Agent-Based Simulation of Household Residential Relocation and Decision-Making Support of Downtown Revitalization

AbstractResidential relocation is a traditional research concern in urban study area, in this chapter we will focus on introducing how to develop an Agent-Based Model (ABM) to simulate household residential relocation affected by a local residential policy regarding to downtown revitalization in Japanese local city. Different from conventional residential relocation model developed on utility theory, in this work the agents’ behaviors on residential location choices are supposed to be affected by argued planning policy. The policy effects will be simulated through reflecting households’ policy attitude sharing in whole city and neighborhoods. We define it as an interaction process between agents during they facing to relocation choices. It is necessary for policy analysis and decision-making support by using ABMs. It means when we develop an ABM for policy analysis or decision-making support, the interactions between agents need to be linked to the policy, such as policy information sharing or policy attitude sharing. As a planning support tool to local residential policy, the parameters set for the simulation model should be consistent to reality. In this work we gain them from questionnaire survey and statistical analysis. While in the future this process may be supported by big data analysis.KeywordsAgent-Based Model (ABM)Household residential relocationResidential location choiceResidential utilityPolicy attitudeDowntown revitalization