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.
Muccini, H., & Tourchi Moghaddam, M. (2017). A cyber-physical space operational approach for crowd evacuation handling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10479 LNCS, pp. 81–95). Springer Verlag. https://doi.org/10.1007/978-3-319-65948-0_6