A review of cellular automata models for crowd evacuation

Yang Li, Maoyin Chen, Zhan Dou, Xiaoping Zheng, Yuan Cheng and Ahmed Mebarki

Physica A: Statistical Mechanics and its Applications, 2019, vol. 526, issue C

Abstract: With the increasing of risk potential in crowded places, evacuation management becomes practically important to ensure the safety of crowds. The studies of crowd evacuation in normal or emergency situations have become a hot topic. Due to the distinct advantages of high efficiency, strong scalability and simple implementation, cellular automata models (CA) have become one of the most widely-used models for evacuation. However, the practical requirements of evacuation propose some important challenges for CA models, for example, to accurately characterize both position and velocity of individuals, to depict environments and accidents, and to describe human behaviors. In the last 20 years, there are many studies aiming at resolving the above challenges. Starting from the challenges mentioned above, this paper tries to give a review of CA models, specially used for crowd evacuation. Firstly, we give an overview of CA models for evacuation, and put forward research paradigm, modeling framework and classification of CA models. The models used for evacuation are classified into three kinds of categories, i.e. lattice gas model, floor field model, and other field-based models. The last category includes potential field model, electrostatic-induced potential field model, cost potential field model, etc. Then, three main challenges of CA models for evacuation are presented, and the improvements for each type of challenge are summarized. Typical simulation scenarios and research issues are further proposed. Finally, the advantages and disadvantages of CA models are illustrated from the aspects of implementation, performance, scalability, accuracy and applicability.

Keywords: Cellular automata; Lattice gas model; Floor field model; Crowd evacuation; Pedestrian dynamic; Evacuation models (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (26)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119303528
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119303528

DOI: 10.1016/j.physa.2019.03.117

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().