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레이더와 비전 센서 융합 기반 도로경계 인식 기술 개발
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 송봉섭 | - |
| dc.contributor.author | 김태련 | - |
| dc.date.accessioned | 2019-10-21T07:28:10Z | - |
| dc.date.available | 2019-10-21T07:28:10Z | - |
| dc.date.issued | 2016-08 | - |
| dc.identifier.other | 23235 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/18879 | - |
| dc.description | 학위논문(석사)--아주대학교 일반대학원 :기계공학과,2016. 8 | - |
| dc.description.tableofcontents | 1. 서 론 1.1 연구 배경 1.2 연구 내용 2. 시스템 구성 2.1 센서 구성 2.2 소프트웨어 아키텍쳐 3. 도로경계 인식 기술 4. 도로경계 추적 기술 5. 실험적 검증 6. 결론 7. 참고 문헌 Abstract | - |
| dc.language.iso | kor | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | 레이더와 비전 센서 융합 기반 도로경계 인식 기술 개발 | - |
| dc.title.alternative | Road Barrier Recognition based on Radar and Vision Sensor Fusion | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.alternativeName | Kim Taeryun | - |
| dc.contributor.department | 일반대학원 기계공학과 | - |
| dc.date.awarded | 2016. 8 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 758715 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000023235 | - |
| dc.subject.keyword | Road barrier | - |
| dc.subject.keyword | Sensor fusion | - |
| dc.subject.keyword | Kalman filter | - |
| dc.subject.keyword | PDAF | - |
| dc.description.alternativeAbstract | In this paper, the detection and tracking algorithms of road barrier including tunnel and guardrail are proposed to enhance performance and reliability for driver assistance systems. Although the road barrier is one of key features to determine a safe drivable area, it may be recognized incorrectly due to performance degradation of commercial sensors such as radar and monocular camera. Two frequent cases among many challenging problems are considered with the commercial sensors. The first case is that few tracks of radar are detected to road barrier due to material type of road barrier. The second one is inaccuracy of relative lateral position by radar, thus resulting in large variance of distance between a vehicle and road barrier. To overcome the problems, the detection and estimation algorithms of tracks corresponding to road barrier are proposed. Then, the tracking algorithm based on a probabilistic data association filter (PDAF) is used to reduce variation of lateral distance between vehicle and road barrier. Finally, the proposed algorithms are validated via field test data and their performance is compared with one of road barrier measured by lidar. | - |
- Appears in Collections:
- Graduate School of Ajou University > Department of Mechanical Engineering > 3. Theses(Master)
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