不确定背景环境下车道检测技术的研究

针对不确定背景的交通环境,提出一种新的车道检测算法。确定道路路面的色彩范围,提取车道标线的色彩信息,消除光照强度变化对车道标线信息提取过程的影响;通过对比车辆与车道标线在大小、形状和运动模式3方面的差异排除车道中车辆对车道线检测的干扰;单帧图像的车道检测结果存储于车道一致性确认模块中,运用车道标志线一致性确认提高车道检测结果的准确性。试验结果表明,该方法能够有效地检测各种天气条件下车道区域以及解决车道遮挡问题。

Study of Lane Detection Techniques under Uncertain Circumstances

A new method for lane detection in uncertain circumstances is proposed. After determining the color scale of the road, the color information of the lane marks is extracted to eliminate the influence of the illumination changes. The interference of the vehicles with the lane detection is eliminated through comparing the size, shape and motion pattern between the vehicles and the lane marks. By storing the single-image lane detection results in the lane-coherence-validation module, the accuracy of the lane detection enhances. Experimental results show that the proposed algorithm is able to robustly find the lane boundary under various lighting conditions and to solve the problem of the occupancy of the road by the vehicles.