Model based traffic congestion detection in optical remote sensing imagery

Abstract

Purpose: A new model based approach for the traffic congestion detection in time series of airborne optical digital camera images is proposed. Methods: It is based on the estimation of the average vehicle speed on road segments. The method puts various techniques together: the vehicle detection on road segments by change detection between two images with a short time lag, the usage of a priori information such as road data base, vehicle sizes and road parameters and a simple linear traffic model based on the spacing between vehicles. Results: The estimated speed profiles from experimental data acquired by an airborne optical sensor - 3K camera system - coincide well with the reference measurements. Conclusions: Experimental results show the great potential of the proposed method for the detection of traffic congestion on highways in along-track scenes. © The Author(s) 2010.