A Realistic Approach to the Traffic Flow Behaviors by Cellular Automata Models

Due to steady increase in traffic density on roads, the traffic phenomena become non-linear and complex. For the traffic engineers and policy makers to regularize the traffic flow, we need to explore the traffic behavior in detail. In the current paper, the usefulness of CA to traffic flow modeling has been determined. Also, some of the existing CA models have been extended to study characteristics of traffic flow that have not been captured either by using analytic models or by existing simulation techniques. We discuss CA models such as Standard Nagal model, Rule 184, Deterministic CA model, Stochastic CA model and Velocity Dependent Randomized CA model. We provide applications of Nagal model for urban streets and for freeway. Higher moments of traffic flow have been examined and their effect on overall traffic performance has been evaluated. We also examine the relationship between lane changing behavior and flow performance for a two-lane system. The ability of this modeling paradigm to capture the most important features of the traffic flow phenomena is established from the simulation results obtained.