Experimental Features of Self-Organization in Traffic Flow

Kerner, Boris S.

doi:10.1103/physrevlett.81.3797

Cited by 524 publications

(469 citation statements)

References 10 publications

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“…As a consequence, the jam size increases with the distance upstream from the bottleneck. Again, this is in agreement with real observations on highway traffic [15].…”

Section: Reaction Time In a Vehicular Traffic Modelsupporting

confidence: 92%

Proceedings of the Asia-Pacific Econophysics Conference 2016 — Big Data Analysis and Modeling toward Super Smart Society — (APEC-SSS2016)

2017

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Transport systems in physical space exhibit various phenomena which may have some counterparts in socio-or econo-systems. We review here several of them. In highway vehicular traffic, the introduction of a reaction time leads to metastability and hysteresis. Pattern formation occurs in pedestrian flows. At a microscopic scale, we can learn from molecular pedestrians that transporting an object by opposite teams can be more efficient in a crowded environment and allow for an easy control of the system. Besides, we will show that the interplay between transport and the dynamics of the underlying network can sometimes lead to positive effects in terms of efficiency of transport.

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“…As a consequence, the jam size increases with the distance upstream from the bottleneck. Again, this is in agreement with real observations on highway traffic [15].…”

Section: Reaction Time In a Vehicular Traffic Modelsupporting

confidence: 92%

Proceedings of the Asia-Pacific Econophysics Conference 2016 — Big Data Analysis and Modeling toward Super Smart Society — (APEC-SSS2016)

2017

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show abstract

“…However, although this second argument can explain occurrences of capacity drops in a fundamental diagram, it does not in our view explain the capacity drop from Kerner andRehborn (1996a, p. R1300), which gives a more complete spatio-temporal picture, and where the flow into the jam is clearly larger than the flow out of the jam.…”

Section: Some Empirical Findingsmentioning

confidence: 68%

“…Often it is better to plot density , flow q, and velocity v as functions of time ( Figure 2). These measurements show that the typical transition is from the free-flow regime to a regime where throughput is virtually undiminished but densities are much higher, meaning much lower velocities (Mika et al 1969, Kerner and Rehborn 1996b, Kerner 1998. In Figure 1, this corresponds to a transition from the "free" branch around = 25 veh/km to values on the data cloud marked "congested" around = 40 veh/km.…”

Section: Some Empirical Findingsmentioning

confidence: 99%

“…The interpretation of these observations is less clear. One interpretation is that there are three phases: free flow, congested or synchronized, and jammed (Kerner and Rehborn 1996b, Kerner 1999b, Kerner and Klenov 2002, Kerner et al 2002. An alternative explanation is that the effects are caused by geometrical constraints.…”

Section: Some Empirical Findingsmentioning

confidence: 99%

“…This paper will look at modeling from the perspective of traffic jams and traffic jam formation. Different perspectives can be found, e.g., in Chowdhury et al (2000a), Helbing (2001), Kerner (1999b), and Lebacque and Lesort (1999).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling

Nagel¹,

Wagner

Woesler

2003

Operations Research

288

165

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Certain aspects of traffic flow measurements imply the existence of a phase transition. Models known from chaos and fractals, such as nonlinear analysis of coupled differential equations, cellular automata, or coupled maps, can generate behavior which indeed resembles a phase transition in the flow behavior. Other measurements point out that the same behavior could be generated by geometrical constraints of the scenario. This paper looks at some of the empirical evidence, but mostly focuses on different modeling approaches. The theory of traffic jam dynamics is reviewed in some detail, starting from the well-established theory of kinematic waves and then veering into the area of phase transitions. One aspect of the theory of phase transitions is that, by changing one single parameter, a system can be moved from displaying a phase transition to not displaying a phase transition. This implies that models for traffic can be tuned so that they display a phase transition or not.This paper focuses on microscopic modeling, i.e., coupled differential equations, cellular automata, and coupled maps. The phase transition behavior of these models, as far as it is known, is discussed. Similarly, fluid-dynamical models for the same questions are considered. A large portion of this paper is given to the discussion of extensions and open questions, which makes clear that the question of traffic jam dynamics is, albeit important, only a small part of an interesting and vibrant field. As our outlook shows, the whole field is moving away from a rather static view of traffic toward a dynamic view, which uses simulation as an important tool.

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Impact of velocity correlation and distribution on transport in fractured media: Field evidence and theoretical model

Kang

Borgne

Dentz

et al. 2015

Water Resources Research

137

176

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Flow and transport through fractured geologic media often leads to anomalous (non-Fickian) transport behavior, the origin of which remains a matter of debate: whether it arises from variability in fracture permeability (velocity distribution), connectedness in the flow paths through fractures (velocity correlation), or interaction between fractures and matrix. Here we show that this uncertainty of distribution-versus correlation-controlled transport can be resolved by combining convergent and push-pull tracer tests because flow reversibility is strongly dependent on velocity correlation, whereas late-time scaling of breakthrough curves is mainly controlled by velocity distribution. We build on this insight, and propose a Lagrangian statistical model that takes the form of a continuous time random walk (CTRW) with correlated particle velocities. In this framework, velocity distribution and velocity correlation are quantified by a Markov process of particle transition times that is characterized by a distribution function and a transition probability. Our transport model accurately captures the anomalous behavior in the breakthrough curves for both push-pull and convergent flow geometries, with the same set of parameters. Thus, the proposed correlated CTRW modeling approach provides a simple yet powerful framework for characterizing the impact of velocity distribution and correlation on transport in fractured media.

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Experimental Features of Self-Organization in Traffic Flow

Cited by 524 publications

References 10 publications

Proceedings of the Asia-Pacific Econophysics Conference 2016 — Big Data Analysis and Modeling toward Super Smart Society — (APEC-SSS2016)

Proceedings of the Asia-Pacific Econophysics Conference 2016 — Big Data Analysis and Modeling toward Super Smart Society — (APEC-SSS2016)

Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling

Impact of velocity correlation and distribution on transport in fractured media: Field evidence and theoretical model

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