CAJ | 학술논문

研究了车辆偏航预警时道路坐标系与图像坐标系转换精度不稳定问题．对 CCD 前方道路图像进行了 ROI 划分，利用自适应动态阈值分割了车道线区域像素，通过 Sobel 算子提取车道线梯度边缘进行了双重阈值约束，运用 Hough 变换实现了车道线的直线拟合．根据成像射影原理推导出车道线左右水平倾角与车辆横向偏航率ε之间的关系，给出了基于车道线图像识别的车辆偏航预警策略，建立了车辆偏航预警模型．道路试验表明：当通过车道线图像识别进行车辆偏航预警时，车辆偏航率的平均相对误差为5．7％，满足车辆偏航预警准确性与实时性要求，有效实现了复杂道路环境中车道线识别与偏航预警．
연구료차량편항예경시도로좌표계여도상좌표계전환정도불은정문제．대 CCD 전방도로도상진행료 ROI 화분，이용자괄응동태역치분할료차도선구역상소，통과 Sobel 산자제취차도선제도변연진행료쌍중역치약속，운용 Hough 변환실현료차도선적직선의합．근거성상사영원리추도출차도선좌우수평경각여차량횡향편항솔ε지간적관계，급출료기우차도선도상식별적차량편항예경책략，건립료차량편항예경모형．도로시험표명：당통과차도선도상식별진행차량편항예경시，차량편항솔적평균상대오차위5．7％，만족차량편항예경준학성여실시성요구，유효실현료복잡도로배경중차도선식별여편항예경．
A robust vehicle departure prewarning system,which is a necessary promotion of active safety for high speed vehicle,was proposed based on lane recognition and vehicle lateral motion monitoring.First of all,a self-adaptive threshold method was adopted to segment the pixels of lane mark regions.Gradient edges of lane mark were then extracted by Sobel operator and restrained by dual-threshold method.Next lane marks were modeled as straight lines by Hough transformation.Departure prewarning model was finally built up based on imaging projection theory,from which the relationship between lane mark horizontal obliquity and lateral departure rate ε could be obtained.The proposed method was tested in real road environments.Experimental results demonstrated that the algorithm could recognize lane mark robustly in complex road environments.The average relative error of departure rateε was 5.7%.It is proved that the proposed method could satisfy the precision and real-time requirement of departure prewarning system.