Research of Congestions in Urban Transport Network Using Cellular Automation Model

Abstract The growing demand for transport and communication services leads to more and more important, traffic related and closely associated problems, especially in the city centre, such as traffic congestion, air pollution, noise and some others. When modelling traffic flows in the Kaunas city centre, the simulation models of crossroads were created based on the principle of cellular automaton model, taking into consideration such relevant traffic indicators as the average speed of traffic flow in different streets, traffic intensity, congestions and distributed flows. Operation of cellular automaton model is associated with the improved approach of further vehicle model. Modelling of microscopic traffic flows is based on the brake light–cellular automaton (BL–CA) model. Random functions were made discreet and autocorrelation values of these functions were calculated in this work. Fundamental macroscopic traffic characteristics were obtained. Numerical dependences of the average traffic speed and traffi...

[1]  Bor-Shong Liu Association of intersection approach speed with driver characteristics, vehicle type and traffic conditions comparing urban and suburban areas. , 2007, Accident; analysis and prevention.

[2]  Ivica Stančerić,et al.  Methods for Setting Road Vehicle Movement Trajectories , 2008 .

[3]  Jadranka Joviæ,et al.  Traffic and Environmental Street Network Modelling: Belgrade Case Study , 2010 .

[4]  Alfredas Laurinavičius,et al.  Investigation into traffic flows on high intensity streets of Vilnius city , 2010 .

[5]  P Nelson,et al.  A critical comparison of the kinematic-wave model with observation data , 2005 .

[6]  M. E. Lárraga,et al.  Cellular automata for one-lane traffic flow modeling , 2005 .

[7]  Takashi Nagatani,et al.  Chaos and Dynamical Transition of a Single Vehicle Induced by Traffic Light and Speedup , 2005 .

[8]  R. Barlovic,et al.  Traffic Jams: Cluster Formation in Low-Dimensional Cellular Automata Models for Highway and City Traffic , 2003 .

[9]  R. Sivanandan,et al.  Evaluation of left turn channelization at a signalized intersection under heterogeneous traffic conditions , 2008 .

[10]  Kornelija Ratkeviciute,et al.  Implementation of Experimental Researchin Road Traffic: Тheory and Practice , 2008 .

[11]  W WEN,et al.  A dynamic and automatic traffic light control expert system for solving the road congestion problem , 2008, Expert Syst. Appl..

[12]  James B. Martin,et al.  The Jammed Phase of the Biham-Middleton-Levine Traffic Model , 2005, math/0504001.

[13]  Erik T. Verhoef,et al.  A behavioural model of traffic congestion: Endogenizing speed choice, traffic safety and time losses , 2004 .

[14]  Michael Carreno,et al.  Importance of Virtual Trips for Transport Infrastructure Planning , 2009 .

[15]  R. Tweedie,et al.  Locally contracting iterated functions and stability of Markov chains , 2001, Journal of Applied Probability.

[16]  B. Kerner The Physics of Traffic: Empirical Freeway Pattern Features, Engineering Applications, and Theory , 2004 .

[17]  Takashi Nagatani,et al.  Control of vehicular traffic through a sequence of traffic lights positioned with disordered interval , 2006 .

[18]  Luis Alvarez-Icaza,et al.  Cellular automaton model for traffic flow based on safe driving policies and human reactions , 2010 .

[19]  Pelin Çalişkanelli,et al.  Comparison of different capacity models for traffic circles , 2009 .

[20]  Gianluca Dell’Acqua,et al.  Speed Factors on Low-Volume Roads for Horizontal Curves and Tangents , 2010 .

[21]  Ahmed Boumediene,et al.  Saturation Flow versus Green Time at Two-Stage Signal Controlled Intersections , 2009 .

[22]  Ludger Santen,et al.  Human behavior as origin of traffic phases. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.