Multiple optimal current difference effect in the lattice traffic flow model

Kerner and Konhauser study moving jam dynamics first discovered in 1993 in Ref. 1. In light of their previous work, a new lattice hydrodynamic model is presented with consideration of the effect of multiple optimal current difference. To investigate the influences of new consideration on traffic jams, the linear stability analysis of the new model is conducted by employing the linear stability theory. Theoretical analysis result shows that the new consideration can stabilize traffic flow. By means of nonlinear analysis method, a modified Korteweg–deVries (mKdV) equation near the critical point is constructed and solved. The propagation behavior of traffic jam can thus be described by the kink–antikink soliton solution for the mKdV equation. Numerical simulation result shows that the effect of the multiple optimal current differences can suppress the emergence of traffic jams and the result is in good agreement with the analytical results.

[1]  Kerner,et al.  Deterministic spontaneous appearance of traffic jams in slightly inhomogeneous traffic flow. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[2]  T. Nagatani The physics of traffic jams , 2002 .

[3]  Boris S. Kerner,et al.  Introduction to Modern Traffic Flow Theory and Control: The Long Road to Three-Phase Traffic Theory , 2009 .

[4]  B. Kerner EXPERIMENTAL FEATURES OF SELF-ORGANIZATION IN TRAFFIC FLOW , 1998 .

[5]  Boris S. Kerner,et al.  Asymptotic theory of traffic jams , 1997 .

[6]  Takashi Nagatani,et al.  Modified KdV equation for jamming transition in the continuum models of traffic , 1998 .

[7]  S. Dai,et al.  Stabilization analysis and modified Korteweg-de Vries equation in a cooperative driving system. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  G. H. Peng A New Lattice Model Of Two-Lane Traffic Flow With The Consideration Of Multi-Anticipation Effect , 2013 .

[9]  孙剑,et al.  A lattice traffic model with consideration of preceding mixture traffic information , 2011 .

[10]  Kai Nagel,et al.  Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling , 2003, Oper. Res..

[11]  B. Kerner Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: A brief review , 2013 .

[12]  A. Schadschneider,et al.  Statistical physics of vehicular traffic and some related systems , 2000, cond-mat/0007053.

[13]  Kerner,et al.  Structure and parameters of clusters in traffic flow. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[14]  Kerner,et al.  Experimental features and characteristics of traffic jams. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[15]  D. Helbing Traffic and related self-driven many-particle systems , 2000, cond-mat/0012229.

[16]  P. Wagner,et al.  Metastable states in a microscopic model of traffic flow , 1997 .

[17]  Hongxia Ge,et al.  The theoretical analysis of the lattice hydrodynamic models for traffic flow theory , 2010 .

[18]  Hai-Jun Huang,et al.  AN EXTENDED OV MODEL WITH CONSIDERATION OF DRIVER'S MEMORY , 2009 .

[19]  Sun Dihua,et al.  Continuum modeling for two-lane traffic flow with consideration of the traffic interruption probability , 2010 .

[20]  Kerner,et al.  Cluster effect in initially homogeneous traffic flow. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[21]  Bin Jia,et al.  PHASE TRANSITIONS AND THE KORTEWEG-DE VRIES EQUATION IN THE DENSITY DIFFERENCE LATTICE HYDRODYNAMIC MODEL OF TRAFFIC FLOW , 2013 .

[22]  Shiqiang Dai,et al.  KdV and kink–antikink solitons in car-following models , 2005 .

[23]  Carlos F. Daganzo,et al.  TRANSPORTATION AND TRAFFIC THEORY , 1993 .

[24]  Boris S. Kerner,et al.  Local cluster effect in different traffic flow models , 1998 .

[25]  Hai-Jun Huang,et al.  A new car-following model with the consideration of the driver's forecast effect , 2010 .

[26]  A. Schadschneider,et al.  Metastable states in cellular automata for traffic flow , 1998, cond-mat/9804170.

[27]  Kurtze,et al.  Traffic jams, granular flow, and soliton selection. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[28]  Li Zhi-peng,et al.  Impact of the Next-Nearest-Neighbor Interaction on Traffic Flow of Highway with Slopes , 2012 .

[29]  Kerner,et al.  Experimental properties of complexity in traffic flow. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[30]  Martin Treiber,et al.  Traffic Flow Dynamics , 2013 .

[31]  Fuqiang Liu,et al.  STABILIZATION ANALYSIS AND MODIFIED KdV EQUATION OF LATTICE MODELS WITH CONSIDERATION OF RELATIVE CURRENT , 2008 .

[32]  Wen-xing Zhu,et al.  Solitary Density Waves for Improved Traffic Flow Model with Variable Brake Distances , 2012 .

[33]  Komatsu,et al.  Kink soliton characterizing traffic congestion. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[34]  Tao Song,et al.  STOCHASTIC CAR-FOLLOWING MODEL FOR EXPLAINING NONLINEAR TRAFFIC PHENOMENA , 2011 .