A Novel Real-Time Traffic Information Collection System Based on Smartphone

  • Xiang Liu
  • Zhibo Wang
  • Zhi Wang
  • Shugang Lv
  • Tao Guan
Part of the Communications in Computer and Information Science book series (CCIS, volume 334)

Abstract

The traffic information collection system is the underlying part of the intelligent transportation system. In this paper, we propose a novel real-time traffic information collection system, which recognizes driving status, detects the driving route, and updates the traffic condition accordingly. Specifically, we first model the roads as a virtual map, and then based on which we design a lightweight road topology relational database. Secondly, taking advantage of accelerometer and compass on the smartphone, we propose a lightweight driving status tracking algorithm that can accurately recognize users driving status. Finally the sensors readings is considered along with users driving status and the database to give real-time automatically route recognition. Meanwhile, in order to get accurate real-time information as well as protect users privacy, users driving speed is calculated in real-time manner and the encrypted driving route results are uploaded to the server. Experiments results show the effectiveness of our system.

Keywords

Intelligent Transportation System GPS algorithms measurement participatory sensing smart phone 

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References

  1. 1.
  2. 2.
    ITS Unit Costs Database, http://www.itscosts.its.dot.gov/
  3. 3.
    Klein, L.A., Mills, M.K., Gibson, D.R.P.: Traffic Detector Handbook, 3rd edn. US Department of Transportation, Washington, DC, USA (2006)Google Scholar
  4. 4.
    Guillaume, L.: Road traffic data: Collection methods and applications. Technical report, Institute for Prospective Technological Studies, EU (2008)Google Scholar
  5. 5.
    Turksma, S.: The various uses of floating car data. Road Transport Information and Control, 51–55 (2000)Google Scholar
  6. 6.
    Schaefer, R.P., Thiessenhusen, K.U., Wagner, P.: A traffic information system by means of real-time floating-car data. In: Proc. ITS World Congress, Chicago, USA (2002)Google Scholar
  7. 7.
    Kerner, B.S., Demir, C., Herrtwich, R.G.: Traffic state detection with floating car data in road networks. In: Proc. 8th International IEEE Conference on Intelligent Transportation Systems, pp. 44–49 (2005)Google Scholar
  8. 8.
    Greenfeld, J.: Matching GPS observations to locations on a digital map. In: Proc. 81st Annual Meeting of the Transportation Research Board, pp. 164–173 (2002)Google Scholar
  9. 9.
    Quddus, M., Ochieng, W., Zhao, L.: A general map matching algorithm for transport telematics applications. GPS Solutions Journal 7(3), 157–167 (2003)CrossRefGoogle Scholar
  10. 10.
    Quddus, M., Ochieng, W., Noland, R.: Current map-matching algorithms for transport applications: State-of-the art and future research directions. Transportation Research Part C: Emerging Technologies 15(5), 312–328 (2007)CrossRefGoogle Scholar
  11. 11.
    Burke, J.A., Estrin, D.: Participatory sensing. In: ACM Sensys World Sensor Web Workshop, Boulder, CO, USA (2006)Google Scholar
  12. 12.
    The mobile millenium project, http://traffic.berkeley.edu/
  13. 13.
    The CarTel project, http://cartel.csail.mit.edu/
  14. 14.
    Wunnava, S., Yen, K., Babij, T.: Travel time estimation using cell phone for highways and roadways. Technical report, Florida Department of Transportation (2007)Google Scholar
  15. 15.
    Arvind, T., Lenin, R., Katrina, L.: VTrack: Accurate, Energy-AwareTraffic Delay Estimation Using Mobile Phones. In: Proc. 7th ACM Conference on Embedded Networked Sensor Systems, Berkeley, CA (2009)Google Scholar
  16. 16.
    Arvind, T., Lenin, R., Hari, B.: Accurate, low-energy trajectory mapping for mobile devices. In: Proceedings of USENIX NSDI (2011)Google Scholar
  17. 17.
    Hoh, B., Gruteser, M., Herring, R.: Virtual trip lines for distributed privacy-preserving traffic monitoring. In: MobiSys 2008: Proceeding of the 6th International Conference on Mobile Systems, Applications, and Services, pp. 15–28 (2008)Google Scholar
  18. 18.
    Mohan, P., Padmanabhan, V.N., Ramjee, R.: Nericell: Rich Monitoring of Road and Traffic Conditions using Mobile Smartphones. In: Proc. of 8th ACM Conference on Embedded Networked Sensor Systems, pp. 357–370 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xiang Liu
    • 1
  • Zhibo Wang
    • 1
  • Zhi Wang
    • 1
  • Shugang Lv
    • 1
  • Tao Guan
    • 2
  1. 1.State Key Laboratory of Industrial Control TechnologyZhejiang UniversityHangzhouChina
  2. 2.Zhejiang Provincial Department of Land Resources, Information CenterZhejiang UniversityHangzhouChina

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