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Design of intelligent carpooling program based on big data analysis and multi-information perception

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Abstract

Carpool platform provides users with efficient service by making full use of the accurate mass data, which plays an important role in promoting carpool travel. The program builds a carpool web platform and mobile client. The backstage comprehensively uses GPS, GSM, WIFI and RFID technology of the internet of things to perceive the exact the user’s position information and realizes to monitor and manage user action trajectory in order to ensure the efficiency and security of carpool. The system is connected with the Amap interface to notify the real-time road condition and the information of the surrounding parking. Based on big data analysis, it also proposes data collaboration to eliminate the effect of data differences from mobile client and web platform, retrieve and filter valuable carpool information and recommend extra information based on carpool travel records. The scheme builds a real-time carpool module based on fixed time and route to meet the uncertain demands. The experimental results show that the driving time and distance of carpool could be saved by 25.7 and 12.4% respectively, which has preliminarily realized the intelligent, simple, flexible, efficient, convenient, economical and safe carpool with the aid of intelligent algorithm.

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References

  1. Wang, Y.Z., Jin, X.L., Cheng, X.Q.: Network big data: present and future. Chin. J. Comput. 36(6), 1125–1138 (2013)

    Article  Google Scholar 

  2. Zhang, Y., Chen, M., Liao, X.F.: Big data applications: a survey. J. Comput. Res. Dev. 50(S2), 216–233 (2013)

    Google Scholar 

  3. Naor, M.: On fairness in the carpool problem. J. Algorithm 55(1), 93–98 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  4. Transport Canada: Carpool trends in Canada and abroad. http://publications.gc.ca/site/fra/427302/publication.htm (2013)

  5. Callaghan, M.J., Gormley, P., McBride, M., Harkin, J., McGinnity, T.M.: Internal location based services using wireless sensor networks and RFID technology. Int. J. Comput. Sci. Netw. Secur. 6(4), 108–113 (2006)

    Google Scholar 

  6. Wang, Z.: The application of Google Maps API in the carpool system. Master Dissertation, China University of Science and Technology (2013)

  7. Tian, Z.Y.: Design and realization of real-time carpool system based on Android. Master Dissertation, Huazhong University of Science and Technology (2007)

  8. Potgantwar, A.D., Wadhai, V.M.: Improved indoor positioning using RSS and directional antenna integrating with RFID and wireless technology. In: Proceedings of International Conference on ICT for Sustainable Development. Springer, Singapore (2016)

  9. Poad, F.A., Ismail, W.: An Active Integrated Zigbee RFID System with GPS Functionalities for Location Monitoring Utilizing Wireless Sensor Network and GSM Communication Platform. Transactions on Engineering Technologies. Springer, Netherlands (2015)

    Book  Google Scholar 

  10. Intae, R., Wonshik, N., Seokhoon, K.: Information exchange architecture based on software defined networking for cooperative intelligent transportation systems. Clust. Comput. 18(2), 771–782 (2015)

    Article  Google Scholar 

  11. Fang, Z., Zhao, Z., Guo, P.: Analysis of distance measurement based on RSSI. J. Sens. Technol. 20(11), 2526–2530 (2007)

    Google Scholar 

  12. Zhou, G., Liu, Z., Shu, W., Bao, T., Mao, L., Wu, D., et al.: Smart savings on private car pooling based on internet of vehicles. J. Intell. Fuzzy Syst. 32(5), 1–12 (2017)

    Google Scholar 

  13. Xu, F.: A study on the application based on 3G mobile phone carpool of private car. Electron. World 10, 28–29 (2012)

    Google Scholar 

  14. Zhang, K., Lu, J., Sun, Y.: The design of an intelligent carpool-matching system based on LBS-Cloud service. Appl. Electron. Tech. 39(8), 22–32 (2013)

    Google Scholar 

  15. Liu. J.: Design and implementation of taxi pooling system based on Android. Doctoral Dissertation, Xiamen University (2014)

  16. Magadevi, N., Kumar, V.J.S.: Energy efficient, obstacle avoidance path planning trajectory for localization in wireless sensor network. Clust Comput. 02(5), 1–7 (2017)

    Google Scholar 

  17. Antonis, M., Eggers, P., Ponnekanti, S.: Wireless personal communications special issue on cellular and wireless location based technologies and services. Wirel. Pers. Commun. 26(2), 281–282 (2003)

    Article  Google Scholar 

  18. Kaiser, T., Oppermann, I., Porcino, D.: Wireless location technologies and applications. EURASIP J. Adv. Signal Process. 1, 1–3 (2006)

    Google Scholar 

  19. Zhang, Q.H.: Search and application of cooperative technology between WebGIS and MobileGIS. Master Dissertation, Ocean University of China (2013)

  20. Vishnu, V.M., Rajalakshmi, M.: Intelligent traffic video surveillance and accident detection system with dynamic traffic signal control. Clust. Comput. 06(1), 1–13 (2017)

    Google Scholar 

  21. Zhang, C., Song, X.R.: Research on accuracy of distance measurement method based on RSSI. J. Hunan Univ. Technol. 25(5) (2011)

  22. Lu, X.J., Guo, L., Chen, Z.R., Lin, Y.: Study on vehicle detection and tracking algorithm based on appearance and motion. Comput. Eng. 24(08), 152–157 (2014)

    Google Scholar 

  23. Zhou, G.L., Huang, K., Mao, L.N., Zhu, Y.R.: Realization and evaluation of commuting carpool program based on fixed time and route: a case study of Huaian. Transp. Inf. Saf. 32(4), 41–45 (2014)

    Google Scholar 

  24. Sun, X.Q.: Research on the problem of vehicle carpool matching. Unpublished Master thesis, Shandong Normal University (2012)

Download references

Acknowledgements

This research was supported by the open fund for Jiangsu key laboratory of traffic and transportation security (Huaiyin Institute of Technology) (TTS2016-06), Graduate Innovative Projects of Jiangsu Province (KYLX_1059, KYLX15_0148), Youth Foundation of Huaiyin Institute of Technology (HGC1408), the National Natural Science Foundation of China (51408252, 51408253), Jiangsu Government Scholarship for Overseas Studies (JS-2016-K009), Key Social Development Research Project of Huai’an (HASZ201638). We wish to thank the anonymous reviewers who helped to improve the quality of the paper.

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Correspondence to Guiliang Zhou.

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Zhou, G., Lv, M., Bao, T. et al. Design of intelligent carpooling program based on big data analysis and multi-information perception. Cluster Comput 22 (Suppl 1), 521–532 (2019). https://doi.org/10.1007/s10586-017-1274-9

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