Improving the Performance of Partitioning Methods for Crowd Simulations

Simulating the realistic behavior of large crowds of autonomous agents is still a challenge for the computer graphics community. In order to handle large crowds, some scalable architectures have been proposed. Nevertheless, the effective use of distributed systems requires the use of partitioning methods that can properly assign different sets of agents to the existing distributed resources. In this paper, we propose the improvement of the partitioning method for distributed crowd simulations by using irregular shape regions. Concretely, we propose the partition of the virtual world using convex hulls. The performance evaluation results show that the convex Hull method outperforms the rest of the considered methods in terms of both fitness function values and execution times, regardless of the movement pattern followed by the agents. These results show that the shape of the regions in the partition can improve the performance of the partitioning method, rather than the heuristic method used.