基于Hough变换的交通流状态辨别方法

Identification Method of Traffic Flow State Based on Hough Transformation

交通流状态辨别在智能交通系统中起着十分重要的作用。本文根据对交通流状态辨别研究的分析,提出基于Hough变换方法和模糊C均值聚类方法的交通状态辨别方法。其中,基于Hough变换的图像识别方法用于交通畅通流的辨别,模糊C均值聚类方法用于其它交通状态分类。而且利用快速路固定型交通检测器实时数据进行了实证分析,且与模糊C均值聚类方法进行了对比分析。分析结果表明本文方法与FCM方法相比,更符合于三相交通流理论,且满足城市快速路交通流的特征。该方法可用于交通流状态分析。

The identification of the traffic flow status plays a very important role in intelligence transportation system. A traffic flow state identification method based on Hough transformation and fuzzy C-means clustering algorithm is proposed in this paper. An image identification method using Hough transformation is used for identifying of traffic free phase, and fuzzy C-means clustering algorithm is used for discriminant of other traffic state phase. Using real traffic data, empirical analysis is conducted, and then proposed method is compared with fuzzy C-means clustering method. The experimental results show that the proposed method is conformed with three-phase traffic theroy better than the FCM method, and satisfistics the character of urban freeway traffic flows. The proposed method, in the future, can be used for the analysis of traffic flow state.