Spectral and cross-spectral analysis of urban traffic flows

Traffic flow modeling and forecasting has attracted much interest in current literature because of its importance in both the theoretical and empirical aspects of ITS deployment and congestion. Despite the importance of modeling traffic flows, most of the literature has concentrated on univariate modeling of flow time-series with freeway data. The approaches considered are the univariate spectral analysis and cross-spectral analysis of urban traffic flow data. The purpose is to study spectral characteristics of traffic flows and to capture the lead and lag structure of flow between different urban locations. The empirical results suggest that the spectral characteristics of flows vary depending on the time of day, while traffic flows exhibit strong positive autocorrelation. The cross-spectral analysis results indicate a strong short-term flow correlation between different locations, and this correlation depends on the distance of the points examined.