Rule 184 fuzzy cellular automaton as a mathematical model for traffic flow

The rule 184 fuzzy cellular automaton is regarded as a mathematical model of traffic flow because it contains the two fundamental traffic flow models, the rule 184 cellular automaton and the Burgers equation, as special cases. We show that the fundamental diagram (flux-density diagram) of this model consists of three parts: a free-flow part, a congestion part and a two-periodic part. The two-periodic part, which may correspond to the synchronized mode region, is a two-dimensional area in the diagram, the boundary of which consists of the free-flow and the congestion parts. We prove that any state in both the congestion and the two-periodic parts is stable, but is not asymptotically stable, while that in the free-flow part is unstable. Transient behaviour of the model and bottle-neck effects are also examined by numerical simulations. Furthermore, to investigate low or high density limit, we consider ultradiscrete limit of the model and show that any ultradiscrete state turns to a travelling wave state of velocity one in finite time steps for generic initial conditions.

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

[2]  B D Greenshields,et al.  A study of traffic capacity , 1935 .

[3]  Paola Flocchini,et al.  On the Asymptotic Behavior of Fuzzy Cellular Automata , 2009, Electron. Notes Theor. Comput. Sci..

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

[5]  Havlin,et al.  Presence of many stable nonhomogeneous states in an inertial car-following model , 2000, Physical review letters.

[6]  Stephen Wolfram,et al.  Theory and Applications of Cellular Automata , 1986 .

[7]  Kai Nagel Comment on: B. S. Kerner and H. Rehborn, experimental properties of complexity in traffic flow, physical review E 53(5) R4275 (1996). , 1996 .

[8]  M J Lighthill,et al.  On kinematic waves II. A theory of traffic flow on long crowded roads , 1955, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[9]  J. Satsuma,et al.  Singularity confinement test for ultradiscrete equations with parity variables , 2009 .

[10]  Takahashi,et al.  From soliton equations to integrable cellular automata through a limiting procedure. , 1996, Physical review letters.

[11]  Y. Sugiyama,et al.  SIMPLE AND EXACTLY SOLVABLE MODEL FOR QUEUE DYNAMICS , 1997 .

[12]  G. Mauri,et al.  Cellular automata in fuzzy backgrounds , 1997 .

[13]  Ihor Lubashevsky,et al.  Long-lived states in synchronized traffic flow: empirical prompt and dynamical trap model. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Nakayama,et al.  Dynamical model of traffic congestion and numerical simulation. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[15]  L. A. Pipes An Operational Analysis of Traffic Dynamics , 1953 .

[16]  Katsuhiro Nishinari,et al.  Analytical properties of ultradiscrete Burgers equation and rule-184 cellular automaton , 1998 .

[17]  G. P. Szegö,et al.  Stability theory of dynamical systems , 1970 .

[18]  Lily Elefteriadou An Introduction to Traffic Flow Theory , 2013 .

[19]  Daiheng Ni,et al.  Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques , 2015 .

[20]  T. Musha,et al.  Traffic Current Fluctuation and the Burgers Equation , 1978 .

[21]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .