基于视频检测技术的交通拥挤判别模型

Video-based discriminant model of traffic congestion

针对日益严重的城市道路交通拥挤问题,提出基于视频检测技术直接判断道路交通拥挤程度的方法。以道路占有率、占有率方差、占有率变化量绝对值为交通特征参数,研究了其与道路拥挤事件发生的关系,在此基础上利用模糊C-均值算法给出了一种交通状态划分方法,最后建立了一种新的交通拥挤判别模型。应用实际采集的视频数据,分别通过该模型及人为判断进行实验验证。实验结果表明该模型是有效可行的。

Aiming at the increasing congestion of traffic,this paper proposed a method employing video detection to judge the extent of congestion directly. The traffic characteristic parameters such as the occupancy of road,mean-variance of occupancy, adopted the absolute value of variation of occupancy and studied their influence on the occurrence of roads crowded events. Then proposed a kind of transportation state partition method,consequently,presented a new model of judging traffic congestion. Testing by the real video data collected on spot,the results of the proposed model is in good agreement with the judgment made by human,and thus the validity of method is demonstrated.