“Dipole-layer” effect in dense traffic flow

Kerner, Boris S.; Konhäuser, P.; Schilke, Martin

doi:10.1016/0375-9601(96)00114-4

Cited by 39 publications

(9 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If one further increases the density, we observed dipole-like structures similarly to those described in Ref. [24]. Finally, for densities above 50-55 vehicles/km, one reaches again a stable regime [ Fig.…”

Section: B Stability Of Homogeneous Traffic With Respect To a Localisupporting

confidence: 83%

“…Investigations of instabilities arising from a localized perturbation of homogeneous traffic showed qualitatively the same scenario as has been found for the model of Kerner and Konhäuser [5,24]. For sufficiently high values of τ , homogeneous traffic at intermediate densities becomes unstable with respect to perturbations, leading to non-linear states like localized clusters, stop-and-go waves, or dipole-like structures, while homogeneous traffic flow is stable for high and low densities.…”

Section: Discussionsupporting

confidence: 68%

See 1 more Smart Citation

Derivation, properties, and simulation of a gas-kinetic-based, nonlocal traffic model

1999

View full text Add to dashboard Cite

We derive macroscopic traffic equations from specific gas-kinetic equations, dropping some of the assumptions and approximations made in previous papers. The resulting partial differential equations for the vehicle density and average velocity contain a non-local interaction term which is very favorable for a fast and robust numerical integration, so that several thousand freeway kilometers can be simulated in real-time. The model parameters can be easily calibrated by means of empirical data. They are directly related to the quantities characterizing individual driver-vehicle behavior, and their optimal values have the expected order of magnitude. Therefore, they allow to investigate the influences of varying street and weather conditions or freeway control measures. Simulation results for realistic model parameters are in good agreement with the diverse non-linear dynamical phenomena observed in freeway traffic. 05.70.Fh,05.60.+w,89.40.+k

show abstract

Section: B Stability Of Homogeneous Traffic With Respect To a Localisupporting

confidence: 83%

Section: Discussionsupporting

confidence: 68%

Derivation, properties, and simulation of a gas-kinetic-based, nonlocal traffic model

1999

View full text Add to dashboard Cite

show abstract

“…Moreover, the best fit of the net distance distributions is obtained for the integer parameter α = 4 in the free traffic regime, while we find an excellent agreement with α = 1 in the congested regime (see Figs. 5,6). This is not only a strong support of studies questioning a uniform behavior of drivers in all traffic regimes [42].…”

Section: Milansupporting

confidence: 71%

“…1: Schematic illustration of (a) the chosen initial perturbation ∆ρ(x) and the density-dependent perturbation amplitudes ∆ρc required for jam formation in the meta-stable density regime, (b) the related instability diagram of homogeneous (and slightly inhomogeneous) traffic flow (predicting stable traffic at small and high densities, linearly unstable traffic at medium densities, and meta-stable traffic in between) and (c) the finally resulting traffic patterns ρ(x) depending on the respective density regime. (Simplified diagram after [5,6], see also [4]. )…”

Section: Fluid-dynamic and Gas-kinetic Traffic Modelsmentioning

confidence: 99%

The physics of traffic and regional development

Helbing

Nagel

2004

Contemporary Physics

View full text Add to dashboard Cite

This contribution summarizes and explains various principles from physics which are used for the simulation of traffic flows in large street networks, the modeling of destination, transport mode, and route choice, or the simulation of urban growth and regional development. The methods stem from many-particle physics, from kinetic gas theory, or fluiddynamics. They involve energy and entropy considerations, transfer the law of gravity, apply cellular automata and require methods from evolutionary game theory. In this way, one can determine interaction forces among driver-vehicle units, reproduce breakdowns of traffic including features of synchronized congested flow, or understand changing usage patterns of alternative roads. One can also describe daily activity patterns based on decision models, simulate migration streams, and model urban growth as a particular kind of aggregation process.

show abstract

“…Schematic illustration of (a) the chosen localized perturbation and the density-dependent perturbation amplitudes ∆ρc required for jam formation in the metastable density regime, (b) the instability diagram of homogeneous (and slightly inhomogeneous) traffic flow, (c) the finally resulting traffic patterns as a function of the respective density regime. (Simplified diagram after Kerner et al, 1995aKerner et al, , 1996; see also Kerner and Konhäuser, 1994).…”

Section: Instability Diagram Stop-and-go Waves Metastability and Hmentioning

confidence: 99%

Traffic and related self-driven many-particle systems

2001

View full text Add to dashboard Cite

46 1. Gas-kinetic and macroscopic models 46 2. Microscopic models and cellular automata 47 E. Bi-directional and city traffic 47 F. Effects beyond physics 48 G. Traffic control and optimization 48 V. Pedestrian traffic 49 A. Observations 49 B. Behavioral force model of pedestrian dynamics 50 C. Self-organization phenomena and noise-induced ordering 51 1. Segregation 51 2. Oscillations 52 3. Rotation 52 D. Collective phenomena in panic situations 53 1. "Freezing by heating" 53 2. "Faster-is-slower effect" 53 3. "Phantom panics" 54 4. Herding behavior 54 VI. Flocking and spin systems 54 A.

show abstract

“Dipole-layer” effect in dense traffic flow

Cited by 39 publications

References 12 publications

Derivation, properties, and simulation of a gas-kinetic-based, nonlocal traffic model

Derivation, properties, and simulation of a gas-kinetic-based, nonlocal traffic model

The physics of traffic and regional development

Traffic and related self-driven many-particle systems

Contact Info

Product

Resources

About