Hierarchical planning-based crowd formation - Liu, Na (2021)
Team formation with realistic crowd simulation behavior is a challenge in computer graphics, multiagent control, and social simulation. In this study, we propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behavior, and action-control planning. In cooperative-task planning, we improve the grid potential field to achieve global path planning for a team. In coordinated-behavior planning, we propose a time–space table to arrange behavior scheduling for a movement. In action-control planning, we combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages. (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behavior only with the local information of his neighbor; the global intelligence of the group emerges from these local interactions. (3) The time–space table fully utilizes three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense, employing quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks.