Variability in regularity: Mining temporal mobility patterns in London, Singapore and Beijing using smart-card data

PLoS ONE

Volumn 11, Issue 2, 2016, Pages

  Zhong, Chen ^a   Batty, Michael ^a   Manley, Ed ^a   Wang, Jiaqiu ^a   Wang, Zijia ^b,c   Chen, Feng ^b,c   Schmitt, Gerhard ^d  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b BEIJING JIAOTONG UNIVERSITY   (China)

^c Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention   (China)

^d ETH ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

CHINA; CIRCADIAN RHYTHM; CITY; COMPARATIVE STUDY; CONTROLLED STUDY; HUMAN; MINING; PREDICTION; SINGAPORE; SMART CARD; TRAVEL; UNITED KINGDOM; AUTOMATED PATTERN RECOGNITION; ENGLAND; TIME FACTOR; TRAFFIC AND TRANSPORT; URBANIZATION;

BEIJING; HUMANS; LONDON; PATTERN RECOGNITION, AUTOMATED; SINGAPORE; TIME FACTORS; TRANSPORTATION; URBANIZATION;

EID: 84960539399     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0149222     Document Type: Article

References (34)

1. Rodrigue J-P, Comtois C, Slack B. The geography of transport systems. 3rded. New York: Routledge; 2013.
2. Hasan S, Schneider C, Ukkusuri S, González M. Spatiotemporal patterns of urban human mobility. Journal of Statistical Physics. 2013;151(1-2):304-18. doi: 10.1007/s10955-012-0645-0
3. Silva R, Kang SM, Airoldi EM. Predicting traffic volumes and estimating the effects of shocks in massive transportation systems. Proceedings of the National Academy of Sciences. 2015;112(18):5643-8.
4. Roth C, Kang SM, Batty M, Barthélemy M. Structure of urban movements: polycentric activity and entangled hierarchical flows. PLOSOne. 2011;6(1):e15923. doi: 10.1371/journal.pone.0015923 PMID: 21249210
5. Eagle N, Pentland AS, Lazer D. Inferring friendship network structure by using mobile phone data. Proceedings of the National Academy of Sciences. 2009;106(36):15274-8.
6. Kang C, Ma X, Tong D, Liu Y. Intra-urban human mobility patterns: An urban morphology perspective. PhysicaA: Statistical Mechanics and its Applications. 2012;391(4):1702-17.
7. Zhong C, Arisona SM, Huang X, Batty M, Schmitt G. Detecting the dynamics of urban structure through spatial network analysis. International Journal of Geographical Information Science. 2014;28(11):2178-99. doi: 10.1080/13658816.2014.914521
8. Sung H, Oh J-T. Transit-oriented development in a high-density city: Identifying its association with transit ridership in Seoul, Korea. Cities. 2011;28(1):70-82.
9. Belik V, Geisel T, Brockmann D. Natural human mobility patterns and spatial spread of infectious diseases. Physical Review X. 2011;1(1):011001.
10. Balcan D, Colizza V, Gonçalves B, Hu H, Ramasco JJ, Vespignani A. Multiscale mobility networks and the spatial spreading of infectious diseases. Proceedings of the National Academy of Sciences. 2009;106(51):21484-9.
11. Kühnert C, Helbing D, West GB. Scaling laws in urban supply networks. PhysicaA: Statistical Mechanics and its Applications. 2006;363(1):96-103.
12. Bettencourt LMA, Lobo J, Helbing D, Kühnert C, West GB. Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences. 2007;104(17):7301-6.
13. Batty M. Polynucleated urban landscapes. Urban Studies. 2001;38(4):635-55.
14. Batty M, Besussi E, Maat K, Harts JJ. Representing multifunctional cities: density and diversity in space and time. Built Environment. 2004;30(4):324-37.
15. Gonzalez MC, Hidalgo CA, Barabasi A-L. Understanding individual human mobility patterns. Nature. 2008;453(7196):779-82. doi: 10.1038/nature06958 PMID: 18528393
16. Schneider CM, Belik V, Couronné T, Smoreda Z, González MC. Unravelling daily human mobility motifs. Journal of The Royal Society Interface. 2013;10(84). doi: 10.1098/rsif.2013.0246
17. Liang X, Zhao J, Dong L, Xu K. Unraveling the origin of exponential law in intra-urban human mobility. Scientific Reports. 2013;3.
18. Sun L, Axhausen KW, Lee D-H, Huang X. Understanding metropolitan patterns of daily encounters. Proceedings of the National Academy of Sciences. 2013;110(34):13774-9. doi: 10.1073/pnas. 1306440110
19. Thiemann C, Theis F, Grady D, Brune R, Brockmann D. The structure of borders in a small world. PLOSOne. 2010;5(11):e15422. doi: 10.1371/journal.pone.0015422 PMID: 21124970
20. Noulas A, Scellato S, Lambiotte R, Pontil M, Mascolo C. A tale of many cities: universal patterns in human urban mobility. PLOSOne. 2012;7(5):e37027. doi: 10.1371/journal.pone.0037027 PMID: 22666339
21. Yan X-Y, Han X-P, Wang B-H, Zhou T. Diversity of individual mobility patterns and emergence of aggregated scaling laws. Scientific reports. 2013;3.
22. Song C, Qu Z, Blumm N, Barabási A-L. Limits of predictability in human mobility. Science. 2010;327(5968):1018-21. doi: 10.1126/science.1177170 PMID: 20167789
23. Agard B, Morency C, Trépanier M, editors. Mining public transport user behaviour from smart card data. 12th IFAC Symposium on Information Control Problems in Manufacturing-INCOM; 2006.
24. Bagchi M, White P. What role for smart-card data from bus systems? Municipal Engineer. 2004;157(1):39-46.
25. Pelletier MP, Trépanier M, Morency C. Smart card data use in public transit: A literature review. Transportation Research PartC: Emerging Technologies. 2011;19(4):557-68.
26. Transportfor London. Travel in London, Supplementary Report: London Travel Demand Survey (LTDS). 2011.
27. Gordon JB, Koutsopoulos HN, Wilson NH, Attanucci JP. Automated Inference of Linked Transit Journeys in London Using Fare-Transaction and Vehicle Location Data. Transportation Research Record: Journal of the Transportation Research Board. 2013;2343(1):17-24.
28. Cheong CC, Toh R. Household interview surveys from 1997 to 2008-A decade of changing travel behaviours. Editorial Team. 2010:52.
29. Land Transport Authority. Household Interview Travel Survey 2012 Singapore 2014.
30. Zhong C, Manley E, Arisona SM, Batty M, Schmitt G. Measuring variability of mobility patterns from multiday smart-card data. Journal of Computational Science. 2015;9:125-30.
31. Liang L, Anyang H, Biderman A, Ratti C, Jun. C, editors. Understanding individual and collective mobility patterns from smart card records: a case study in Shenzhen. Intelligent Transportation Systems, 2009 ITSC '09 12th International IEEE Conference; 2009 4-7 Oct. 2009.
32. Zhong C, Huang X, Müller Arisona S, Schmitt G, Batty M. Inferring building functions from a probabilistic model using public transportation data. Computers, Environment and Urban Systems. 2014;48:124-37.
33. Munizaga MA, Palma C. Estimation of a disaggregate multimodal public transport Origin-Destination matrix from passive smartcard data from Santiago, Chile. Transportation Research Part C: Emerging Technologies. 2012;24:9-18.
34. Manual HC. Highway capacity manual. Washington, DC. 2000.