Incorporating Urban Spatial Structure in Agent-Based Urban Simulations

Abstract

The spatial equilibrium approach to urban systems has been criticized for lack of geographic details and realism. Agent-based urban simulation takes a bottom-up approach as an alternative perspective on urban modeling. The architecture of many urban simulation frameworks, though built upon geographical features, does not necessarily provide a structural understanding of urban systems. Structural understanding of urban systems requires taking into account all geographic, social, economic components, and their interrelationships in a unified framework. Urban spatial structure models integrate two major components: Socio-economic behavior and landscape. Incorporating urban spatial structure, therefore, provides simulation of an urban system with solid behavioral foundation and socio-economic intuition. From a public policy perspective, explicit urban spatial structure can help to identify more general policy implications out of simulation results, for example, on land use, transportation, housing, and other aspects of urban life. In this chapter, necessary components of agent-based urban simulations are discussed, with an agent-based modeling (ABM) simulation on transportation cost and congestion effects developed to illustrate the role that urban spatial structure models can play in urban simulations.