Spatiotemporal Patterns of Urban Human Mobility
Name
Gonzalez_Spatiotemporal patterns.pdf
Size
1.35 MB
Format
Adobe PDF
Checksum (MD5)
afa00758176fa242bd0b5d7789a30a44
Author(s)
Hasan, Samiul
Schneider, Christian M.
Ukkusuri, Satish V.
Gonzalez, Marta C.
Date Issued
December 2012
Journal
Journal of Statistical Physics
Publisher
Springer Science+Business Media
Citation
Hasan, Samiul, Christian M. Schneider, Satish V. Ukkusuri, and Marta C. González. “Spatiotemporal Patterns of Urban Human Mobility.” J Stat Phys 151, no. 1–2 (December 7, 2012): 304–318.
Version
Author's final manuscript
Abstract
The modeling of human mobility is adopting new directions due to the increasing availability of big data sources from human activity. These sources enclose digital information about daily visited locations of a large number of individuals. Examples of these data include: mobile phone calls, credit card transactions, bank notes dispersal, check-ins in internet applications, among several others. In this study, we consider the data obtained from smart subway fare card transactions to characterize and model urban mobility patterns. We present a simple mobility model for predicting peoples’ visited locations using the popularity of places in the city as an interaction parameter between different individuals. This ingredient is sufficient to reproduce several characteristics of the observed travel behavior such as: the number of trips between different locations in the city, the exploration of new places and the frequency of individual visits of a particular location. Moreover, we indicate the limitations of the proposed model and discuss open questions in the current state of the art statistical models of human mobility.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s10955-012-0645-0
