Delineating a ‘15-Minute City’: An Agent-based Modeling Approach to Estimate the Size of Local Communities

Inflow and outflow of people


With progressively increased people living in cities, and lately the global COVID-19 outbreak, human mobility within cities has changed. Coinciding with this change, is the recent uptake of the ‘15-Minute City’ idea in urban planning around the world. One of the hallmarks of this idea is to create a high quality of life within a city via an acceptable travel distance (i.e., 15 minutes). However, a definitive benchmark for defining a ‘15- Minute City’ has yet to be agreed upon due to the heterogeneous character of urban morphologies worldwide. To shed light on this issue, we develop an agent-based model named ‘D-FMCities’ utilizing realistic street networks and points-of-interest, in this instance the borough of Queens in New York City as a test case. Through our modeling we grow diverse communities from the bottom up and estimate the size of such local communities to delineate 15-minute cities. Our findings suggest that the model could be helpful to detect the flexibility of defining the extent of a ‘15-minute city’ and consequently support uncovering the underlying factors that may affect its various definitions and diverse sizes throughout the world.

In Proceedings of the 4th ACM SIGSPATIAL International Workshop on Geospatial Simulation (GeoSim 2021)
Qingqing Chen
Qingqing Chen
PhD Candidate | Data Scientist

Ph.D. candidate focuses on critically understanding urban space by leveraging big data, combined with data science and machine learning techniques.