Eric Daudé, Kevin Chapuis, Clément Caron, Alexis Drogoul, Benoit Gaudou, Sebastien Rey-Coyrehourq, et al. (2019). ESCAPE: Exploring by Simulation Cities Awareness on Population Evacuation. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Partial or total horizontal evacuation of populations in urban areas is an important protection measure against a natural or technological risk. However, casualties during massive displacement in a context of stress and in a potentially degraded environment may be high due to non-compliance with instructions, accidents, traffic jams, incivilities, lack of preparation of civil security or increased exposure to hazards. Working in evacuation plans is therefore fundamental in avoiding casualties caused by improvisation and in promoting self-evacuation whenever possible. Since it is impossible to re-create the conditions of a crisis on the ground to assess such evacuation plans, there is a need for realistic models in order to evaluate them using simulations. In this paper, we present the ESCAPE software framework that helps in the development of such plans and testing them. In particular, ESCAPE, which uses the GAMA open-source platform as a core component, provides an agent-based simulation tool that supports simulation of the evacuation of a city's population at fine temporal and Geographical scales. The framework was developed such that it works for a wide range of scenarios, both in terms of hazards, geographical configurations, individual behaviors and crisis management. In order to show its adaptability, two applications are presented, one concerning the evacuation of the city of Rouen (France) in the context of a technological hazard and the other pertaining to the evacuation of the district of Hanoi (Vietnam) in the event of floods.
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Leon J.M. Rothkrantz, & Zhenke Yang. (2009). Crowd control by multiple cameras. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: One of the goals of the crowd control project at Delft University of Technology is to detect and track people during a crisis event, classify their behavior and assess what is happening. The assumption is that the crisis area is observed by multiple cameras (fixed or mobile). The cameras sense the environment and extract features such as the amount of motion. These features are the input to a Bayesian network with nodes corresponding to situations such as terroristic attack, fire, and explosion. Given the probabilities of the observed features, by reasoning, the likelihood of the possible situations can be computed. A prototype was tested in a train compartment and its environment. Forty scenarios, performed by actors, were recorded. From the recordings the conditional probabilities have been computed. The scenarios are designed as scripts which proved to be a good methodology. The models, experiments and results will be presented in the paper.
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