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arXiv · cond-mat/0112139

Long-lived states in synchronized traffic flow. Empirical prompt and dynamical trap model

Abstract

The present paper proposes a novel interpretation of the widely scattered states (called synchronized traffic) stimulated by Kerner's hypotheses about the existence of a multitude of metastable states in the fundamental diagram. Using single vehicle data collected at the German highway A1, temporal velocity patterns have been analyzed to show a collection of certain fragments with approximately constant velocities and sharp jumps between them. The particular velocity values in these fragments vary in a wide range. In contrast, the flow rate is more or less constant because its fluctuations are mainly due to the discreteness of traffic flow. Subsequently, we develop a model for synchronized traffic that can explain these characteristics. Following previous work (I.A.Lubashevsky, R.Mahnke, Phys. Rev. E v. 62, p. 6082, 2000) the vehicle flow is specified by car density, mean velocity, and additional order parameters $h$ and $a$ that are due to the many-particle effects of the vehicle interaction. The parameter $h$ describes the multilane correlations in the vehicle motion. Together with the car density it determines directly the mean velocity. The parameter $a$, in contrast, controls the evolution of $h$ only. The model assumes that $a$ fluctuates randomly around the value corresponding to the car configuration optimal for lane changing. When it deviates from this value the lane change is depressed for all cars forming a local cluster. Since exactly the overtaking manoeuvres of these cars cause the order parameter $a$ to vary, the evolution of the car arrangement becomes frozen for a certain time. In other words, the evolution equations form certain dynamical traps responsible for the long-time correlations in the synchronized mode.

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BibTeXRIS

Ihor Lubashevsky, Reinhard Mahnke, Peter Wagner, Sergey Kalenkov. 2002-04-06. Long-lived states in synchronized traffic flow. Empirical prompt and dynamical trap model. https://doi.org/10.1103/physreve.66.016117

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