This study presents an agent-based modeling approach to analyze crowd movement and evacuation performance in confined spaces. The model simulates individual agents navigating toward a single exit while avoiding collisions under varying density conditions. Three evacuation scenarios were evaluated, consisting of 20, 40, and 60 agents within a confined environment measuring 10 × 8 meters. The simulation was executed using a discrete time step of 0.1 seconds, and performance was assessed based on evacuation time and collision frequency. The results indicate that increasing crowd density significantly affects movement efficiency. The 20-agent scenario achieved an average evacuation time of 6.42 seconds with 95.33 collision events. When the number of agents increased to 40, the evacuation time rose to 6.90 seconds with 391.77 collisions. The highest density scenario, consisting of 60 agents, produced an average evacuation time of 7.08 seconds and 890.73 collision events. These findings demonstrate that higher density levels lead to a disproportionate increase in interaction intensity and congestion, resulting in reduced evacuation efficiency. The study confirms that agent-based modeling is an effective approach for analyzing crowd dynamics in confined environments and provides a reproducible framework for evaluating evacuation performance under varying density conditions.
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