Citation

Li S, He G. J. Wuhan Univ. Technol. Transp. Sci. Eng. 2006; 30(5): 747-750.

Affiliation

Institute of Systems Engineering, Tianjin University, Tianjin 300072, China

Copyright

(Copyright © 2006, Wuhan University of Technology)

DOI

unavailable

PMID

unavailable

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.