Traffic Jams

2017 ◽  
Author(s):  
Paul Charbonneau
Keyword(s):  
Collective Behavior ◽  
The Self ◽  
Traffic Model ◽  
Numerical Implementation ◽  
Basic Design ◽  
Traffic Jam ◽  
Traffic Jams ◽  
Self Organized ◽  
Car Traffic ◽  
Self Organized Criticality

This chapter considers the occurrence of traffic jams in the flow of moving automobiles as an example of complex collective behavior emerging from the interactions of system elements. It begins with a discussion of the basic design principle of an automobile traffic model and the numerical implementation of the model using the Python code. It then describes a representative simulation involving an ensemble of 300 cars initially at rest and distributed randomly, with a mean spacing of 10 units. It also examines how the traffic jam model behaves, traffic jams as avalanches, and the self-organized criticality of car traffic. The chapter includes exercises and further computational explorations, along with a suggested list of materials for further reading.

Sandpiles

2017 ◽  
Author(s):  
Paul Charbonneau
Keyword(s):  
Power Law ◽  
Slope Angle ◽  
The Self ◽  
Numerical Implementation ◽  
Sandpile Model ◽  
Self Organized ◽  
Self Organized Criticality

This chapter describes a simple computational idealization of a sandpile. When sand trickles slowly through your fingers, a small conical pile of sand forms below your hand. Sand avalanches of various sizes intermittently slide down the slope of the pile, which is growing both in width and in height but maintains the same slope angle. The pile of sand is a classic example of self-organized criticality. The chapter first provides an overview of the sandpile model before discussing its numerical implementation and a representative simulation involving a small 100-node lattice. It then examines the invariant power-law behavior of avalanches and the self-organized criticality of a sandpile. The chapter includes exercises and further computational explorations, along with a suggested list of materials for further reading.

SOLVING TRAFFIC JAMS: HUMAN INTERVENTION OR SELF-ORGANIZATION?

2003 ◽  
Vol 14 (08) ◽  
pp. 1007-1014
Author(s):  
ETAY MAR OR ◽  
ERAN SHIR ◽  
SORIN SOLOMON
Keyword(s):  
Critical Density ◽  
Original Model ◽  
The Self ◽  
Traffic Model ◽  
Self Organization ◽  
Human Intervention ◽  
Jamming Transition ◽  
Traffic Jams ◽  
Self Organized ◽  
External Intervention

We study the effect of external intervention on the self-organized jamming phase transition. The classical traffic model of Biham, Middleton, and Levine (BML) is modified to give priority to longer queues. It is shown that this lowers the critical density at which the jamming transition takes place (in comparison to the original model).

Problem behavior in autism spectrum disorders: A paradigmatic self-organized perspective of network structures

2019 ◽  
Vol 42 ◽  
Author(s):  
Lucio Tonello ◽  
Luca Giacobbi ◽  
Alberto Pettenon ◽  
Alessandro Scuotto ◽  
Massimo Cocchi ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Problem Behaviors ◽  
Autism Spectrum ◽  
The Self ◽  
Network Structures ◽  
Self Organized ◽  
Critical Equilibrium ◽  
Self Organized Criticality ◽  
Acute Agitation ◽  
Spectrum Disorders

AbstractAutism spectrum disorder (ASD) subjects can present temporary behaviors of acute agitation and aggressiveness, named problem behaviors. They have been shown to be consistent with the self-organized criticality (SOC), a model wherein occasionally occurring “catastrophic events” are necessary in order to maintain a self-organized “critical equilibrium.” The SOC can represent the psychopathology network structures and additionally suggests that they can be considered as self-organized systems.

SELF-ORGANIZED CRITICALITY IN 1D TRAFFIC FLOW

Fractals ◽  
1996 ◽  
Vol 04 (03) ◽  
pp. 279-283 ◽  
Author(s):  
TAKASHI NAGATANI
Keyword(s):  
Traffic Flow ◽  
Transition Probability ◽  
Annihilation Process ◽  
One Dimensional ◽  
Traffic Jams ◽  
Self Organized ◽  
Stochastic Transition ◽  
Self Organized Criticality ◽  
The One ◽  
Empty Wave

Annihilation process of traffic jams is investigated in a one-dimensional traffic flow on a highway. The one-dimensional fully asymmetric exclusion model with open boundaries for parallel update is extended to take into account stochastic transition of cars, where a car moves ahead with transition probability pt. Near pt=1, the system is driven asymptotically into a steady state exhibiting a self-organized criticality. Traffic jams with various lifetimes (or sizes) appear and disappear by colliding with an empty wave. The typical lifetime <m> of traffic jams scales as [Formula: see text], where ∆pt=1−pt. It is shown that the cumulative lifetime distribution Nm(∆pt) satisfies the scaling form [Formula: see text].

scholarly journals Transition from Self-Organized Criticality into Self-Organization during Sliding Si3N4 Balls against Nanocrystalline Diamond Films

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1055
Author(s):  
Bogatov ◽  
Podgursky ◽  
Vagiström ◽  
Yashin ◽  
Shaikh ◽  
...  
Keyword(s):  
Friction Force ◽  
Power Law ◽  
Early Stage ◽  
Nanocrystalline Diamond ◽  
The Self ◽  
Self Organization ◽  
Power Law Distribution ◽  
Reciprocating Sliding ◽  
Self Organized ◽  
Self Organized Criticality

