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The cellular automata (CA) approach to traffic modeling is extended to allow for spatially homogeneous steady state solutions that cover a two dimensional region in the flow-density plane. Hence these models fulfill a basic postulate of a…

统计力学 · 物理学 2009-11-07 Boris S. Kerner , Sergey L. Klenov , Dietrich E. Wolf

Cellular automata have turned out to be important tools for the simulation of traffic flow. They are designed for an efficient impletmentation on the computer, but hard to treat analytically. Here we discuss several approaches for an…

统计力学 · 物理学 2007-05-23 Andreas Schadschneider

A model for 1D traffic flow is developed, which is discrete in space and time. Like the cellular automaton model by Nagel and Schreckenberg [J. Phys. I France 2, 2221 (1992)], it is simple, fast, and can describe stop-and-go traffic. Due to…

统计力学 · 物理学 2009-10-31 Dirk Helbing , Michael Schreckenberg

A new stochastic cellular automaton (CA) model of traffic flow, which includes slow-to-start effects and a driver's perspective, is proposed by extending the Burgers CA and the Nagel-Schreckenberg CA model. The flow-density relation of this…

统计力学 · 物理学 2009-11-10 Katsuhiro Nishinari , Minoru Fuku , Andreas Schadschneider

A general stochastic traffic cellular automaton (CA) model, which includes slow-to-start effect and driver's perspective, is proposed in this paper. It is shown that this model includes well known traffic CA models such as…

统计力学 · 物理学 2007-05-23 Satoshi Sakai , Katsuhiro Nishinari , Shinji Iida

In this paper a cellular automata model for one-lane traffic flow is presented. A new set of rules is proposed to better capture driver reactions to traffic that are intended to preserve safety on the highway. As a result, drivers behavior…

统计力学 · 物理学 2009-09-29 M. E. Larraga , L. Alvarez-Icaza

Although traffic simulations with cellular-automata models give meaningful results compared with empirical data, highway traffic requires a more detailed description of the elementary dynamics. Based on recent empirical results we present a…

统计力学 · 物理学 2007-05-23 W. Knospe , L. Santen , A. Schadschneider , M. Schreckenberg

We investigate a cellular automaton (CA) model of traffic on a bi-directional two-lane road. Our model is an extension of the one-lane CA model of {Nagel and Schreckenberg 1992}, modified to account for interactions mediated by passing, and…

统计力学 · 物理学 2009-10-31 Patrice Simon , Howard A Gutowitz

We suggest a disordered traffic flow model that captures many features of traffic flow. It is an extension of the Nagel-Schreckenberg (NaSch) stochastic cellular automata for single line vehicular traffic model. It incorporates random…

物理与社会 · 物理学 2009-11-11 K. Fourrate , M. Loulidi

We have developed a Nagel-Schreckenberg cellular automata model for describing of vehicular traffic flow at a single intersection. A set of traffic lights operating in fixed-time scheme controls the traffic flow. Open boundary condition is…

物理与社会 · 物理学 2011-05-10 M. Ebrahim Foulaadvand , Somayyeh Belbasi

We present results on the modeling of on- and off-ramps in cellular automata for traffic flow, especially the Nagel-Schreckenberg model. We study two different types of on-ramps that cause qualitatively the same effects. In a certain…

统计力学 · 物理学 2009-10-31 G. Diedrich , L. Santen , A. Schadschneider , J. Zittartz

Effects of large value assigned to the maximal car velocity on the fundamental diagrams in the Nagel-Schreckenberg model are studied by extended simulations. The function relating the flow in the congested traffic phase with the car density…

物理与社会 · 物理学 2007-05-23 Danuta Makowiec , Wieslaw Miklaszewski

We have developed a Nagel-Schreckenberg cellular automata model for describing of vehicular traffic flow at a single intersection. A set of traffic lights operating either in fixed-time or traffic adaptive scheme controls the traffic flow.…

元胞自动机与格子气 · 物理学 2008-09-23 M. Ebrahim Foulaadvand , Sommayeh Belbaasi

We examine a simple two lane cellular automaton based upon the single lane CA introduced by Nagel and Schreckenberg. We point out important parameters defining the shape of the fundamental diagram. Moreover we investigate the importance of…

凝聚态物理 · 物理学 2015-06-25 Marcus Rickert , Kai Nagel , Michael Schreckenberg , Andreas Latour

The jamming behavior of a single lane traffic model based on a cellular automaton approach is studied. Our investigations concentrate on the so-called VDR model which is a simple generalization of the well-known Nagel-Schreckenberg model.…

统计力学 · 物理学 2009-11-07 Robert Barlovic , Andreas Schadschneider , Michael Schreckenberg

We present a new cellular automata model of vehicular traffic in cities by combining ideas borrowed from the Biham-Middleton-Levine (BML) model of city traffic and the Nagel-Schreckenberg (NaSch) model of highway traffic. The model exhibits…

统计力学 · 物理学 2007-05-23 A. Schadschneider , D. Chowdhury , E. Brockfeld , K. Klauck , L. Santen , J. Zittartz

Within the class of stochastic cellular automata models of traffic flows, we look at the velocity dependent randomization variant (VDR-TCA) whose parameters take on a specific set of extreme values. These initial conditions lead us to the…

统计力学 · 物理学 2009-09-29 Sven Maerivoet , Bart De Moor

In recent years the modelling of traffic flow using methods from statistical physics, especially cellular automata models have allowed simulations of large traffic networks faster than real time. In this paper, we study a probabilistic…

软凝聚态物质 · 物理学 2007-05-23 M. E. Larraga , J. A. del Rio

Nonlinear wave phenomena such as stop-and-go traffic patterns are widely observed in vehicular flow but remain challenging to describe within a rigorous mathematical framework. Motivated by this, we investigate nonlinear wave structures in…

动力系统 · 数学 2026-05-18 Kota Ikeda , Tomoyuki Miyaji

Cellular automaton (CA) approach is an important theoretical framework for studying complex system behavior and has been widely applied in various research field. CA traffic flow models have the advantage of flexible evolution rules and…

元胞自动机与格子气 · 物理学 2018-10-09 Junfang Tian , Chenqiang Zhu , Rui Jiang
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