Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

주행 데이터 학습을 통한 주행 성향 판단 및 경로 예측

Full metadata record
DC Field Value Language
dc.contributor.author권나현-
dc.contributor.author김동찬-
dc.contributor.author양찬욱-
dc.contributor.author손혁주-
dc.contributor.author최승원-
dc.contributor.author최재웅-
dc.contributor.author허건수-
dc.date.accessioned2023-09-26T09:56:22Z-
dc.date.available2023-09-26T09:56:22Z-
dc.date.created2023-07-21-
dc.date.issued2021-11-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/191362-
dc.description.abstractWhile there are various drivers on the road and it is difficult to predict the future behavior of the vehicle because of different driving style even in the same situation. Therefore, it is necessary to judge the driving style and predict the trajectory using the driving style. In this paper, an algorithm for judging the driving style and predicting the trajectory of the vehicle by reflecting the style is proposed. The proposed algorithm is constructed by integrating the driving style judgement network and the trajectory prediction network. The driving style is classified into normal, aggressive, and careless driving, and CAN-bus data is used to determine the driving style. In addition, trajectory prediction is performed using a conditional generation model based on the determined style and driving data. The driving data is collected using CarMaker/HIL and the performance of the algorithm is verified in simulations with the proposed network structure.-
dc.language한국어-
dc.language.isoko-
dc.publisher한국자동차공학회-
dc.title주행 데이터 학습을 통한 주행 성향 판단 및 경로 예측-
dc.typeArticle-
dc.contributor.affiliatedAuthor허건수-
dc.identifier.bibliographicCitation2021년 한국자동차공학회 추계학술대회 및 전시회, pp.452 - 454-
dc.relation.isPartOf2021년 한국자동차공학회 추계학술대회 및 전시회-
dc.citation.title2021년 한국자동차공학회 추계학술대회 및 전시회-
dc.citation.startPage452-
dc.citation.endPage454-
dc.type.rimsART-
dc.type.docTypeProceeding-
dc.description.journalClass3-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassother-
dc.identifier.urlhttps://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11034985-
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 미래자동차공학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Huh, Kunsoo photo

Huh, Kunsoo
COLLEGE OF ENGINEERING (DEPARTMENT OF AUTOMOTIVE ENGINEERING)
Read more

Altmetrics

Total Views & Downloads

BROWSE