Guidance path scheduling using particle swarm optimization in crowd simulation

Sai-Keung Wong*, Pao Kun Tang, Fu Shun Li, Zong Min Wang, Shih Ting Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In this paper, we propose a method for using particle swarm optimization (PSO) to compute optimal guidance paths for various crowd densities in an agent-based crowd simulation. The inputs of our system are guidance paths that provide hints for the movement directions of agents. Input guidance paths may not be located correctly (e.g., leading to congestion or high traveling cost); therefore, our method adjusts the guidance paths by using PSO. We consider several factors for evaluating the quality of a guidance path, including the average traveling time and interaction distance between agents. We apply our method in several examples. Experimental results show that our method can compute adaptive guidance paths for various crowd densities. Our system can simulate organized crowds that move in directions specified by the guidance paths.

Original languageEnglish
Pages (from-to)387-395
Number of pages9
JournalComputer Animation and Virtual Worlds
Volume26
Issue number3-4
DOIs
StatePublished - 1 May 2015

Keywords

  • crowd simulation
  • guidance paths
  • particle swarm optimization (PSO)

Fingerprint Dive into the research topics of 'Guidance path scheduling using particle swarm optimization in crowd simulation'. Together they form a unique fingerprint.

Cite this