Self-Organized Criticality and $1/f$ Noise in Traffic
Abstract
Description
Phantom traffic jams may emerge ``out of nowhere'' from small fluctuations rather than being triggered by large, exceptional events. We show how phantom jams arise in a model of single lane highway traffic, which mimics human driving behavior. Surprisingly, the optimal state of highest efficiency, with the largest throughput, is a critical state with traffic jams of all sizes. We demonstrate that open systems self-organize to the most efficient state. In the model we study, this critical state is a percolation transition for the phantom traffic jams. At criticality, the individual jams have a complicated fractal structure where cars follow an intermittent stop and go pattern. We analytically derive the form of the corresponding power spectrum to be $1/f^α$ with $α=1$ exactly. This theoretical prediction agrees with our numerical simulations and with observations of $1/f$ noise in real traffic.
13 pages, uuencoded with style file mprocl.sty. 6 Figures not included but can be mailed on request. Will appear in ``Traffic and Granular Flow,'' eds. D.E. Wolf, M. Schreckenberg, and A. Bachem (World Scientific, Singapore, 1996.)
13 pages, uuencoded with style file mprocl.sty. 6 Figures not included but can be mailed on request. Will appear in ``Traffic and Granular Flow,'' eds. D.E. Wolf, M. Schreckenberg, and A. Bachem (World Scientific, Singapore, 1996.)