Effect of driver over-acceleration on traffic breakdown in three-phase cellular automaton traffic flow models

Kerner, Boris S.; Klenov, Sergey L.; Hermanns, Gerhard; Schreckenberg, Michael

doi:10.1016/j.physa.2013.04.035

Cited by 90 publications

(41 citation statements)

References 66 publications

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“…We will show that this microscopic theory of the S→F instability exhibits a general character: All results can be derived with very different mathematical stochastic three-phase traffic flow models, in particular with the KKSW (Kerner-Klenov-SchreckenbergWolf) CA model [42,53,54] and the Kerner-Klenov stochastic model [41,43,[48][49][50][51]. Because the KKSW CA model is considerably more simple one than the KernerKlenov stochastic model, we present results of the microscopic theory of the S→F instability based on a study on the KKSW CA model; associated results derived with the Kerner-Klenov stochastic model are briefly considered in discussion section.…”

Section: Introductionmentioning

confidence: 91%

“…Other physical features of the KKSW CA model have been explained in [53]. A model of an on-ramp bottleneck is the same as that presented in [55].…”

Section: Rules Of Vehicle Motion In Kksw Ca Modelmentioning

confidence: 99%

“…The first mathematical implementation of these hypotheses of three-phase theory [29,30,[32][33][34][35][36] has been a stochastic continuous in space microscopic model [41] and a CA three-phase model [42], which has been further developed for different applications in [43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58]. Over time there has been developed a number of other three-phase flow models (e.g., ) that incorporate some of the hypotheses of the three-phase theory [29,30,[34][35][36].…”

Section: Introductionmentioning

confidence: 99%

“…(iv) What is the physics of a random time delay to the F→S transition at the bottleneck found in simulations with stochastic three-phase traffic flow models [29,30,[42][43][44][45][46][47][48][49][50][51][53][54][55]?…”

Section: Introductionmentioning

confidence: 99%

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Microscopic theory of traffic-flow instability governing traffic breakdown at highway bottlenecks: Growing wave of increase in speed in synchronized flow

Kerner

2015

Phys. Rev. E

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We have revealed a growing local speed wave of increase in speed that can randomly occur in synchronized flow (S) at a highway bottleneck. The development of such a traffic flow instability leads to free flow (F) at the bottleneck; therefore, we call this instability as an S→F instability. Whereas the S→F instability leads to a local increase in speed (growing acceleration wave), in contrast, the classical traffic flow instability introduced in 50s-60s and incorporated later in a huge number of traffic flow models leads to a growing wave of a local decrease in speed (growing deceleration wave). We have found that the S→F instability can occur only, if there is a finite time delay in driver overacceleration. The initial speed disturbance of increase in speed (called "speed peak") that initiates the S→F instability occurs usually at the downstream front of synchronized flow at the bottleneck. There can be many speed peaks with random amplitudes that occur randomly over time. It has been found that the S→F instability exhibits the nucleation nature: Only when a speed peak amplitude is large enough, the S→F instability occurs; in contrast, speed peaks of smaller amplitudes cause dissolving speed waves of a local increase in speed (dissolving acceleration waves) in synchronized flow. We have found that the S→F instability governs traffic breakdown -a phase transition from free flow to synchronized flow (F→S transition) at the bottleneck: The nucleation nature of the S→F instability explains the metastability of free flow with respect to an F→S transition at the bottleneck.

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Section: Introductionmentioning

confidence: 91%

“…Other physical features of the KKSW CA model have been explained in [53]. A model of an on-ramp bottleneck is the same as that presented in [55].…”

Section: Rules Of Vehicle Motion In Kksw Ca Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Microscopic theory of traffic-flow instability governing traffic breakdown at highway bottlenecks: Growing wave of increase in speed in synchronized flow

Kerner

2015

Phys. Rev. E

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“…In this work, the generic feature refers to a discontinuous character of driver over-acceleration which is inferred by an integration of two qualitatively different mechanisms of overacceleration [10].…”

Section: Related Workmentioning

confidence: 99%

City traffic flow breakdown prediction based on fuzzy rough set

Yang

et al. 2017

Open Physics

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Abstract:In city traffic management, traffic breakdown is a very important issue, which is defined as a speed drop of a certain amount within a dense traffic situation. In order to predict city traffic flow breakdown accurately, in this paper, we propose a novel city traffic flow breakdown prediction algorithm based on fuzzy rough set. Firstly, we illustrate the city traffic flow breakdown problem, in which three definitions are given, that is, 1) Pre-breakdown flow rate, 2) Rate, density, and speed of the traffic flow breakdown, and 3) Duration of the traffic flow breakdown. Moreover, we define a hazard function to represent the probability of the breakdown ending at a given time point. Secondly, as there are many redundant and irrelevant attributes in city flow breakdown prediction, we propose an attribute reduction algorithm using the fuzzy rough set. Thirdly, we discuss how to predict the city traffic flow breakdown based on attribute reduction and SVM classifier. Finally, experiments are conducted by collecting data from I-405 Freeway, which is located at Irvine, California. Experimental results demonstrate that the proposed algorithm is able to achieve lower average error rate of city traffic flow breakdown prediction.

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Parallel Simulation and Visualization of Traffic Flows Using Cellular Automata Theory and Quasigasdynamic Approach

Chechina

Churbanova

Sokolov

et al. 2020

Emerging Extended Reality Technologies for Industry 4.0

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Effect of driver over-acceleration on traffic breakdown in three-phase cellular automaton traffic flow models

Cited by 90 publications

References 66 publications

Microscopic theory of traffic-flow instability governing traffic breakdown at highway bottlenecks: Growing wave of increase in speed in synchronized flow

Microscopic theory of traffic-flow instability governing traffic breakdown at highway bottlenecks: Growing wave of increase in speed in synchronized flow

City traffic flow breakdown prediction based on fuzzy rough set

Parallel Simulation and Visualization of Traffic Flows Using Cellular Automata Theory and Quasigasdynamic Approach

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