Impact of the traffic interruption probability of optimal current on traffic congestion in lattice model

Peng, Guanghan; Lu, Wen-Hsiang; He, Hong-di

doi:10.1016/j.physa.2015.01.045

Cited by 33 publications

(6 citation statements)

References 47 publications

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“…Based on the single-lane case, Nagatani [28] developed a two-lane lattice hydrodynamic model to reveal the effect of lane changing on the stability of traffic flow. Since then, the two-lane lattice hydrodynamic model was extended with various traffic factors such as traffic flux difference [29][30][31], traffic density difference [32][33][34], optimal current difference [35][36][37], and anticipation effect [38,39].…”

Section: Introductionmentioning

confidence: 99%

A New Two-Lane Lattice Model with the Consideration of the Driver’s Self-Anticipation Current Difference Effect

Zhao

Wan

Qin

et al. 2022

Mathematical Problems in Engineering

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To prevent traffic congestion, drivers always adjust the driving behavior with their driving information. By considering the self-anticipation effect and the optimal current difference effect on traffic flow stability, a novel two-lane lattice hydrodynamic model is proposed. Compared with Peng’s model, the linear stability analysis results reveal that the self-anticipation term can effectively enlarge the stable region on the phase diagram. Then, a reductive perturbation method is used to derive the mKdV equation describing traffic congestion near the critical point. Nonlinear analyses show that the traffic congestions can be effectively suppressed by taking the coefficient of lane-changing behaviors γ and the anticipation time τ into account. These results further indicate that the driver’s self-anticipation current difference effect can efficiently alleviate traffic jams. Furthermore, the numerical simulations with periodic boundary conditions also confirm the effectiveness of theoretical results.

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Section: Introductionmentioning

confidence: 99%

A New Two-Lane Lattice Model with the Consideration of the Driver’s Self-Anticipation Current Difference Effect

Zhao

Wan

Qin

et al. 2022

Mathematical Problems in Engineering

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“…en, the stability condition and mKdV equation can be, respectively, obtained with the linear analysis and nonlinear analysis methods. Subsequently, many extended works have been developed by taking different factors into accounts, such as driver's memory [27][28][29][30][31], driver's anticipation effect [32][33][34], density difference [35], traffic interruption probability [36][37][38], and "backward-looking" effect [39][40][41].…”

Section: Introductionmentioning

confidence: 99%

An Improved Lattice Hydrodynamic Model by considering the Effect of “Backward‐Looking” and Anticipation Behavior

et al. 2021

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In order to prevent the occurrence of traffic accidents, drivers always focus on the running conditions of the preceding and rear vehicles to change their driving behavior. By taking into the “backward-looking” effect and the driver’s anticipation effect of flux difference consideration at the same time, a novel two-lane lattice hydrodynamic model is proposed to reveal driving characteristics. The corresponding stability conditions are derived through a linear stability analysis. Then, the nonlinear theory is also applied to derive the mKdV equation describing traffic congestion near the critical point. Linear and nonlinear analyses of the proposed model show that how the “backward-looking” effect and the driver’s anticipation behavior comprehensively affect the traffic flow stability. The results show that the positive constant γ , the driver’s anticipation time τ , and the sensitivity coefficient p play significant roles in the improvement of traffic flow stability and the alleviation of the traffic congestion. Furthermore, the effectiveness of linear stability analysis and nonlinear analysis results is demonstrated by numerical simulations.

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“…Xue (2002), Li et al (2011) use twodimensional lattice fluid mechanics models to study pedestrian flow; Sun et al (2014), and Zhu and Li (2018) constructed separately the lattice models considering the influence of two adjacent grids or multiple grids in front; Ge and Cheng (2008) construct the lattice model considering the influence of rear adjacent lattices. In addition, Peng et al (2014), Peng (2013), Peng et al (2015Peng et al ( , 2012b use the lattice models to study the effect of response delay, expectation effect, memory effect, traffic flow interruption effect and other factors on traffic flow.…”

Section: Introductionmentioning

confidence: 99%

Analysis of a novel two-lane lattice model with consideration of density integral and relative flow information

Cheng

2020

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Purpose This study aims to consider the influence of density difference integral and relative flow difference on traffic flow, a novel two-lane lattice hydrodynamic model is proposed. The stability criterion for the new model is obtained through the linear analysis method. Design/methodology/approach The modified Korteweg de Vries (KdV) (mKdV) equation is derived to describe the characteristic of traffic jams near the critical point. Numerical simulations are carried out to explore how density difference integral and relative flow difference influence traffic stability. Numerical and analytical results demonstrate that traffic congestions can be effectively relieved considering density difference integral and relative flow difference. Findings The traffic congestions can be effectively relieved considering density difference integral and relative flow difference. Originality/value Novel two-lane lattice hydrodynamic model is presented considering density difference integral and relative flow difference. Applying the linear stability theory, the new model’s linear stability is obtained. Through nonlinear analysis, the mKdV equation is derived. Numerical results demonstrate that the traffic flow stability can be efficiently improved by the effect of density difference integral and relative flow difference.

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Impact of the traffic interruption probability of optimal current on traffic congestion in lattice model

Cited by 33 publications

References 47 publications

A New Two-Lane Lattice Model with the Consideration of the Driver’s Self-Anticipation Current Difference Effect

A New Two-Lane Lattice Model with the Consideration of the Driver’s Self-Anticipation Current Difference Effect

An Improved Lattice Hydrodynamic Model by considering the Effect of “Backward‐Looking” and Anticipation Behavior

Analysis of a novel two-lane lattice model with consideration of density integral and relative flow information

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