This study introduces a novel crowd simulation framework tailored for special natural environments, such as earthquakes, landslides, and hunting scenarios. The framework integrates continuous dynamics with agent-based mechanisms to model diverse biological cluster interactions effectively. By combining global path planning and local collision detection, it enhances crowd-driven interactions through innovative strategies for path finding, motion, and crowd management. A lightweight 3D reconstruction approach ensures a balance between large-scale simulations, high-fidelity scenarios, and computational efficiency. This framework allows each agent to maintain individual initiative and behavioral diversity, making it highly suitable for large-scale simulations. The proposed model can simulate crowd behavior realistically across various natural scenarios and adapt seamlessly to different environments, offering a robust solution for crowd simulation.
Zou et al. (Sun,) studied this question.