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

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.