miSFM: On combination of Mutual Information and Social Force Model towards simulating crowd evacuation
- Resource Type
- Authors
- Mingxuan Luo; Yunpeng Wu; Yangdong Ye; Hao Jiang; Mingliang Xu; Pei Lv
- Source
- Neurocomputing. 168:529-537
- Subject
- Computer science
business.industry
Cognitive Neuroscience
Mutual information
Machine learning
computer.software_genre
Computer Science Applications
Crowd evacuation
Artificial Intelligence
Social force model
Crowd simulation
Artificial intelligence
business
computer
Simulation
- Language
- ISSN
- 0925-2312
In this paper we propose a novel technique termed miSFM for the simulation of crowd evacuation. miSFM take merits of both Mutual Information (MI) and Social Force Model (SFM). More specifically, MI of interacting agents is adopted to determine the level of order within a crowd during an evacuation. In such a way, SFM can be improved by adapting the forces involved at microscopic level between mutually interacting agents. The key innovation lies in highlighting how the dynamic adjustment of SFM parameters reveals much more realistic crowd movements for the evacuation simulation. Extensive experiments over several alternative and state-of-the-art works demonstrate the advantages of the proposed algorithm.