Crowd Dynamic

Crowd dynamics research focuses on understanding and predicting the collective behavior of groups of people, aiming to improve safety and efficiency in various settings. Current research employs diverse approaches, including agent-based modeling, deep reinforcement learning, and physics-informed machine learning, often incorporating social force models and analyzing data from sources like location-based social networks and drone footage to detect anomalies and optimize crowd flow. These advancements have significant implications for urban planning, emergency response, robotics, and security, enabling better design of infrastructure and improved safety protocols in high-density environments.