An agent-based simulation system for evaluating gridding urban management strategies

摘要

Traditional means of urban management are not satisfying the new demands placed by a modern city. Gridding urban management (GUM) seems to be a promising model for urban management in the 21st century. But the GUM must be more than “infrastructure” – it needs to support effective management strategies. This paper outlines our initial attempt of examining urban problems within a GUM framework and studying strategy choices. To this end, we construct an agent-based simulation system, namely DeciUrban, to explore GUM and strategy development. This paper proposes the architecture of DeciUrban and describes its core agent-based model using a model documentation protocol. A simulation of grid inspecting activities in Shanghai GUM is conducted with the purpose of assessing different inspecting strategies. The strategies involve district-first, community-first, cooperative, and random inspecting strategies. The results show how the effectiveness of strategies and the distribution of their impacts can be very different from what one would expect without the benefit of a simulation model. These simulations are presented as a demonstration that DeciUrban can help urban strategy developers understand a multitude of local interactions in cities, explore strategies, and improve community wellbeing without always designing field experiments. To sum up, simulation systems similar to DeciUrban could be valuable tools for addressing the challenges in the further development of GUM.