Modeling Train Traffic Flow Using Cellular Automata

This paper is concerned with increasing the safety of railway transportation, using Cellular Automata (CA). Train traffic flow considers as a spatial and dynamic complex process. In the proposed algorithm, the dynamic system was divided to discrete cells in space and time, each in one of a finite number of states. For each cell, a set of cells called its neighborhood is defined. An initial state is selected by assigning a state for each cell. The new state of each cell was determined in terms of the current state of the cell, the states of the cells in its neighborhood and a transition rule. The results showed the efficiency of the proposed method to model train traffic flow in the railway transportation system.