An extended floor field model based on regular hexagonal cells for pedestrian simulation
Biao Leng,
Jianyuan Wang,
Wenyuan Zhao and
Zhang Xiong
Physica A: Statistical Mechanics and its Applications, 2014, vol. 402, issue C, 119-133
Abstract:
Recently the floor field (FF) model has been widely used to simulate pedestrian dynamics. This paper presents an extended FF model based on regular hexagonal cells to simulate pedestrian dynamics in a corridor scenario. In this model, the elements in FF model are redefined. Scenarios are discretized into regular hexagonal cells rather than squared ones. Pedestrian repulsion is adopted instead of dynamic floor field. Velocity level is proposed to describe pedestrian movements. Simulations in a corridor scenario are conducted, and the basic property of the new model is discussed deeply, including the parametric effects on flow and wait distribution of pedestrian. The fundamental diagrams of pedestrian dynamics are used to verify the model.
Keywords: Cellular automata; Regular hexagonal cell; Pedestrian dynamics; Floor field model; Corridor scenario (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S037843711400051X
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:402:y:2014:i:c:p:119-133
DOI: 10.1016/j.physa.2014.01.039
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 ().