Memory effects and scaling properties of traffic flowsB.-S. K. Skagerstam and A. Hansen
Department of Physics, The Norwegian University of Science and Technology N-7491 Trondheim, Norway
received 21 April 2005; accepted in final form 28 September 2005
published online 19 October 2005
Traffic flows are studied in terms of their local noise of sound, which is an easily accessible experimental quantity. The sound noise data is studied making use of scaling properties of discrete wavelet transforms and Hurst exponents are extracted. The scaling behavior is used to characterize the traffic flows in terms of scaling properties of the memory function in the framework of Mori-Lee stochastic differential equations. The results obtained provides for a new theoretical as well as experimental framework to characterize the large-time behavior of traffic flows. The present paper outlines the procedure by making use of data from one-lane computer simulations as well as sound data of a real traffic flow. The experimental real traffic flow data we have obtained, using standard sound measurement techniques, is compatible with the presence of conventional diffusion at small time scales as well as 1/f noise at large time scales.
05.10.Gg - Stochastic analysis methods (Fokker-Planck, Langevin, etc.).
05.40.Ca - Noise.
89.40.Bb - Land transportation.
© EDP Sciences 2005