Empirical mode decomposition of traffic time series

We apply an important tool to extract the traffic cycle signal from traffic data. An alternative to traditional analysis is a non-linear empirical mode decomposition (EMD) method. This method is adaptive and therefore highly efficient at identifying embedded structures, even those with small amplitudes. Using this analysis, the traffic time series are completely decomposed into five non-stationary temporal modes including a 24-hour cycle signal, a 1-week cycle signal and a trend. It indicates that EMD can be used to analyze and interpret the traffic flow.