Agent-Based Modelling for Urban Planning Current Limitations and Future Trends

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• 关键词：Agent ; based modelling ; Key challenges ; Urban modelling ; Urban planning
• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10051
• 期：1
• 页码：60-69
• 丛书名：Agent Based Modelling of Urban Systems
• ISBN：978-3-319-51957-9
• 卷排序：10051

文摘

With the global population expected to increase form 7.3 billion in 2015 to 9.5 billion by 2050 [41], 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 multi-dimensional 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.