Affiliation:
1. Charlotte Visualization Center, Department of Computer Science, The University of North Carolina at Charlotte, Charlotte, NC, USA
Abstract
Evacuation of large urban structures, such as campus buildings, arenas, or stadiums, is of prime interest to emergency responders and planners. Although there is a large body of work on evacuation algorithms and their application, most of these methods are impractical to use in real-world scenarios (nonreal-time, for instance) or have difficulty handling scenarios with dynamically changing conditions. Our overall goal in this work is toward developing computer visualizations and real-time visual analytic tools for evacuations of large groups of buildings, and in the long term, integrate this with the street networks in the surrounding areas. A key aspect of our system is to provide situational awareness and decision support to first responders and emergency planners. In our earlier work, we demonstrated an evacuation system that employed a modified variant of a heuristic-based evacuation algorithm, which (1) facilitated real-time complex user interaction with first responder teams, in response to information received during the emergency; (2) automatically supported visual reporting tools for spatial occupancy, temporal cues, and procedural recommendations; and (3) multi-scale building models, heuristic evacuation models, and unique graph manipulation techniques for producing near real-time situational awareness. The system was tested in collaboration with our campus police and safety personnel, via a tabletop exercise consisting of three different scenarios. In this work, we have redesigned the system to be able to handle larger groups of buildings, in order to move toward a full-campus evacuation system. We demonstrate an evacuation simulation involving 22 buildings in the University of North Carolina, Charlotte campus. Second, the implementation has been redesigned as a WebGL application, facilitating easy dissemination and use by stakeholders.
Subject
Computer Vision and Pattern Recognition
Cited by
6 articles.
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