Agent-based modelling for urban planning current limitations and future trends



Publication Details

Perez, P., Banos, A. & Pettit, C. (2017). Agent-based modelling for urban planning current limitations and future trends. Lecture Notes in Computer Science, 10051 60-69.


With the global population expected to increase form 7.3 billion in 2015 to 9.5 billion by 2050, smart city planning is becoming increasingly important. This is further exasperated by the fact that an increasing number of people are relocating to cities as we live in a highly urbanised world. Cities are evolving in complex and multidimensional ways that can no longer be limited to land use and transport development. In increasingly important that cities planning embraces a more holistic, participatory and iterative approach that balances productivity, livability and sustainability outcomes. A new generation of bottom up, highly granular, highly dynamic and spatially explicit models have emerged to support evidence-based and adaptive urban planning. Agent-based modelling, in particular, has emerged as a dominant paradigm to create massive simulations backed by ever-increasing computing power. In this paper we point at current limitations of pure bottom-up approaches to urban modelling and argue for more flexible frameworks mixing other modelling paradigms, particularly participatory planning approaches. Then, we explore four modelling challenges and propose future trends for agent-based modelling of urban systems to better support planning decisions.

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