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Improving Driver Behavior Using Gamification

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Mobile Web and Intelligent Information Systems (MobiWIS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10995))

Abstract

This work proposes a gamification approach to measure the driving behavior using the in-vehicle data and score drivers. Existing work largely focus on one functionality: either displaying vehicular info or scoring the driver. And some other work just provides navigation or Point of Interest (POI). In our work, we combine these features with minimal distraction for the driver. With this goal, we consider a system that interfaces to the vehicle bus and find the errors of the driver during the drive using multiple criteria. Furthermore, by providing achievements and leader boards, the driver is motivated to have a good score while driving. To facilitate this analysis and to evaluate the system, we recorded two trips in real traffic. The results show that we achieve more than 95% accuracy between real-world scenario and the simulation. We also present POI feature that finds nearest preferred locations which are restaurants, hospitals, gas stations, pharmacies, car repair shops.

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Notes

  1. 1.

    www.obdii.com.

References

  1. Association for Safe International Road Travel (2017). http://asirt.org/initiatives/informing-road-users/road-safety-facts/road-crash-statistics. Accessed 29 May 2018

  2. OpenXC. http://openxcplatform.com/. Accessed 30 May 2018

  3. Qiu, H., et al.: Towards robust vehicular context sensing. IEEE Trans. Veh. Technol. 67(3), 1909–1922 (2018)

    Article  Google Scholar 

  4. OBD-II Regulations. https://www.arb.ca.gov/msprog/obdprog/obdregs.htm. Accessed 30 May 2018

  5. Kar, G., Jain, S., Gruteser, M., Bai, F., Govindan, R.: Real-time traffic estimation at vehicular edge nodes. In: Proceedings of the Second ACM/IEEE Symposium on Edge Computing, p. 3. ACM (2017)

    Google Scholar 

  6. Pentland, A., Lin, A.: Modeling and prediction of human behavior. Neural Comput. 11, 229–242 (1995)

    Article  Google Scholar 

  7. Eren, H., Makinist, S., Akin, E., Yilmaz, A.: Estimating driving behavior by a smartphone. In: Intelligent Vehicles Symposium (IV), 2012 IEEE, pp. 234–239. IEEE (2012)

    Google Scholar 

  8. Wang, Y.: Determining driver phone use by exploiting smartphone integrated sensors. IEEE Trans. Mob. Comput. 15(8), 1965–1981 (2016)

    Article  Google Scholar 

  9. DriveWell on the App Store (2015). https://itunes.apple.com/us/app/drivewell/id655601647?mt=8. Accessed 29 May 2018

  10. Cambridge Mobile Telematics (2015). https://www.cmtelematics.com/blog/. Accessed 29 May 2018

  11. mercedes-benz.com. Mercedes-Benz Apps (2007). https://www.mercedes-benz.com/en/mercedes-benz/lifestyle/mercedes-benz-apps/. Accessed 29 May 2018

  12. Liu, L., et al.: Toward detection of unsafe driving with wearables. In: Proceedings of the 2015 Workshop on Wearable Systems and Applications, pp. 27–32. ACM (2015)

    Google Scholar 

  13. Karatas, C., et al.: Leveraging wearables for steering and driver tracking. In: IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications, pp. 1–9. IEEE (2016)

    Google Scholar 

  14. Brown, A.K., Sturza, M.A.: Vehicle tracking system employing global positioning system (GPS) satellites, 6 July 1993. US Patent 5,225,842

    Google Scholar 

  15. Brown, A.K., Sturza, M.A.: GPS tracking system, 3 January 1995. US Patent 5,379,224

    Google Scholar 

  16. Chadil, N., Russameesawang, A., Keeratiwintakorn, P.: Real-time tracking management system using GPS, GPRS and Google earth. In: 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008. ECTI-Con 2008, vol. 1, pp. 393–396. IEEE (2008)

    Google Scholar 

  17. Kar, G., et al.: Detection of on-road vehicles emanating GPS interference. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 621–632. ACM (2014)

    Google Scholar 

  18. OnStar. OnStar by GM (2015). https://www.onstar.com/us/en/home/. Accessed 30 May 2018

  19. Fleetio Review. https://reviews.financesonline.com/p/fleetio. Accessed 29 May 2018

  20. Turk, Y., Ozcan, B., Gören, S.: Precise vehicle positioning for indoor navigation via OpenXC. In: Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS, vol. 1, pp. 440–445. INSTICC, SciTePress (2018)

    Google Scholar 

  21. Department of Electrical Engineering Linkopings universitet. Detection of Critical Events Using Limited Sensors (2012). http://www.diva-portal.org/smash/get/diva2:570048/FULLTEXT01.pdf. Accessed 29 May 2018

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Acknowledgement

We want to thank to Mine Kandil, Burak Koc, and Yanki Insel for their constant supports and contributions to the project.

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Authors and Affiliations

  1. Department of Computer Engineering, Yeditepe University, Istanbul, Turkey

    Simge Helvaci, Aras Senova, Gorkem Kar & Sezer Gören

Authors
  1. Simge Helvaci
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  2. Aras Senova
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  3. Gorkem Kar
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  4. Sezer Gören
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Corresponding author

Correspondence to Sezer Gören .

Editor information

Editors and Affiliations

  1. Oxford Brookes University, Oxford, United Kingdom

    Muhammad Younas

  2. University of Bradford, Bradford, United Kingdom

    Irfan Awan

  3. Brunel University London, Uxbridge, United Kingdom

    George Ghinea

  4. i2CAT, Barcelona, Spain

    Marisa Catalan Cid

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Helvaci, S., Senova, A., Kar, G., Gören, S. (2018). Improving Driver Behavior Using Gamification. In: Younas, M., Awan, I., Ghinea, G., Catalan Cid, M. (eds) Mobile Web and Intelligent Information Systems. MobiWIS 2018. Lecture Notes in Computer Science(), vol 10995. Springer, Cham. https://doi.org/10.1007/978-3-319-97163-6_16

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  • DOI: https://doi.org/10.1007/978-3-319-97163-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97162-9

  • Online ISBN: 978-3-319-97163-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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