Abstract
Crowded public venues are significantly under risks and uncertainties caused by fire and overcrowding hazards. For this purpose, Situational Awareness (SiA) -that is a mechanism to know what is going on around- can facilitate the automatic (or human involved) critical decision making and executing processes. Considering the dynamic and uncertain essence of crowd and hazard behavior in an emergency, executing the optimum evacuation plan is highly complex and needs strong models. In this paper, taking in input a model of the Cyber-Physical Space under SiA monitoring, we define an architectural-map-based Dynamic Bayesian Network (DBN) to describe and predict crowd and hazard behavior. Then, in order to minimize the total evacuation time, the authors present a quickest flow model for consecutive time intervals. Overall, the paper shows the importance of hazard quiddity, and crowd behavior on the evacuation efficiency in emergency situations. The approach is demonstrated through a small (but concrete) running example.
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Acknowledgment
We acknowledge that the work is a part of cyber-physical Situational Awareness project with the UFFIZI galleries, Florence, Italy. In addition, we would like to thank our colleagues Mohammad Sharaf and Fabrizio Rossi for their valuable comments and suggestions to improve this paper
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Muccini, H., Tourchi Moghaddam, M. (2017). A Cyber-Physical Space Operational Approach for Crowd Evacuation Handling. In: Romanovsky, A., Troubitsyna, E. (eds) Software Engineering for Resilient Systems. SERENE 2017. Lecture Notes in Computer Science(), vol 10479. Springer, Cham. https://doi.org/10.1007/978-3-319-65948-0_6
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DOI: https://doi.org/10.1007/978-3-319-65948-0_6
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