Time-dependent Hurst exponent in traffic time series

In this paper, we propose a new measure of variability, called the time-dependent Hurst exponent H(t), which fully captures the degree of variability of traffic flow at each time t. In order to assess the accuracy of the technique, we calculate the exponent H(t) for artificial series with assigned Hurst exponents H. We next calculate the exponent H(t) for the traffic time series observed on the Beijing Yuquanying highway. We find a much more pronounced time-variability in the local scaling exponent of traffic series compared to the artificial ones. In addition, the results show that the traffic variability can exhibit a non-monotonic multi-fractal behavior.