Spectral and time‐frequency analyses of freeway traffic flow

This paper uses spectral and time‐frequency analyses to treat three macroscopic traffic characteristics, namely, time mean speed, volume and occupancy as stochastic processes. Spectral and time‐frequency analyses are performed to characterize power spectral density (PSD), cross‐PSD, autocorrelation and cross‐correlation of these characteristics using TransGuide traffic data collected from four different freeways. It is found that low‐frequency components dominate the PSDs of speed, volume and occupancy at all times. The magnitude of PSDs decreases dramatically as frequency increases and remains almost at a constant level in high‐frequency regimes. A power law is found to exist, which describes the relationship between the frequency and the PSD of traffic characteristics. It is also found that speed can be properly modeled by a narrowband low‐pass stochastic process in a low‐frequency regime and by a nonzero mean white noise in a high‐frequency regime. Strong periodicities and synchronization are both shown in traffic flow. A variety of frequencies can be excited by congestion, and there is no dominant frequency found in stop‐and‐go traffic. Copyright © 2013 John Wiley & Sons, Ltd.