Interactive, GPU-based urban growth simulation for agile urban policy modelling

In this paper we present a novel approach of simulating urban growth by utilising the computation power of modern GPUs. The simulation results can be used in urban policy modelling to reduce turnaround times in the policy cycle. We use a state-of-the-art agent-based simulation model that consists of rules to describe human behaviour. The simulation incorporates geospatial information such as land-use, current population density and road network data. In order to simulate the phenomena of urbanisation, in our model citizens more likely settle near roads or existing settlements/cities. In this paper we present our implementation that is based on the FLAME GPU framework. Each agent on the GPU represents a group of citizens at a specific location. In order to evaluate our approach we present a practical use case. We measure the performance of our implementation and compare it with a Java-based solution. Finally, we discuss our approach and show opportunities for agile and interactive urban policy modelling