Lane merging is a fundamental aspect of modern road networks, occurring at locations such as highway on-ramps, work zones, and lane reductions due to obstacles or construction. The need for lane merging arises due to various practical and operational constraints, ensuring efficient traffic movement, safety, and optimal utilization of road infrastructure. In this study, we develop a cellular automata (CA) based merging model to analyze the behavior of vehicles transitioning from a two-lane road into a single lane. The model extends the Nagel-Schreckenberg (NaSch) framework, incorporating lane changing rules and merging constraints to capture realistic driving behavior. This paper proposes microscopic and macroscopic lane merging models using cellular automata based on the vehicle velocity, position, and waiting time. Our simulation analysis concludes that the cooperative merging reduced 37% congestion by improving 50% of throughput.