Compare linear interpolation and adaptive smoothing methods on traffic flow information reconstruction

With rapid development of transportation system, traffic information collection, which provides accurate and reliable traffic data, receives more and more attentions. However, under practical conditions, most roads and freeways are equipped with limited amount of loop detectors. Thus, researchers are delving into traffic information reconstruction by utilizing limited information. In this paper, we compare the classical linear interpolation method and a special nonlinear interpolation method, the adaptive smoothing method, on reconstructing the spatial-temporal dynamics of traffic flow rate, density and velocity. Tests on NGSIM dataset show that both methods are effective.