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International Conference on Green, Pervasive, and Cloud Computing

GPC 2018: Green, Pervasive, and Cloud Computing pp 215–225Cite as

Estimating Origin-Destination Flows Using Radio Frequency Identification Data

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11204))

Abstract

The origin-destination (OD) demand is a critical information source used in the traffic strategic planning and management. The Radio Frequency Identification (RFID) is an advanced technique to collect traffic data. In this paper, daily origin-destination trips were inferred from the RFID data. Locations of RFID readers are considered as the origins and destinations. However, the sparseness of RFID data leads uncertainty to the destination of trip. To handle this problem, an approach was proposed to estimate the OD matrix. At first, the driving time of trip-legs in all trajectories are calculated by the driving time of taxis, which can be distinguished from the RFID data. And then, the stay, the last pass-by RFID reader of a trip, is inferred based on the calculated driving time. Finally, we extracted daily origin-destination trips for all vehicles. Using the proposed method, a case study was developed employing the real-world data collected in Chongqing, China, which demonstrated the effectiveness of our proposed approach.

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References

  1. Dixon, M.P., Rilett, L.R.: Population origin-destination estimation using automatic vehicle identification and volume data. J. Transp. Eng. ASCE 131(2), 75–82 (2005)

    Article  Google Scholar 

  2. Chen, C., Zhang, D., Guo, B., Ma, X., Pan, G., Wu, Z.: TripPlanner: personalized trip planning leveraging heterogeneous crowdsourced digital footprints. IEEE Trans. Intell. Transp. Syst. 16(3), 1259–1273 (2015)

    Article  Google Scholar 

  3. Chen, C., Zhang, D., Li, N., Zhou, Z.H.: B-planner: planning bidirectional night bus routes using large-scale taxi GPS traces. IEEE Trans. Intell. Transp. Syst. 15(4), 1451–1465 (2014)

    Article  Google Scholar 

  4. Peng, C., Jin, X., Wong, K.C., Shi, M., Liò, P.: Collective human mobility pattern from taxi trips in urban area. PLoS ONE 7(4), e34487 (2012)

    Article  Google Scholar 

  5. Pan, G., Qi, G., Wu, Z., Zhang, D., Li, S.: Land-use classification using taxi GPS traces. IEEE Trans. Intell. Transp. Syst. 14(1), 113–123 (2013)

    Article  Google Scholar 

  6. Yuan, J., Zheng, Y., Xie, X.: Discovering regions of different functions in a city using human mobility and POIs. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD 2012, p. 186. ACM Press, New York (2012)

    Google Scholar 

  7. Radio-frequency identification. https://en.wikipedia.org/wiki/Radio-frequency_identification, Accessed 16 Jan 2018

  8. Calabrese, F., Di Lorenzo, G., Liang, L., Ratti, C.: Estimating origin-destination flows using mobile phone location data. Pervasive Comput. IEEE 10(4), 36–44 (2011)

    Article  Google Scholar 

  9. Ickowicz, A., Sparks, R.: Estimation of an origin/destination matrix: application to a ferry transport data. Public Transp. 7(2), 235–258 (2015). https://doi.org/10.1007/s12469-015-0102-y

    Article  Google Scholar 

  10. Lu, M., Liang, J., Wang, Z., Yuan, X.: Exploring OD patterns of interested region based on taxi trajectories. J. Vis. 19(4), 811–821 (2016). https://doi.org/10.1007/s12650-016-0357-7

    Article  Google Scholar 

  11. Demissie, M.G., Antunes, F., Bento, C., Phithakkitnukoon, S., Sukhvibul, T.: Inferring origin-destination flows using mobile phone data: a case study of Senegal. In: 2016 13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON (2016). https://doi.org/10.1109/ECTICon.2016.7561328

  12. Alexander, L., Jiang, S., Murga, M., González, M.C.: Origin-destination trips by purpose and time of day inferred from mobile phone data. Transp. Res. C Emerg. Technol. 58, 240–250 (2015). https://doi.org/10.1016/j.trc.2015.02.018

    Article  Google Scholar 

  13. Alsger, A., Assemi, B., Mesbah, M., Ferreira, L.: Validating and improving public transport origin-destination estimation algorithm using smart card fare data. Transp. Res. C Emerg. Technol. 68, 490–506 (2016)

    Article  Google Scholar 

  14. Feng, Y., Sun, J., Chen, P.: Vehicle trajectory reconstruction using automatic vehicle identification and traffic count data. J. Adv. Transp. 49(2), 174–194 (2015). https://doi.org/10.1002/atr.1260

    Article  Google Scholar 

  15. Guo, J., Liu, Y., Li, X., Huang, W., Cao, J., Wei, Y.: Enhanced least square based dynamic OD matrix estimation using Radio Frequency Identification data. Math. Comput. Simul. (2017). https://doi.org/10.1016/j.matcom.2017.10.014

  16. Shang, J., Zheng, Y., Tong, W., Chang, E., Yu, Y.: Inferring gas consumption and pollution emission of vehicles throughout a city. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD 2014, pp. 1027–1036. ACM Press, New York (2014). https://doi.org/10.1145/2623330.2623653

  17. Wang, Y., et al.: Unlicensed taxis detection service based on large-scale vehicles mobility data. In: Proceedings of the 2017 IEEE 24th International Conference on Web Services, ICWS 2017, pp. 857–861. Institute of Electrical and Electronics Engineers Inc. (2017). https://doi.org/10.1109/ICWS.2017.106

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Authors and Affiliations

  1. Key Laboratory of Dependable Service Computing in Cyber Physical Society, Chongqing University, Ministry of Education, Chongqing, 400030, China

    Chaoxiong Chen, Linjiang Zheng, Chen Cui & Weining Liu

  2. College of Computer Science, Chongqing University, Chongqing, 400030, China

    Chaoxiong Chen, Linjiang Zheng, Chen Cui & Weining Liu

Authors
  1. Chaoxiong Chen
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  2. Linjiang Zheng
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  3. Chen Cui
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  4. Weining Liu
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Corresponding author

Correspondence to Chaoxiong Chen .

Editor information

Editors and Affiliations

  1. Zhejiang University, Hangzhou, China

    Shijian Li

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Chen, C., Zheng, L., Cui, C., Liu, W. (2019). Estimating Origin-Destination Flows Using Radio Frequency Identification Data. In: Li, S. (eds) Green, Pervasive, and Cloud Computing. GPC 2018. Lecture Notes in Computer Science(), vol 11204. Springer, Cham. https://doi.org/10.1007/978-3-030-15093-8_15

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  • DOI: https://doi.org/10.1007/978-3-030-15093-8_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15092-1

  • Online ISBN: 978-3-030-15093-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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