Simulation of Traffic Flow Using Three Cellular Automata Models

In this project, we investigate three distinct cellular automata programs for simulating traffic flow dynamics. These implementations utilize Rule 184 for basic vehicle movement and incorporate stochastic lane-changing mechanisms for dual-vehicle types (typically representing cars and trucks). The simulation framework accounts for vehicle length as a critical parameter in traffic modeling. Our implementation addresses varying vehicle dimensions through customized cell occupation rules, where longer vehicles occupy multiple consecutive cells in the automata grid. We observe that different cellular automata approaches produce diverse traffic flow patterns, demonstrating the importance of methodological variations in traffic simulation studies. The Rule 184 component governs forward movement based on neighbor states, while the lane-changing module employs probability thresholds to determine switching decisions. Through our research, we have identified several noteworthy results and proposed potential enhancements for simulation methodology, including optimized update sequences and improved boundary handling. We believe these findings will contribute positively to future traffic flow research and computational modeling advancements.