目前，基于视觉传感器的车辆检测已经成为车辆驾驶辅助领域的研究热点。但是迄今为止，大多数研究集中在白天好的光照条件，对夜晚条件下的车辆检测研究较少。本文提出了一种基于车灯的夜晚道路环境下的车辆检测算法,利用摄像机采集实时图像来检测自车后方的车辆。首先，基于亮度信息提取夜晚环境图像中的光亮目标物,然后，对提取的光亮目标物进行验证，去除路灯等干扰光源，从而得到真正的车辆头灯;最后，按照基于知识的方法，对提取到的车灯进行组合，并对组合后的车灯对进行验证，从而检测出夜晚道路环境下的车辆。实验结果表明本文算法易于实现，识别率高，适应性好。

Recently, vision sensor based vehicle detection becomes an attractive research area for the driver assistance system (DAS). But most research was carried out in the day time with a good lighting condition and what little research so far done in the night time assumed no interference of light. Hence a headlights based vehicle detection algorithm at nighttime environment is proposed in this paper. The proposed algorithm detects the rear vehicles via real-time image sequence capture Firstly, bright objects are extracted from the nighttime road scene images Then the extracted bright objects are verified based on rules to eliminate the interferential light sources and obtain the actual vehicle headlights Finally, a knowledge-based method is used to cluster vehicle headlights The clustered headlights are then validated Experimental results demonstrate the feasibility, effectiveness and robustness of the proposed algorithm on vehicle detection at night