Microscopic crowd models are computational and mathematical frameworks that simulate pedestrian dynamics by representing each individual as a distinct agent with its own state, decision-making rules, and interactions with neighbors and the environment, as opposed to aggregate continuum approaches. They matter because they enable fine-grained analysis of emergent collective behaviors — such as lane formation, clogging, and flow disruption — from individual-level mechanics and cognition, making them essential for safety planning, architectural design, and behavioral research. Key variants include social force models, Follow-the-Leader models, granular interaction models, cellular automata, and agent-based models with explicit decisional layers such as ANDA, which decouple locomotion mechanics from higher-level anticipatory or cognitive processes like smartphone distraction.
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