Procedural City Generation Beyond Game Development

In the current SIGSPATIAL Special Newsletter whose theme is Urban Analytics and Mobility, Joon-Seok Kim, Hamdi Kavak and myself have a paper entitled "Procedural City Generation Beyond Game Development". In the paper we discuss how synthetic urban areas created via procedural city generation in which agents occupy could be used to automatically generate data which  could then be used as urban testbeds for applications such as social simulation, self-driving cars and transportation.  Specifically, we review procedural city generation from several perspectives: goals , inputs , outputs and methods. Which in turn allows us to address specific issues (e.g., plausibility, level of detail, ease of use) to sufficiently capture real-world cities and the people who inhabit them. If you want to find out more, below is the abstract to the paper along with the full reference an a link to the paper.

Abstract:

The common trend in the scientific inquiry of urban areas and their populations is to use real-world geographic and population data to understand, explain, and predict urban phenomena. We argue that this trend limits our understanding of urban areas as dealing with arbitrarily collected geographic data requires technical expertise to process; moreover, population data is often aggregated, sparsified, or anonymized for privacy reasons. We believe synthetic urban areas generated via procedural city generation, which is a technique mostly used in the gaming area, could help improve the state-of-the-art in many disciplines which study urban areas. In this paper, we describe a selection of research areas that could benefit from such synthetic urban data and show that the current research in procedurally generated cities needs to address specific issues (e.g., plausibility) to sufficiently capture real-world cities and thus take such data beyond gaming.

Full Reference:

Kim, J-S., Kavak, H. and Crooks A.T. (2018), Procedural City Generation Beyond Game Development, SIGSPATIAL Special, 10(2), 34-41. DOI: 10.1145/3292390.3292397 (pdf)