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An agent-based parallel geo-simulation of urban mobility during city-scale evacuation

An agent-based parallel geo-simulation of urban mobility during city-scale evacuation
An agent-based parallel geo-simulation of urban mobility during city-scale evacuation
The simulation of urban mobility is a modeling challenge due to the complexity and scale. The complexity in modeling a social agent is due to three reasons: (i) the agent is behaviorally complex itself due to several interrelated/overlapping modeling aspects; (ii) the setting in which a social agent operates usually demands a multi-resolution approach; and (iii) the consideration of real spatial and population data is the underpinning that has to be realized. In this paper, we propose an agent-based parallel geo-simulation framework of urban mobility based on necessary modeling aspects. The aspect-oriented modeling paradigm relates the models vertically as well as horizontally and highlights the situations requiring multi-resolution interfacing. The framework takes into consideration the importance of technological footprints embedded with social behavior along with essential space and mobility features keeping focus on the importance of the city-scale scenario. We have used a real, high-quality raster map of a medium-sized city in central Europe converting it into a cellular automata (CA). The fine-grained CA readily supports pedestrian mobility and can easily be extended to support other mobility modes. The urban mobility simulation is performed on a real parallel and distributed hardware platform using a CA compatible software platform. Considering city-wide mobility in an emergency scenario, an analysis of the simulation efficiency and agent behavioral response is presented.
0037-5497
1184-1214
Zia, Kashif
d79cc3b9-7062-4ffc-8d62-626a677d1e35
Farrahi, Katayoun
bc848b9c-fc32-475c-b241-f6ade8babacb
Riener, Andreas
06dfa637-8ae9-4bff-bff3-6f6843dd630a
Ferscha, Alois
b8b048c0-8980-4519-8001-280074f0e7bd
Zia, Kashif
d79cc3b9-7062-4ffc-8d62-626a677d1e35
Farrahi, Katayoun
bc848b9c-fc32-475c-b241-f6ade8babacb
Riener, Andreas
06dfa637-8ae9-4bff-bff3-6f6843dd630a
Ferscha, Alois
b8b048c0-8980-4519-8001-280074f0e7bd

Zia, Kashif, Farrahi, Katayoun, Riener, Andreas and Ferscha, Alois (2013) An agent-based parallel geo-simulation of urban mobility during city-scale evacuation. Simulation, 89 (10), 1184-1214. (doi:10.1177/0037549713485468).

Record type: Article

Abstract

The simulation of urban mobility is a modeling challenge due to the complexity and scale. The complexity in modeling a social agent is due to three reasons: (i) the agent is behaviorally complex itself due to several interrelated/overlapping modeling aspects; (ii) the setting in which a social agent operates usually demands a multi-resolution approach; and (iii) the consideration of real spatial and population data is the underpinning that has to be realized. In this paper, we propose an agent-based parallel geo-simulation framework of urban mobility based on necessary modeling aspects. The aspect-oriented modeling paradigm relates the models vertically as well as horizontally and highlights the situations requiring multi-resolution interfacing. The framework takes into consideration the importance of technological footprints embedded with social behavior along with essential space and mobility features keeping focus on the importance of the city-scale scenario. We have used a real, high-quality raster map of a medium-sized city in central Europe converting it into a cellular automata (CA). The fine-grained CA readily supports pedestrian mobility and can easily be extended to support other mobility modes. The urban mobility simulation is performed on a real parallel and distributed hardware platform using a CA compatible software platform. Considering city-wide mobility in an emergency scenario, an analysis of the simulation efficiency and agent behavioral response is presented.

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e-pub ahead of print date: 13 May 2013
Published date: October 2013

Identifiers

Local EPrints ID: 419794
URI: http://eprints.soton.ac.uk/id/eprint/419794
ISSN: 0037-5497
PURE UUID: aa8a7599-e703-4349-99d7-d86fc73cb8fe

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Date deposited: 20 Apr 2018 16:30
Last modified: 13 Mar 2019 18:37

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