Development of a road traffic state identification method based on image texture features

To determine the real-time traffic state accurately in road network or intersections, traffic state identification method is proposed based on image processing technology. During the image process, by analyzing the image texture features, the multi-scale block local binary patterns are taken as the features. The road traffic state identification model is established based on support vector classification. A road section is taken as an example, the images of three traffic states (free traffic flow, steady traffic flow, and forced traffic flow) are selected to test the established traffic state identification model. This method can be applied to determine the real-time traffic conditions, which can provide information for the traffic management decisions.