Lane Detection and Lane Departure Warning Using Front View Camera in Vehicle

Domagoj Špoljar, M. Vranješ, Sandra Nemet, N. Pjevalica
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引用次数: 6

Abstract

There has been a significant change in trends in the automotive industry over the last ten years. Vehicles equipped with different Advanced Driver Assistance Systems (ADAS) are increasingly present on the roads, whereas the level of their autonomy increases over time. For autonomous vehicles to work properly, it is necessary to have reliable ADAS that process different input signals from distinct sensors. One of the most important ADAS algorithms is that intended for lane detection (LD) and lane departure warning (LDW). In this paper, a new algorithm for LD on the road and LDW, which processes only images obtained from the camera located at the front end of the vehicle, is proposed. The algorithm provides information on the number of detected lane lines in the image and their position on the image while marking the current driving lane and the first two adjacent lanes if they exist. If the vehicle is departing from the lane, a corresponding warning message is shown to the driver. The algorithm was tested on a set of 12 video sequences (17552 frames in total) recorded during day and night in different weather conditions. The results showed that the algorithm achieves high performance in most cases, while for some challenging cases there is room for further improvement.
基于车辆前视摄像头的车道检测与车道偏离预警
在过去的十年里,汽车工业的趋势发生了重大变化。配备不同高级驾驶辅助系统(ADAS)的车辆越来越多地出现在道路上,而它们的自主程度也随着时间的推移而提高。为了让自动驾驶汽车正常工作,必须有可靠的ADAS来处理来自不同传感器的不同输入信号。最重要的ADAS算法之一是车道检测(LD)和车道偏离警告(LDW)。本文提出了一种仅处理车辆前端摄像头图像的道路LDW和LDW算法。该算法提供图像中检测到的车道线的数量及其在图像上的位置信息,同时标记当前行驶车道和前两个相邻车道(如果存在)。如果车辆偏离车道,则会向驾驶员显示相应的警告信息。该算法在不同天气条件下白天和夜间录制的12个视频序列(共17552帧)上进行了测试。结果表明,该算法在大多数情况下都达到了较高的性能,但在一些具有挑战性的情况下仍有进一步改进的空间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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