Video-Based Traffic Flow Monitoring Algorithm

Yongmei Zhang, Jiarui Zhao, Ying Xiang, Jie Shu
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Abstract

Intelligent traffic is the main trend of urban development at present. In view of the increasing number of vehicles and traffic congestion, this paper presents a video-based traffic flow monitoring algorithm. The proposed algorithm extracts the vehicles using characteristics of the video, detects the moving vehicles and the non-motor vehicles by the pixel sizes and positions. According to the results of vehicle detection, the number of vehicles is analyzed, speed is calculated by moving distance, and combined with traffic flow to judge current road conditions are smooth, general, or congested. This algorithm adopts the three-frame difference method to detect moving vehicles to ensure the real-time performance of the algorithm and displays the number of vehicles, speed information, the number of vehicles per lane in a direct visual way, and vehicles entering the region of interest can be identified. The experiment results show the proposed algorithm can judge the current traffic situations in real-time based on video, and vehicle detection is more accurate.
基于视频的交通流量监控算法
智能交通是当前城市发展的主要趋势。针对车辆日益增多和交通拥堵的现状,提出了一种基于视频的交通流监控算法。该算法利用视频的特征提取车辆,通过像素大小和位置检测移动车辆和非机动车辆。根据车辆检测结果,分析车辆数量,通过移动距离计算速度,并结合交通流量判断当前道路状况是顺畅、一般还是拥堵。该算法采用三帧差分法检测移动车辆,保证了算法的实时性,并以直观的方式显示车辆数量、速度信息、每车道车辆数量,对进入感兴趣区域的车辆进行识别。实验结果表明,该算法能够基于视频实时判断当前交通状况,车辆检测更加准确。
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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