Abstract

Recently, traffic problems have attracted considerable attention Numerical simulations, hydrodynamics models, and queueing theory are a few of the basic theoretical tools used to describe car traffic on highways Computationally, Cellular Automaton models are simple and flexible and are increasingly used in simulations of complex systems, providing considerable insight on traffic behaviour. A particular strength of these models is fast "minimal" microscopic simulation, which nevertheless can reproduce important macroscopic features. This methodology requires streets to be divided into sites (cells), with sites linked into road segments and forming networks, punctuated by junctions, traffic signals and so on. Car movements are represented by “jumps”, where each jump represents the current car speed. Much previous work has concentrated on flow o f cars under highway conditions, but less effort has been concerned with urban networks and the constraints, which apply in this context. The research reported here, uses Cellular Automaton methodology to examine traffic patterns in urban and inter-urban areas. A three state deterministic Cellular Automata Model is defined for the dynamic process and networks of various sizes are investigated, with all nodes controlled and diverse traffic conditions considered at each intersection. Both transient movements of cars through the network and temporary lost to flow , through off-street parking, are examined for impact on traffic parameters. A stochastic feeding mechanism, in which car arrivals follow a Poisson process, has been implemented throughout the simulation ’for different arrival rates Lane-changing rules for simulation of two-lane traffic are also discussed and, finally, a Stochastic Cellular Automata Model for inter-urban areas is presented. Key features of traffic behaviour under the various network conditions are analysed and comparisons with highway flow. Suggestions and future improvements on model realism are also given.