@article{ref1,
title="Identification of Chaos in the Traffic Flow Based on the Improved Largest Lyapunov Exponents Algorithm",
journal="Journal of Wuhan University of Technology (Transportation Science and Engineering)",
year="2006",
author="Li, Shuoqi and He, G.",
volume="30",
number="5",
pages="747-750",
abstract="An improved largest Lyapunov exponents' algorithm is put forward for rapid identification of chaos in traffic flow. First, the improved algorithm uses correlation integral method (C-C method) and Cao method to estimate two important variances of phase space reconstruction: embedding dimension m and delay time, then, uses small data sets to calculate the largest Lyapunov exponent from the time series. It can not only reconstruct characteristics of original data, but also avoid the limitation of the Wolf algorithm. In this case, the improved largest Lyapunov exponents' algorithm is used for the identification of chaos in time series of the simulated traffic flow based on car-following model and real traffic flow. The results indicate that there is chaos in the simulated traffic flow based on car-following model and real traffic flow, and the improved largest Lyapunov exponents' algorithm is one of the effective methods to identify the chaos in the time series exactly.<p />",
language="",
issn="1006-2823",
doi="",
url="http://dx.doi.org/"
}