Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 정정주 | - |
dc.date.accessioned | 2022-03-29T00:44:33Z | - |
dc.date.available | 2022-03-29T00:44:33Z | - |
dc.date.issued | 2020-07 | - |
dc.identifier.citation | 2020 제35회 제어로봇시스템학회 학술대회, page. 17-18 | en_US |
dc.identifier.uri | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE09410313 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/169477 | - |
dc.description.abstract | In this paper, we propose estimation of the exact vehicle position based on the Interaction Multiple Model Extended Kalman Filter(IMM EKF) when the road surface changes. Since the vehicle has different cornering stiffness as the road surface varies, it is difficult to accurately estimate the position of the vehicle. To resolve this problem, we improve the estimation performance by using IMM EKF considering each model of different roads. From the numerical simulation using MATLAB/CarSim, we observed that the performance of proposed algorithm improves vehicle positioning performance. | en_US |
dc.description.sponsorship | 본 연구는 2019 년도 정부(과학기술정보통신부)의 재원으로 정보통신기술진흥터의 지원을 받아 수행된 연구임. (No R7117-19-0164, 차량 통신 기반의 광역 주행환경인지 및협조 주행기술 개발) | en_US |
dc.language.iso | ko_KR | en_US |
dc.publisher | 제어로봇시스템학회 | en_US |
dc.subject | Autonomous driving | en_US |
dc.subject | interacting multiple model | en_US |
dc.subject | Kalman filter algorithm | en_US |
dc.title | Interacting Multiple Model Filter 를 이용한 차량의 위치 추정 | en_US |
dc.title.alternative | Vehicle position estimation using Interacting Multiple Model Filter | en_US |
dc.type | Article | en_US |
dc.relation.page | 17-18 | - |
dc.contributor.googleauthor | 허현욱 | - |
dc.contributor.googleauthor | 김대정 | - |
dc.contributor.googleauthor | 정정주 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | SCHOOL OF ELECTRICAL AND BIOMEDICAL ENGINEERING | - |
dc.identifier.pid | cchung | - |
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