Smart City Gnosys

Smart city article details

Title	An Integrated Framework For Population Synthesis At Fine-Grained Spatial Scales
ID_Doc	8443
Authors	Huang Y.; Zhou M.; Deng R.; Huang Z.; You L.
Year	2023
Published	Lecture Notes in Civil Engineering, 211 LNCE
DOI	http://dx.doi.org/10.1007/978-981-19-5217-3_129
Abstract	With the conception and development of Smart City and its applications, Digital Twins and other related technologies have been growing rapidly during the past years. Simultaneously, in the fields of transportation and urban analytics, agent-based models (ABMs) and microsimulations have also gained popularity, partly echoing the Digital Twins initiatives in Smart City applications, and is also owing to the sharply rising utilizability of high-performance computation resources and rapidly boosting high scale data storage. This study mainly developed a population synthesis pipeline to generate spatially detailed populations in urban environments and combined probabilistic models and re-weighting techniques for agent synthesis to cope with microdata on heterogeneity and marginal control matching. We also structured the built environment with higher spatial resolution than previous studies. We then created a realistic and spatially fine-grained synthetic population by the assignment of agents to the spatial units via rule-based and behavioral modeling. The results show good performance in terms of the accuracies over different dimensions and the proposed pipeline can facilitate the use of ABMs in Smart City projects. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Author Keywords	Agent-based modeling; Data fusion; Population synthesis; Probabilistic modeling; Smart city

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