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SWARMFEST 2007 1
An Agent-Based Simulation For Emergency Response Management
Timothy Schoenharl, R. Ryan McCune, Greg Madey
of the University of Notre Dame du Lac
This material is based upon work supported by the National Science Foundation under Grant No. CNS-0540348
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Wireless Phone-based Emergency Response System
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Purpose of Simulation Limited knowledge
of events by emergency managers
Understand crisis development
Develop strategy for better response
http://www.nyc.gov/html/fdny/gif/photo_unit/fires/122602/122602_157_truck.jpg
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Overview of Simulation Agent-based simulations model
behavior of city’s population Simulate normal and crisis behavior Output call activity and agent location
on GIS map
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Implementation RePast 3.1 for Java
Colt High Performance Scientific Library
Geotools OpenMap
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Implementation Pattern Oriented Design Singleton Class
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The Agent Each agent represents pedestrian Randomly assigned initial position
inside of Voronoi Cell Call activity based on empirical
distributions Movement determined by given
scenario
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The Environment
Real city created with GIS files Cell phone tower
locations Roads, Water, Political Boundaries
Voronoi cells built around cell phone towers
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Simulation Scenarios Simulate Regular behavior
Move and return Location and call activity based on empirical data
Crisis behavior Flee – Run from a point Bounded Flee – Run a distance from a point
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Validation Movement Model
Face Value Call Activity
Empirical vs. Simulated results plotted
Kolmogorov-Smirnov test
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Validation cont.
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Interface RePast GUI OpenMap Display Voronoi cell color changes with agent
containment Call Activity Graph
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Screenshot of Repast GUI
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Runtime Performance Runtime vs. Graphical Output
500 Agents Move and Return Model Distribution-Based Calling Activity
GIS Agent Location Snapshot Time (s)
No No No 240
Yes No No 354
Yes Yes No 363
Yes Yes Yes 35200
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Runtime Performance Runtime vs. Number of Agents
Linear Scaling demonstrates excellent runtime characteristics
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Summary Agent-based model to simulate crisis
behavior Movement dependent on behavior
model and outputted to GIS map Calling Activity based on empirical data Designed for WIPER System
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Future Work Implement more crisis scenarios Study of aggregate patterns More realistic agent paths
Road and Highway use Vary Speed Traffic Jam Scenarios
Water Social network structure
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Questions?