Spectral and time‐frequency analyses of freeway traffic flow

SUMMARY 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.

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