SURVEY ON CHANGES IN PASSENGER FLOWS

Ashwini Ashok Phadtare, Khairmode Pooja S., Nikam Priyanka V., Lokhande Snehal B.

Abstract


Railway systems in mega-cities are affected by various events such as natural disasters, accidents, and public gatherings. In 2017 near Manikpur railway station in Uttar Pradesh killing three and injuring at least nine passenger because of the thirteen coaches of Vasco Da Gama-Patna Express derailed. A huge and complicated networks in the railway system increase uncertainty in the network because they provides various transfer routes to passenger. Visualization is one of the most important techniques for examining such unnecessary situations in the large networks. In this paper, we proposed a new approach for visual integration of traffic analysis and social media analysis using two forms of big data: railway station data and social media data like SMS service. In that we present different views to usually and simultaneously explore changes in passenger flow and abnormal situations extract from railway station data and situational explanations of passenger such as complaints about services extracted from social media. It exhibits the possibilities and usefulness of our visualization environment using a dataset studies and experts feedback about various kinds of events.

Keywords


Visual analysis, Information visualization, Data mining, big data, Railway station data, Social media data.

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References


Masahiko Itoh, Member, IEEE, Daisaku Yokoyama, Member, IEEE, Masashi Toyoda, Member, IEEE,Yoshimitsu Tomita, Satoshi Kawamura, and Masaru Kitsuregawa, Fellow, “Visual Exploration of Changes in Passenger Flows and Tweets on Mega-City Metro Network” IEEE TRANSACTIONS ON BIG DATA, VOL. 2, NO. 1, JANUARY-MARCH 2016

R. Kr€uger, D. Thom, and T. Ertl, “Visual analysis of movement behavior using web data for context enrichment,” in Proc. IEEE Pacific Vis. Symp.,2014, pp. 193–200.

I. Ceapa, C. Smith, and L. Capra, “Avoiding the crowds: Understanding tube station congestion patterns from trip data,” in Proc. ACM SIGKDD Int. Workshop Urban Comput., 2012, pp. 134–141.

L. Sun, D.-H. Lee, A. Erath, and X. Huang, “Using smart card data to extract passenger’s spatio-temporal density and train’s trajectory of MRT system,” in Proc.ACM SIGKDD Int. Workshop Urban Comput., 2012, pp. 142–148.

C. Tominski, P. Schulze-Wollgast, and H. Schumann, “3D information visualization for time dependent data on maps,” in Proc.9th Int. Conf. Inf. Vis., 2005, pp. 175–181.

S. Hadlak, H. Schulz, and H. Schumann, “In situ exploration of large dynamic networks,” IEEE Trans. Vis. Comput. Graph. vol. 17, no. 12, pp. 2334–2343, Dec. 2011.

W. Dou, X. Wang, D. Skau, W. Ribarsky, and M. X. Zhou, “LeadLine: Interactive visual analysis of text data through event identification and exploration,” in Proc. IEEE Conf. Visual Anal.Sci. Technol., 2012, pp. 93–102.

A. M. MacEachren, A. R. Jaiswal, A. C. Robinson, S. Pezanowski, A. Savelyev, P. Mitra, X. Zhang, and J. Blanford, “SensePlace2: GeoTwitter analytics support for situational awareness,” in Proc.IEEE Conf. Visual Anal. Sci. Technol., 2011, pp. 181–190.

D. Thom, H. Bosch, S. Koch, M. W€orner, and T. Ertl, “Spatiotemporal anomaly detection through visual analysis of geolocated Twitter messages,” in Proc. PacificVis, 2012, pp. 41–48.

D. Yokoyama, M. Itoh, M. Toyoda, Y. Tomita, S. Kawamura, and M. Kitsuregawa, “A framework for large-scale train trip record analysis and its application to passengers’ flow prediction after train accidents,” in Proc. 18th Pacific-Asia Conf. Adv. Knowl. Discovery Data Mining, 2014, pp. 533–544.

E. R. Tufte, The Visual Display of Quantitative Information. Cheshire, CT, USA: Graphics Press, 1983.

T. N. Dang, L. Wilkinson, and A. Anand, “Stacking graphic elements to avoid over-plotting,” IEEE Trans. Vis. Comput. Graph., vol. 16, no. 6, pp. 1044–1052, Nov./Dec. 2010.

M. Sarkar and M. H. Brown, “Graphical fisheye views,” Commun. ACM, vol. 37, no. 12, pp. 73–83, 1994.

E. R. Tufte, Beautiful Evidence. Cheshire, CT, USA: Graphics Press, 2006.

T. M. J. Fruchterman and E. M. Reingold, “Graph drawing by force-directed placement,” Softw. Practice Experience, vol. 21, no. 11, pp. 1129–1164, 1991.




DOI: https://doi.org/10.26483/ijarcs.v9i1.5157

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