Model based traffic congestion detection in optical remote sensing imagery

摘要

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.