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학술지 Toward Accurate Road Detection in Challenging Environments Using 3D Point Clouds
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저자
변재민, 서범수, 이지홍
발행일
201506
출처
ETRI Journal, v.37 no.3, pp.606-616
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.15.0113.1131
협약과제
13VC1700, ICT기반 차량/운전자 협력자율주행 시스템(Co-Pilot)의 판단/제어 기술 개발, 한우용
초록
In this paper, we propose a novel method for road recognition using 3D point clouds based on a Markov random field (MRF) framework in unstructured and complex road environments. The proposed method is focused on finding a solution for an analysis of traversable regions in challenging environments without considering an assumption that has been applied in many past studies; that is, that the surface of a road is ideally flat. The main contributions of this research are as follows: (a) guidelines for the best selection of the gradient value, the average height, the normal vectors, and the intensity value and (b) how to mathematically transform a road recognition problem into a classification problem that is based on MRF modeling in spatial and visual contexts. In our experiments, we used numerous scans acquired by an HDL-64E sensor mounted on an experimental vehicle. The results show that the proposed method is more robust and reliable than a conventional approach based on a quantity evaluation with ground truth data for a variety of challenging environments.
키워드
3D point clouds, 3DLiDAR sensor, Intelligent vehicle, MRF model, Road detection
KSP 제안 키워드
3D point cloud, Classification problems, Complex road, Ground truth data, MRF model, Markov Random Field, Recognition problem, Road recognition, experimental vehicle, gradient value, intelligent vehicle