The paper investigates the variation of friction force (Fx) during reciprocating sliding tests on nanocrystalline diamond (NCD) films. The analysis of the friction behavior during the run-in period is the focus of the study. The NCD films were grown using microwave plasma-enhanced chemical vapor deposition (MW-PECVD) on single-crystalline diamond SCD(110) substrates. Reciprocating sliding tests were conducted under 500 and 2000 g of normal load using Si3N4 balls as a counter body. The friction force permanently varies during the test, namely Fx value can locally increase or decrease in each cycle of sliding. The distribution of friction force drops (dFx) was extracted from the experimental data using a specially developed program. The analysis revealed a power-law distribution f-µ of dFx for the early stage of the run-in with the exponent value (µ) in the range from 0.6 to 2.9. In addition, the frequency power spectrum of Fx time series follows power-law distribution f-α with α value in the range of 1.0–2.0, with the highest values (1.6–2.0) for the initial stage of the run-in. No power-law distribution of dFx was found for the later stage of the run-in and the steady-state periods of sliding with the exception for periods where a relatively extended decrease of coefficient of friction (COF) was observed. The asperity interlocking leads to the stick-slip like sliding at the early stage of the run-in. This tribological behavior can be related to the self-organized criticality (SOC). The emergence of dissipative structures at the later stages of the run-in, namely the formation of ripples, carbonaceous tribolayer, etc., can be associated with the self-organization (SO).

Reinforcement Learning Scheme for Flocking Behavior Emergence

2007 ◽  
Vol 11 (2) ◽  
pp. 155-161 ◽  
Author(s):  
Koichiro Morihiro ◽  
◽  
Teijiro Isokawa ◽  
Haruhiko Nishimura ◽  
Masahito Tomimasu ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Collective Behavior ◽  
A Priori ◽  
The Self ◽  
Self Organized ◽  
Learning Scheme ◽  
Fish Schooling ◽  
Grouping Behavior ◽  
Flocking Behavior ◽  
New Framework

Collective behavior such as bird flocking, land animal herding, and fish schooling is well known in nature. Many observations have shown that there are no leaders to control the behavior of a group. Several models have been proposed for describing the grouping behavior, which we regard as a distinctive example of aggregate motions. In these models, a fixed rule is provided for each of the individuals a priori for their interactions in a reductive and rigid manner. In contrast, we propose a new framework for the self-organized grouping of agents by reinforcement learning. It is important to introduce a learning scheme for causing collective behavior in artificial autonomous distributed systems. The behavior of agents is demonstrated and evaluated through computer simulations and it is shown that their grouping behavior emerges as a result of learning.

scholarly journals Research on MAS-Based Supply Chain Resilience and Its Self-Organized Criticality

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Liang Geng ◽  
Renbin Xiao ◽  
Xing Xu
Keyword(s):  
Supply Chain ◽  
Fitness Function ◽  
The Self ◽  
Self Organization ◽  
Neighborhood Structure ◽  
Supply Chain System ◽  
Supply Chain Resilience ◽  
Self Organized ◽  
Agglomeration Effect ◽  
Self Organized Criticality

Building resilient supply chain is an effective way to deal with uncertain risks. First, by analyzing the self-organization of supply chain, the supply chain resilience is described as a macroscopic property that generates from self-organizing behavior of each enterprise on the microlevel. Second, a MAS-based supply chain resilience model is established and its local fitness function, neighborhood structure, and interaction rules that are applicable to supply chain system are designed through viewing the enterprise as an agent. Finally, with the help of a case, we find that there is an agglomeration effect and a SOC characteristic in supply chain and the evolution of supply chain is controlled by parameters of MAS. Managers can control the supply chain within the resilient range and choose a good balance between interest and risk by controlling enterprises’ behavior.

scholarly journals SELF-ORGANIZED CRITICAL BEHAVIOR: THE EVOLUTION OF FROZEN SPIN NETWORKS MODEL IN QUANTUM GRAVITY

2008 ◽  
Vol 23 (24) ◽  
pp. 3891-3899 ◽  
Author(s):  
JIAN-ZHEN CHEN ◽  
JIAN-YANG ZHU
Keyword(s):  
Quantum Gravity ◽  
The Self ◽  
Spin Networks ◽  
Spin Network ◽  
Underlying Graph ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Propagation Rule ◽  
First Time ◽  
The Universe

In quantum gravity, we study the evolution of a two-dimensional planar open frozen spin network, in which the color (i.e. the twice spin of an edge) labeling edge changes but the underlying graph remains fixed. The mainly considered evolution rule, the random edge model, is depending on choosing an edge randomly and changing the color of it by an even integer. Since the change of color generally violate the gauge invariance conditions imposed on the system, detailed propagation rule is needed and it can be defined in many ways. Here, we provided one new propagation rule, in which the involved even integer is not a constant one as in previous works, but changeable with certain probability. In random edge model, we do find the evolution of the system under the propagation rule exhibits power-law behavior, which is suggestive of the self-organized criticality (SOC), and it is the first time to verify the SOC behavior in such evolution model for the frozen spin network. Furthermore, the increase of the average color of the spin network in time can show the nature of inflation for the universe.

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