Learning method and learning device for updating HD map by V2X information integration technique

A map and high-definition technology, applied in nuclear methods, integrated learning, measurement devices, etc., can solve problems such as high cost and inability to make high-definition maps

Active Publication Date: 2020-08-07
STRADVISION
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Because of such a high cost, the actual status quo is that it is impossible to produce a large number of high-definition maps

Method used

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  • Learning method and learning device for updating HD map by V2X information integration technique
  • Learning method and learning device for updating HD map by V2X information integration technique
  • Learning method and learning device for updating HD map by V2X information integration technique

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Embodiment Construction

[0054] The detailed description of the present invention will be described later, and in order to clarify the object, technical solutions, and advantages of the present invention, refer to the accompanying drawings that show specific embodiments that the present invention can implement as examples. These embodiments are described in detail enough to enable those of ordinary skill to practice the invention.

[0055] In addition, in the detailed description and claims of the present invention, the terms "comprising" and its variants are not intended to exclude other technical features, additions, constituent elements or steps. For those skilled in the art, other objects, advantages and characteristics of the present invention will appear partly from the description and partly from the practice of the present invention. The following examples and drawings are provided as examples and are not intended to limit the present invention.

[0056] Further, the present invention covers ...

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Abstract

A learning method for selecting specific information, to be used for updating an HD Map is provided. And the method includes steps of: (a) a learning device instructing a coordinate neural network togenerate a local feature map and a global feature vector by applying a coordinate neural network operation to a coordinate matrix; (b) the learning device instructing a determination neural network togenerate a first estimated suitability score to an N-th estimated suitability score by applying a determination neural network operation to the integrated feature map; (c) the learning device instructing a loss layer to generate a loss by referring to (i) the first estimated suitability score to the N-th estimated suitability score and (ii) a first Ground Truth(GT) suitability score to an N-th GTsuitability score, and perform backpropagation by using the loss, to thereby learn parameters of the determination neural network and the coordinate neural network.

Description

[0001] priority claim [0002] This application claims priority over U.S. Provisional Application No. 62 / 798,656, filed January 30, 2019, the entire contents of which are incorporated herein by reference. technical field [0003] The present invention relates to a learning method and a learning device for an automatic driving vehicle, in particular to reconstructing a three-dimensional space, updating a HD map (high definition map, High Definition Map), the learning method and the learning device, and using the learning method and learning Device test method and test device. Background technique [0004] Recently, the autonomous driving technology of vehicles has attracted much attention. The so-called autonomous driving technology refers to the technology that uses modules that can obtain external information from sensors, cameras, etc. mounted on the vehicle to collect external information and use it to drive the vehicle safely. [0005] High-definition maps are indispe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/0967G06T17/00G06N3/08G01C21/32G01C21/36
CPCG08G1/096725G06T17/00G06N3/084G01C21/32G01C21/3638G06V20/64G06V20/56G06N3/045G06N3/04H04W4/40G06T2211/416G06N20/20G06N20/10G01C21/3691G06F18/2113G06F18/2413G06F18/2431
Inventor 金桂贤金镕重金鹤京南云铉夫硕焄成明哲申东洙吕东勋柳宇宙李明春李炯树张泰雄郑景中诸泓模赵浩辰
Owner STRADVISION
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