基于时空图的交通流量统计和交通状态检测

Traffic flow estimation and traffic state detection based on the space-time map

提出了一种新的基于时空图的交通流量统计和交通状态检测方法。首先,通过人机交互的方法设定检测线,并利用检测线计算时空图;然后,对时空图进行边缘提取、图像分割等处理,利用时空图上车辆的边缘、形状和占道率等信息,计算出一段时间内的交通流量。此外,还通过时空图的边缘信息的差异,将当前时间段的交通状态分为通畅、拥挤和堵塞三种不同的情况。实验结果表明,在摄像机安装位置合适的情况下,该方法统计交通流量的误差低于8%,判断交通状态的误差为0,具有很好的商业实用性。

We propose a novel traffic flow estimation and traffic state detection approach. Firstly, the detection line used to compute the space-time map is set via man-machine interaction, and the proces- ses such as edge detection, image segmentation and so on are then performed in the space-time map. The traffic flow for a period of time is estimated by using the information of edge, shape and the rate of road occupation. In addition, the current traffic state is divided into three levels： clear, crowd and jam by u- sing the difference between edge information in the space-time map. Experimental results show that the proposed approach can effectively compute the traffic flow and detect the traffic state, and it is practical for commerce.