scholarly journals Self-Organized Criticality of Traffic Flow

Author(s):  
Jorge Laval

This paper shows that the kinematic wave model exhibits self-organized criticality when initialized with random initial conditions around the critical density. This has several important implications for traffic flow in the capacity state, such as: \item jam sizes obey a power law distribution with exponents 1/2, implying that both the mean and variance diverge to infinity, \item self-organization is an intrinsic property of traffic flow models in general, independently of other random perturbations, \item this critical behavior is a consequence of the flow maximization objective of traffic flow models, which can be observed on a density range around the critical density that depends on the length of the segment, \item typical measures of performance are proportional to the area under a Brownian excursion, and therefore are given by different scalings of the Airy distribution, \item traffic in the time-space diagram forms self-affine fractals where the basic unit is a triangle, in the shape of the fundamental diagram, containing 3 traffic states: voids, capacity and jams.

Author(s):  
Jorge Laval

This paper shows that the kinematic wave model exhibits self-organized criticality when initialized with random initial conditions around the critical density. A direct consequence is that conventional traffic management strategies seeking to maximize the flow may be detrimental as they make the system more unpredictable and more prone to collapse. Other implications for traffic flow in the capacity state are discussed, such as: \item jam sizes obey a power-law distribution with exponents 1/2, implying that both its mean and variance diverge to infinity, and therefore traditional statistical methods fail for prediction and control, \item the tendency to be at the critical state is an intrinsic property of traffic flow driven by our desire to travel at the maximum possible speed, \item traffic flow in the critical region is chaotic in that it is highly sensitive to initial conditions, \item aggregate measures of performance are proportional to the area under a Brownian excursion, and therefore are given by different scalings of the Airy distribution, \item traffic in the time-space diagram forms self-affine fractals where the basic unit is a triangle, in the shape of the fundamental diagram, containing 3 traffic states: voids, capacity and jams. This fractal nature of traffic flow calls for analysis methods currently not used in our field.


Author(s):  
Monish Tandale ◽  
Jinwhan Kim ◽  
Karthik Palaniappan ◽  
P. K. Menon ◽  
Jay Rosenberger ◽  
...  

The traffic flow conditions in developing countries are predominantly heterogeneous. The early developed traffic flow models have been derived from fluid flow to capture the behavior of the traffic. The very first two-equation model derived from fluid flow is known as the Payne-Whitham or PW Model. Along with the traffic flow, this model also captures the traffic acceleration. However, the PW model adopts a constant driver behavior which cannot be ignored, especially in the situation of heterogeneous traffic.This research focuses on testing the PW model and its suitability for heterogeneous traffic conditions by observing the model response to a bottleneck on a circular road. The PW model is mathematically approximated using the Roe Decomposition and then the performance of the model is observed using simulations.


2008 ◽  
Vol 41 (2) ◽  
pp. 14078-14083 ◽  
Author(s):  
J.W.C. Van Lint ◽  
Serge P. Hoogendoorn ◽  
A. Hegyi

1998 ◽  
Vol 47 (11) ◽  
pp. 1761
Author(s):  
LV XIAO-YANG ◽  
LIU MU-REN ◽  
KONG LING-JING

2003 ◽  
Vol 36 (2) ◽  
pp. 289-293 ◽  
Author(s):  
H. Ez-Zahraouy ◽  
Z. Benrihane ◽  
A. Benyoussef

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