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Human mobility modelling: exploration and preferential return meet the gravity model

Conference Paper
Publication Date:
2016
abstract:
Modeling the properties of individual human mobility is a challenging task that has received increasing attention in the last decade. Since mobility is a complex system, when modeling individual human mobility one should take into account that human movements at a collective level influence, and are influenced by, human movement at an individual level. In this paper we propose the d-EPR model, which exploits collective information and the gravity model to drive the movements of an individual and the exploration of new places on the mobility space. We implement our model to simulate the mobility of thousands synthetic individuals, and compare the synthetic movements with real trajectories of mobile phone users and synthetic trajectories produced by a prominent individual mobility model. We show that the distributions of global mobility measures computed on the trajectories produced by the d-EPR model are much closer to empirical data, highlighting the importance of considering collective information when simulating individual human mobility.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Human Mobility; Data Science; Mobility Modeling
List of contributors:
Pappalardo, Luca; Rinzivillo, Salvatore
Authors of the University:
PAPPALARDO LUCA
RINZIVILLO SALVATORE
Handle:
https://iris.cnr.it/handle/20.500.14243/407234
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/407234/91369/prod_424160-doc_151173.pdf
Published in:
PROCEDIA COMPUTER SCIENCE
Journal
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URL

https://www.sciencedirect.com/science/article/pii/S1877050916302216
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