Multifractal Fourier detrended cross-correlation analysis of traffic signals

Xiaojun Zhao, Pengjian Shang, Aijing Lin and Gang Chen

Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, issue 21, 3670-3678

Abstract: Multifractal detrended cross-correlation analysis (MF-DXA) has been developed to detect the long-range power-law cross-correlation of considered signals in the presence of non-stationarity. However, crossovers arising from extrinsic periodic trends make the scaling behavior difficult to analyze. We introduce a Fourier filtering method to eliminate the trend effects and systematically investigate the multifractal cross-correlation of simulated and real traffic signals. The crossover locations are found approximately corresponding to the periods of underlying trend. Traffic velocity on one road and flows on adjacent roads show strong cross-correlation. They also present weak multifractality after periodic trends are removed. The traffic velocity and flow are cross-correlated in opposite directions which is accordant to their actual evolution.

Keywords: Multifractal detrended cross-correlation analysis; Fourier filtering; Traffic signal; Cross-correlation exponent; Periodic trend; Crossover (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (44)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:390:y:2011:i:21:p:3670-3678

DOI: 10.1016/j.physa.2011.06.018

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