Predicting Evacuation Capacity for Public Buildings

Pejman Kamkarian, Henry Hexmoor


This paper demonstrates a solution for analyzing public space evacuation rates. Evacuating from a public building in a reasonable amount of time is reliant upon how safe the space is in terms of achieving a minimum time to move people outside. In order to increase the safety of evacuation in public spaces, we employed the Bayesian Belief Network method. To have a better estimation pattern, we have to focus on important physical environmental features as well as crowd formation and specifications in a public space.


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Paper Citation

in Harvard Style

Kamkarian P. and Hexmoor H. (2013). Predicting Evacuation Capacity for Public Buildings . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8565-39-6, pages 433-440. DOI: 10.5220/0004217704330440

in Bibtex Style

author={Pejman Kamkarian and Henry Hexmoor},
title={Predicting Evacuation Capacity for Public Buildings},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},

in EndNote Style

JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Predicting Evacuation Capacity for Public Buildings
SN - 978-989-8565-39-6
AU - Kamkarian P.
AU - Hexmoor H.
PY - 2013
SP - 433
EP - 440
DO - 10.5220/0004217704330440