Development and Visualization of Cellular Automata Models for Predicting Heterogeneous Traffic Flows

The paper deals with the creation of mathematical and software tools for modeling heterogeneous traffic flows based on the cellular automata theory. Different types of vehicles, namely, passenger cars, vans, buses or trucks, are distinguished by length and maximum velocity. Generalizations of the Nagel–Schreckenberg and Helbing–Schreckenberg models for the heterogeneous case are developed using multi-cellular representation of vehicles. The models are implemented in the original program environment TrafficFlowViz3D enabling dynamic visualization of simulation results. The visualization system allows constructing lattices with cells of various shapes to study traffic on roads with complex geometry. A multi-lane version of the generalized Nagel–Schreckenberg model on regular hexagonal cells is proposed and completed by the algorithm of movement to a destination. Some test predictions are analyzed to verify the developed models and software.