基于CUDA的行车安全预警方法

为了提高机动车驾驶时的安全性，提出了基于计算机视觉的行车安全中车距估计与超车检测方法。首先，使用车辆阴影检测方法确定车辆位置，根据阴影位置和视觉中心点的距离建立车距估计函数；其次，对超车情况使用背景光流建模的方法建立光流估计方程，通过估计光流将行驶中的正常物体与非正常物体分开，从而辨识驾驶途中的超车现象。根据车距和超车情况的检测及时提醒驾驶员注意行车中可能存在的安全隐患。实验结果表明该方法可以较为准确地估计车距、检测超车情况。在统一设备架构（CUDA）下使用图形处理器（GPU） NVIDIA GeForce GTX680显卡对算法进行加速，可以达到48.9ms/帧的处理速率，基本满足了实时处理的要求。

Early warning method for driving safety based on CUDA

To improve the safety of vehicles while driving, a computer vision-based inter-vehicle distance estimation and warning method was proposed in this paper. First, shadow detection method was applied to detect shadow of cars ahead, and inter-vehicle distance estimation function was built based on the distance between shadow and vision center of a frame. Then, estimation equations for non-threatened background optical flow was built, and by judging optical flow with the estimation equations, the abnormal objects could be separated from others, thus the overtaking event could be recognized. Based on the inter-vehicle distance and detection of overtaking event, the driver could be timely warned of the potential safety hazard. The experimental results prove that the proposed method can estimate inter-vehicle distance and detect overtaking event accurately. Finally, NVIDIA GeForce GTX680 GPU (Graphic Processing Unit) was used to accelerate the algorithm on Compute Unified Device Architecture (CUDA) platform and achieve the processing speed of 48.9 ms per frame which basically meets the real-time processing demand.