公开(公告)号：US20190087672A1

公开(公告)日：2019-03-21

申请号：US15709832

申请日：2017-09-20

Applicant: TuSimple

Inventor： Yijie WANG ,  Ligeng ZHU ,  Panqu WANG ,  Pengfei CHEN

IPC: G06K9/00 ,  G06K9/62 ,  G06K9/20 ,  G05D1/02

CPC classification number: G06K9/00825 ,  B60Y2200/11 ,  B60Y2200/12 ,  B60Y2200/143 ,  B60Y2200/22 ,  B60Y2200/252 ,  B60Y2200/30 ,  B60Y2200/51 ,  B60Y2200/52 ,  B60Y2200/86 ,  G05D1/0088 ,  G05D1/0246 ,  G05D2201/0201 ,  G05D2201/0204 ,  G05D2201/0208 ,  G05D2201/0213 ,  G06K9/00718 ,  G06K9/00805 ,  G06K9/209 ,  G06K9/6256 ,  G06K9/6288 ,  G06K2209/21

Abstract: A system method for detecting taillight signals of a vehicle using a convolutional neural network is disclosed. A particular embodiment includes: receiving a plurality of images from one or more image-generating devices; generating a frame for each of the plurality of images; generating a ground truth, wherein the ground truth includes a labeled image with one of the following taillight status conditions for a right or left taillight signal of the vehicle: (1) an invisible right or left taillight signal, (2) a visible but not illuminated right or left taillight signal, and (3) a visible and illuminated right or left taillight signal; creating a first dataset including the labeled images corresponding to the plurality of images, the labeled images including one or more of the taillight status conditions of the right or left taillight signal; and creating a second dataset including at least one pair of portions of the plurality of images, wherein the at least one pair of portions of the plurality of the images are in temporal succession.

公开(公告)号：US20190164018A1

公开(公告)日：2019-05-30

申请号：US15822467

申请日：2017-11-27

Applicant: TuSimple

Inventor： Ligeng ZHU ,  Panqu WANG ,  Pengfei CHEN

IPC: G06K9/62 ,  G06T5/30 ,  G06K9/44 ,  G06K9/00 ,  G06K9/40 ,  G05D1/02 ,  G08G1/16

Abstract: A system and method for drivable road surface representation generation using multimodal sensor data are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on a vehicle and receiving three dimensional (3D) point cloud data from a distance measuring device mounted on the vehicle; projecting the 3D point cloud data onto the 2D image data to produce mapped image and point cloud data; performing post-processing operations on the mapped image and point cloud data; and performing a smoothing operation on the processed mapped image and point cloud data to produce a drivable road surface map or representation.