The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Feb. 16, 2021
Filed:
Dec. 23, 2019
Stradvision, Inc., Gyeongsangbuk-do, KR;
Kye-Hyeon Kim, Seoul, KR;
Yongjoong Kim, Gyeongsangbuk-do, KR;
Hak-Kyoung Kim, Gyeongsangbuk-do, KR;
Woonhyun Nam, Gyeongsangbuk-do, KR;
SukHoon Boo, Gyeonggi-do, KR;
Myungchul Sung, Gyeongsangbuk-do, KR;
Dongsoo Shin, Gyeonggi-do, KR;
Donghun Yeo, Gyeongsangbuk-do, KR;
Wooju Ryu, Gyeongsangbuk-do, KR;
Myeong-Chun Lee, Gyeongsangbuk-do, KR;
Hyungsoo Lee, Seoul, KR;
Taewoong Jang, Seoul, KR;
Kyungjoong Jeong, Gyeongsangbuk-do, KR;
Hongmo Je, Gyeongsangbuk-do, KR;
Hojin Cho, Gyeongsangbuk-do, KR;
StradVision, Inc., Gyeongsangbuk-do, KR;
Abstract
A learning method for calculating collision probability, to be used for determining whether it is appropriate or not to switch driving modes of a vehicle capable of an autonomous driving, by analyzing a recent driving route of a driver is provided. And the method includes steps of: (a) a learning device, on condition that a status vector and a trajectory vector are acquired, performing processes of (i) instructing a status network to generate a status feature map and (ii) instructing a trajectory network to generate a trajectory feature map; (b) the learning device instructing a safety network to calculate a predicted collision probability representing a predicted probability of an accident occurrence; and (c) the learning device instructing a loss layer to generate a loss by referring to the predicted collision probability and a GT collision probability, which have been acquired beforehand, to learn at least part of parameters.