21 ,  G06F18/214 ,  G06F18/2413 ,  G06N3/045 ,  G06N20/00 ,  G06V10/44 ,  G06V10/764 ,  G06V20/56

CPC classification number: G06N3/08 ,  G06F18/214 ,  G06F18/2178 ,  G06F18/24143 ,  G06N3/045 ,  G06N20/00 ,  G06V10/454 ,  G06V10/764 ,  G06V20/588

Abstract: A system and method for instance-level roadway feature detection for autonomous vehicle control are disclosed. A particular embodiment includes: receiving image data from an image data collection system associated with an autonomous vehicle; extracting roadway features from the image data, causing a plurality of trained tasks to generate instance-level roadway feature detection results based on the image data, the plurality of trained tasks having been individually trained with different features of training image data received from a training image data collection system and corresponding ground truth data, the training image data and the ground truth data comprising data collected from real-world traffic scenarios; causing the plurality of trained tasks to generate task-specific predictions of feature characteristics based on the image data and to generate corresponding instance-level roadway feature detection results; and providing the instance-level roadway feature detection results to an autonomous vehicle subsystem of the autonomous vehicle to control operation of the autonomous vehicle based on the instance-level roadway feature detection results.

公开(公告)号：US20230385637A1

公开(公告)日：2023-11-30

申请号：US18233802

申请日：2023-08-14

Applicant: TuSimple, Inc.

Inventor： Panqu WANG ,  Tian LI

IPC: G06N3/08 ,  G05D1/00 ,  G05D1/02 ,  G06N3/04 ,  G06V20/58 ,  G06V10/82 ,  G06V10/44 ,  G06F18/214 ,  G06V10/764 ,  G06V20/56

CPC classification number: G06N3/08 ,  G05D1/0088 ,  G05D1/0246 ,  G06N3/04 ,  G06V20/584 ,  G06V10/82 ,  G06V10/454 ,  G06F18/214 ,  G06V10/764 ,  G06V20/56 ,  G05D2201/0213

Abstract: A system and method for taillight signal recognition using a convolutional neural network is disclosed. An example embodiment includes: receiving a plurality of image frames from one or more image-generating devices of an autonomous vehicle; using a single-frame taillight illumination status annotation dataset and a single-frame taillight mask dataset to recognize a taillight illumination status of a proximate vehicle identified in an image frame of the plurality of image frames, the single-frame taillight illumination status annotation dataset including one or more taillight illumination status conditions of a right or left vehicle taillight signal, the single-frame taillight mask dataset including annotations to isolate a taillight region of a vehicle; and using a multi-frame taillight illumination status dataset to recognize a taillight illumination status of the proximate vehicle in multiple image frames of the plurality of image frames, the multiple image frames being in temporal succession.

公开(公告)号：US20220262135A1

公开(公告)日：2022-08-18

申请号：US17739289

申请日：2022-05-09

Applicant: TuSimple, Inc.

Inventor： Panqu WANG ,  Tian LI

IPC: G06V20/58 ,  G06K9/62 ,  G06N3/08 ,  G05D1/00 ,  G05D1/02 ,  G06N3/04 ,  G06V10/40

Abstract: A system and method for taillight signal recognition using a convolutional neural network is disclosed. An example embodiment includes: receiving a plurality of image frames from one or more image-generating devices of an autonomous vehicle; using a single-frame taillight illumination status annotation dataset and a single-frame taillight mask dataset to recognize a taillight illumination status of a proximate vehicle identified in an image frame of the plurality of image frames, the single-frame taillight illumination status annotation dataset including one or more taillight illumination status conditions of a right or left vehicle taillight signal, the single-frame taillight mask dataset including annotations to isolate a taillight region of a vehicle; and using a multi-frame taillight illumination status dataset to recognize a taillight illumination status of the proximate vehicle in multiple image frames of the plurality of image frames, the multiple image frames being in temporal succession.

公开(公告)号：US20210216792A1

公开(公告)日：2021-07-15

申请号：US17214828

申请日：2021-03-27

Applicant: TuSimple, Inc.

Inventor： Tian LI ,  Panqu WANG ,  Pengfei CHEN

IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62 ,  G06N20/00 ,  G06N3/04 ,  G06N3/08

Abstract: A system and method for instance-level lane detection for autonomous vehicle control are disclosed. A particular embodiment includes: receiving image data from an image data collection system associated with an autonomous vehicle; performing an operational phase comprising extracting roadway lane marking features from the image data, causing a plurality of trained tasks to execute concurrently to generate instance-level lane detection results based on the image data, the plurality of trained tasks having been individually trained with different features of training image data received from a training image data collection system and corresponding ground truth data, the training image data and the ground truth data comprising data collected from real-world traffic scenarios; causing the plurality of trained tasks to generate task-specific predictions of feature characteristics based on the image data and to generate corresponding instance-level lane detection results; and providing the instance-level lane detection results to an autonomous vehicle subsystem of the autonomous vehicle.