Efficient evacuation in a multi-exit environment: an agent-based decision support model
Kashif Zia,
Dinesh Kumar Saini and
Arshad Muhammad
International Journal of Information and Decision Sciences, 2019, vol. 11, issue 4, 355-375
Abstract:
A majority of research work carried out in crowd evacuation rely on simulation due to non-availability of real and realistic trial data. In this paper, an agent-based simulation study of an evacuating crowd is presented. The model is based on the microscopic behavioural rules formulated through small-scale empirical evidence in conjunction with crowd behavioural theories. In particular, the study focuses on the possibility of efficient evacuation from the environment with limited perceptions. Extending Moore's neighbourhood model, local congestion avoidance mechanism capable of detecting the relative displacement and orientation of the all the individuals in its neighbourhood is considered. Other strategies based on exit capacity and exit population are also modelled and tested. A probabilistic exit selection strategy is also designed that considers a sensitivity of an exit as a deciding factor. The simulation results show that the enhanced exit selection strategies make the proposed system more robust and increase the evacuation efficiency substantially.
Keywords: crowd evacuation; decision support model; multi-exit efficiency; agent-based modelling; Netlogo simulation. (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=103352 (text/html)
Access to full text is restricted to subscribers.
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:ids:ijidsc:v:11:y:2019:i:4:p:355-375
Access Statistics for this article
More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().