The thesis’ purpose is the simulation of motorcycle platoon behavior on mountain roads. The act of driving particularly motorcycles offer a sense of gratification, tranquility and freedom. Many enthusiasts gravitate towards mountainous terrain where winding roads offer both excitement and respite amidst breathtaking panoramas. The increasing number of motorcyclists makes it an interesting topic for research and behavioral simulation on road conditions. Various methodologies have been used to simulate traffic, among which cellular automata stand out for their capacity to capture emergent properties within complex systems. In line with this endeavor the thesis aimed to construct a cellular automata which would simulate such scenarios. The envisioned model encapsulates the nuanced dynamics of motorcycle platoons navigating varied terrains, encompassing braking, accelerating, overtaking and back to lane behaviors. The aim also encompasses an architecture that is easily adaptable for different road conditions by the use of standard format GPX files and retrieving the extra information from the internet using various APIs. The project also entails several key objectives, firstly a comprehensive review of contemporary methodologies for visually intuitive representation of motor traffic simulations with a focus on high-resolution modeling and integration in real-time data and advanced technologies. A rigorous evaluation of the model’s performance vis-à-vis real life traffic dynamics using iterative process refinement and parameter optimization ensures a continuous improvement in the pursuit of enhanced fidelity to real-world phenomena.