Investigation of Traffic Pattern for the Augmented Reality Applications

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10372)


In this article, the interaction between augmented reality and flying ubiquitous sensor networks (FUSN) technologies is investigated. Such modern applications require development of the new traffic patterns, which can be used to establish a new approach to the further Quality of Experience assurance and estimation. The proposed new traffic pattern captures service space model, model of an environment of the user and behavior model.


Augmented reality Flying ubiquitous sensor networks Unmanned aerial vehicles Interaction model Traffic pattern Quality of experience 



The publication was financially supported by the Ministry of Education and Science of the Russian Federation (the Agreement number 02.a03.21.0008), RFBR according to the research project No. 16-37-00209 mol_a “Development of the principles of integration the Real Sense technology and Internet of Things”.


  1. 1.
    Ong, S.K., Yeh, A., Nee, C.: Virtual and augmented reality applications in manufacturing. Springer Science & Business Media (2013)Google Scholar
  2. 2.
    Billinghurst, M., Clark, A, Lee, G.: A survey of augmented reality. Found. Trends Hum. Comput. Interact. 8(2-3), 73–272 (2015)Google Scholar
  3. 3.
    Bergenti, F., Gotta, D.: Augmented reality for field maintenance of large telecommunication networks. In: Conference and Exhibition of the European Association of Virtual and Augmented Reality (2014)Google Scholar
  4. 4.
    Hui, M., Bai, L., Li, Y., Wu, Q.: Highway traffic flow nonlinear character analysis and prediction. Mathematical Problems in Engineering (2015)Google Scholar
  5. 5.
    Abdi, L., Ben Abdallah, F., Meddev, A.: In-vehicle augmented reality traffic information system: a new type of communication between driver and vehicle. Procedia Comput. Sci. 73, 242–249 (2015)CrossRefGoogle Scholar
  6. 6.
    Park, J.-G., Kim, K.-J.: Design of a visual perception model with edge-adaptive gabor filter and support vector machine for traffic sign detection. Expert Syst. Appl. 40(9), 3679–3687 (2013)CrossRefGoogle Scholar
  7. 7.
    Vinel, A., Vishnevsky, V., Koucheryavy, Y.: A simple analytical model for the periodic broadcasting in vehicular ad-hoc networks. In: 2008 IEEE GLOBECOM Workshops, pp. 1–5 (2008)Google Scholar
  8. 8.
    Hong-Bin, Z., Xiao-Duan, S., Yu-Long, H.: Analysis and prediction of complex dynamical characteristics of short-term traffic flow. Acta Physica Sinica 63(4), 1–8 (2014)Google Scholar
  9. 9.
    Topór-Kamiñski, T., Krupanek, B., Homa, J.: Delays models of measurement and control data transmission network. In: Nawrat, A., Simek, K., Świerniak, A. (eds.) Advanced Technologies for Intelligent Systems. SCI, vol. 440, pp. 257–278. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-31665-4_21
  10. 10.
    Ng-Thow-Hing, V., Bark, K., Beckwith, L., Tran, C., Bhandari, R., Sridhar S. User-centered perspectives for automotive augmented reality. In: IEEE International Symposium on Mixed and Augmented Reality 2013, Adelaide, SA, Australia, October 2013Google Scholar
  11. 11.
    de Winter, J.: Preparing drivers for dangerous situations: a critical reflection on continuous shared control. Systems, Man, and Cybernetics (SMC) 1050–1056 (2011)Google Scholar
  12. 12.
    Zollmann, S., Hoppe, C., Langlotz, T., Reitmayr, G.: FlyAR: augmented reality supported micro aerial vehicle navigation. IEEE Trans. Vis. Comput. Graph. 20, 560–568 (2014)CrossRefGoogle Scholar
  13. 13.
    Shafig, M.Z., et al.: A first look at cellular machine-to-machine traffic: large scale measurement and characterization. In: 12th ACM Sigmetrics Performance International Conference. June 11–15, London, England, UK (2012)Google Scholar
  14. 14.
    Dao, N., Koucheryavy, A., Paramonov, A.: Analysis of routes in the network based on a swarm of UAVs. In: Kim, K., Joukov, N. (eds.) ICISA 2016. LNEE, vol. 376, pp. 1261–1271. Springer, Singapore (2016). doi: 10.1007/978-981-10-0557-2_119
  15. 15.
    Pokric, B., Krco, S., Pokric, M.: Augmented reality based smart city services using secure IoT Infrastructure. In: 2014 IEEE 28th International Conference on Advanced Information Networking and Applications Workshops (WAINA) (2014)Google Scholar
  16. 16.
    Andreev, S., Galinina, O., Pyattaev, A., Johansson, K., Koucheryavy, Y.: Analyzing assisted offloading of cellular user sessions onto D2D links in unlicensed bands. IEEE J. Sel. Areas Commun. 33(1), 67–80 (2014)CrossRefGoogle Scholar
  17. 17.
    Pyattaev, A., Johnsson, K., Surak, A., Florea, R., Andreev, S., Koucheryavy, Y.: Network-assisted D2D communications: implementing a technology prototype for cellular traffic offloading. In: 2014 IEEE Wireless Communications and Networking Conference (WCNC), pp. 3266–3271 (2014)Google Scholar
  18. 18.
    Drajic, D., et al.: Traffic generation application for simulating online games and M2M applications via Wireless Networks. In: 9th Conference on Wireless on-demand Network Systems and Services WONS 2012, Courmayeur, Italy, 9–11 January 2012Google Scholar
  19. 19.
    Orlovsky, J., Kiyokawa, K., Takemura, H.: Virtual and augmented reality on the 5G highway. J. Inform. Process. 25, 133–141 (2017)CrossRefGoogle Scholar
  20. 20.
    Westphal, C.: Challenges in networking to support augmented reality and virtual reality. In: ICNC 2017, Silicon Valley, California, USA, 26–29 January 2017Google Scholar
  21. 21.
    Vybornova, A., Koucheryavy, A.: Traffic analysis in target tracking ubiquitous sensor networks. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) NEW2AN 2014. LNCS, vol. 8638, pp. 389–398. Springer, Cham (2014). doi: 10.1007/978-3-319-10353-2_34 Google Scholar
  22. 22.
    Koucheryavy, A., Makolkina, M., Paramonov, A.: Applications of augmented reality traffic and quality requirements study and modeling. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds.) DCCN 2016. CCIS, vol. 678, pp. 241–252. Springer, Cham (2016). doi: 10.1007/978-3-319-51917-3_22 CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  1. 1.The Bonch-Bruevich State University of TelecommunicationsSt. PetersburgRussian Federation
  2. 2.Peoples’ Friendship University of Russia (RUDN University)MoscowRussian Federation

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