Agent-based Crowd Simulation Research Articles

Generating freestyle group formations in agent-based crowd simulations.

Few crowd simulation algorithms take collective group features such as group formations into consideration. Recent approaches often manually specify hard constraints such as predefined keyframe agent formations and interpolate them during the simulation. A proposed interactive, scalable framework generates freestyle group formations and transitions via natural and flexible sketching interaction. It automatically computes a plausible agent distribution in the target formation and agent correspondences between keyframes. In addition, two-level formation trajectory control lets users intuitively guide agents' transition paths from the initial formation to the target formation. In experiments, the framework efficiently generated formations on the fly while providing sufficiently flexible control to users.

Analysis of an efficient rule-based motion planning system for simulating human crowds

This paper proposes a rule-based motion planning system for agent-based crowd simulation, consisting of sets of rules for both collision avoidance and collision response. In order to avoid an oncoming collision, a set of rules for velocity sampling and evaluation is proposed, which aims to choose a velocity with an expected time to collision larger than a predefined threshold. In order to improve the efficiency over existing methods, the sampling procedure terminates upon finding an appropriate velocity. Moreover, the proposed motion planning system does not guarantee a collision-free movement. In case of collision, another set of rules is also defined to direct the agent to make a corresponding response. The experiment results show that the proposed approach can be applied in different scenarios, while making the simulation execution efficient.

Modeling group structures in pedestrian crowd simulation

Grouping is a common phenomenon in pedestrian crowds and plays important roles in affecting crowd behavior. Group modeling is still an open challenging problem and has not been incorporated by existing crowd simulation models. Motivated by the need of group modeling for crowd behavior simulation, this paper presents a unified and well-defined framework for modeling the structure aspect of different groups in pedestrian crowds. Both intra-group structure and inter-group relationships are considered and their effects on the crowd behavior are modeled. Based on this framework, an agent-based crowd simulation system is developed and crowd behavior simulations using two different group structures are presented. The simulation results show that the developed framework allows different group structures to be easily modeled. Besides, different group sizes, intra-group structures and inter-group relationships can have significant impacts on crowd behaviors.

Layered Intelligence for Agent-based Crowd Simulation

We adapt a scalable layered intelligence technique from the game industry, for agent-based crowd simulation. We extend this approach for planned movements, pursuance of assignable goals, and avoidance of dynamically introduced obstacles/threats as well as congestions, while keeping the system scalable with the number of agents. We demonstrate the various behaviors in hall-evacuation scenarios, and experimentally establish the scalability of the frame rates with increasing numbers of agents.