Interactive analysis and visualization of situationally aware building evacuations

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.

[1]  William Ribarsky,et al.  Semi-automated processing and routing within indoor structures for emergency response applications , 2010, Defense + Commercial Sensing.

[2]  David S. Ebert,et al.  Visual Analytics on Mobile Devices for Emergency Response , 2007, 2007 IEEE Symposium on Visual Analytics Science and Technology.

[3]  Kristin A. Cook,et al.  Illuminating the Path: The Research and Development Agenda for Visual Analytics , 2005 .

[4]  Siuming Lo,et al.  An Artificial Neural-network Based Predictive Model for Pre-evacuation Human Response in Domestic Building Fire , 2009 .

[5]  Jim X. Chen,et al.  OpenGL Shading Language , 2009 .

[6]  Cje Castle,et al.  Ucl Centre for Advanced Spatial Analysis Principles and Concepts of Agent-based Modelling for Developing Geospatial Simulations Principles and Concepts of Agent-based Modelling for Developing Geospatial Simulations 1.2.4.2: Guidelines for Choosing a Simulation / Modelling System .................24 , 2022 .

[7]  Chris Weaver,et al.  RimSim Response Hospital Evacuation: Improving Situation Awareness and Insight through Serious Games Play and Analysis , 2011, Int. J. Inf. Syst. Crisis Response Manag..

[8]  Ngai Ming Kwok,et al.  Swarm Interaction-Based Simulation of Occupant Evacuation , 2008, 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application.

[9]  Randi J. Rost OpenGL shading language , 2004 .

[10]  Gennady L. Andrienko,et al.  Interactive visual interfaces for evacuation planning , 2008, AVI '08.

[11]  Shashi Shekhar,et al.  Contraflow Transportation Network Reconfiguration for Evacuation Route Planning , 2008, IEEE Transactions on Knowledge and Data Engineering.

[12]  William Ribarsky,et al.  Visual analysis of situationally aware building evacuations , 2013, Electronic Imaging.

[13]  Christopher Richard Wren,et al.  Visualizing the History of Living Spaces , 2007, IEEE Transactions on Visualization and Computer Graphics.

[14]  Atsushi Takizawa,et al.  An efficient algorithm for the evacuation problem in a certain class of networks with uniform path-lengths , 2009, Discret. Appl. Math..

[15]  Shashi Shekhar,et al.  Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results , 2005, SSTD.

[16]  Shashi Shekhar,et al.  Processing in-route nearest neighbor queries: a comparison of alternative approaches , 2003, GIS '03.

[17]  David S. Ebert,et al.  Mobile Analytics for Emergency Response and Training , 2008, Inf. Vis..

[18]  Dinesh Manocha,et al.  ClearPath: highly parallel collision avoidance for multi-agent simulation , 2009, SCA '09.

[19]  Bianchi Serique Meiguins,et al.  Multiple coordinated views supporting visual analytics , 2009, VAKD '09.