A new stochastic cellular automata model for traffic flow simulation with drivers' behavior prediction

In this work, we introduce a novel, flexible and robust traffic flow cellular automata model. Our proposal includes two important stages that make possible the consideration of different profiles of drivers' behavior in a simple way. We first consider the motion expectation of vehicles that are in front of each driver. Secondly, we define how a specific vehicle decides to get around, considering the foreground traffic configuration. Our model uses stochastic rules for both situations, using the Probability Density Function of the Beta Distribution to model three drivers' behavior, adjusting different parameters of the Beta Distribution for each one.