Measuring variability of mobility patterns from multiday smart-card data

Journal of Computational Science

Volumn 9, Issue , 2015, Pages 125-130

  Zhong, Chen ^a,b   Manley, Ed ^a   Müller Arisona, Stefan ^b,c   Batty, Michael ^a   Schmitt, Gerhard ^b  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b ETH ZURICH   (Switzerland)

^c Fachhochschule Nordwestschweiz   (Switzerland)

Author keywords

Clustering; Network; Smart card data; Spatial analysis; Variability

Indexed keywords

NETWORKS (CIRCUITS); TRANSPORTATION;

CLUSTERING; CORRELATION MATRIX; GENERIC FRAMEWORKS; SPATIAL ANALYSIS; SYSTEMIC FRAMEWORKS; TRANSPORT NETWORKS; URBAN APPLICATIONS; VARIABILITY;

SMART CARDS;

EID: 84930207033     PISSN: 18777503     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jocs.2015.04.021     Document Type: Article

References (20)

1. Agard B., Morency C., Trépanier M. Mining public transport user behaviour from smart card data. Paper Presented at the 12th IFAC Symposium on Information Control Problems in Manufacturing-INCOM 2006.
2. Ahas R., Aasa A., Silm S., Tiru M. Daily rhythms of suburban commuters' movements in the Tallinn metropolitan area: case study with mobile positioning data. Trans. Res. Part C: Emerg. Technol. 2010, 18(1):45-54.
3. Axhausen K.W., Zimmermann A., Schönfelder S., Rindsfüser G., Haupt T. Observing the rhythms of daily life: a six-week travel diary. Transportation 2002, 29(2):95-124.
4. Barthélemy M. Spatial networks. Phys. Rep. 2011, 499(1):1-101.
5. Gonzalez M.C., Hidalgo C.A., Barabasi A.-L. Understanding individual human mobility patterns. Nature 2008, 453(7196):779-782.
6. Hasan S., Schneider C., Ukkusuri S., González M. Spatiotemporal patterns of urban human mobility. J. Statist. Phys. 2013, 151(1-2):304-318. 10.1007/s10955-012-0645-0
7. Jones P., Clarke M. The significance and measurement of variability in travel behaviour. Transportation 1988, 15(1-2):65-87. 10.1007/BF00167981
8. Liang L., Anyang H., Biderman A., Ratti C., Jun C. Understanding individual and collective mobility patterns from smart card records: a case study in Shenzhen. Paper Presented at the Intelligent Transportation Systems, 2009 2009, 4-7 October.
9. M.P. Pelletier, M. Trépanier, C. Morency. Smart card data in public transit planning: a review: CIRRELT (2009).
10. Ratti C., Sobolevsky S., Calabrese F., Andris C., Reades J., Martino M., Strogatz S.H. Redrawing the map of Great Britain from a network of human interactions. PloS One 2010, 5(12):e14248.
11. Schneider C.M., Belik V., Couronné T., Smoreda Z., González M.C. Unravelling daily human mobility motifs. J. R. Soc. Interface 2013, 10(84):20130246.
12. Schönfelder S., Axhausen K.W. Urban Rhythms and Travel Behaviour: Spatial and Temporal Phenomena of Daily Travel 2010, Ashgate Publishing Ltd.
13. Simini F., González M.C., Maritan A., Barabási A.-L. A universal model for mobility and migration patterns. Nature 2012, 484(7392):96-100. 10.1038/nature10856
14. Song C., Koren T., Wang P., Barabási A.-L. Modelling the scaling properties of human mobility. Nat. Phys. 2010, 6(10):818-823. 10.1038/nphys1760
15. Soto V., Frías-Martínez E. Automated land use identification using cell-phone records. Paper Presented at the Proceedings of the 3rd ACM International Workshop on MobiArch 2011.
16. Szell M., Sinatra R., Petri G., Thurner S., Latora V. Understanding mobility in a social petri dish. Sci. Rep. 2012, 2:1-6. 10.1038/srep00457
17. Thiemann C., Theis F., Grady D., Brune R., Brockmann D. The structure of borders in a small world. PloS One 2010, 5(11):e15422.
18. Zhong C., Arisona S.M., Huang X., Batty M., Schmitt G. Detecting the dynamics of urban structure through spatial network analysis. Int. J. Geog. Inf. Sci. 2014, 28(11):2178-2199. 10.1080/13658816.2014.914521
19. Zhong C., Huang X., Müller Arisona S., Schmitt G., Batty M. Inferring building functions from a probabilistic model using public transportation data. Comput. Environ. Urban Syst. 2014, 48:124-137.
20. Zhong C., Müller Arisona S., Huang X., Schmitt G. Identifying spatial structure of urban functional centers using travel survey data: a case study of Singapore. Paper Presented at the Proceedings of The First ACM SIGSPATIAL International Workshop on Computational Models of Place 2013.