A Campus Carpooling System Based on GPS Trajectories

  • Xuesong Wang
  • Yizhi LiuEmail author
  • Zhengtao Jiang
  • You Peng
  • Tianhao Yin
  • Zhuhua Liao
  • Jingqiang Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11637)


College students are special because they relatively have tighter in economy but have greater consistency in leisure time. They prefer to go out together with schoolfellows due to higher trusts and closeness. Moreover, the electronic map is difficult to be updated. Campus-roads recently are updated rapidly. And many alleys in campuses are not shown in the electronic map. Therefore, we devise and implement a campus carpooling system based on GPS trajectories. It includes three parts. Firstly, the campus road network is extracted based on GPS trajectories. Next, the shortest sharing path in the campus is computed in terms of the campus road network. Then, passengers are matched automatically by the carpooling matching algorithm (CMA) in our system. Experiments show that our system is able to provide a safer and more comfortable carpooling experience for college students.


Trajectory mining Campus carpooling Road network extraction Carpooling matching algorithm (CMA) The shortest sharing path 



This work is supported by National Nature Science Foundation of China (Grant No. 41871320); the Provincial and Municipal Joint Fund of Hunan Provincial Natural Science Foundation of China (Grant No. 2018JJ4052); Hunan Provincial Natural Science Foundation of China (Grant No. 2017JJ2099 and 2017JJ2081); Hunan Provincial Education Department of China (Grant No. 18B200, 17C0646, and 10C0688); Undergraduate Scientific Research Innovation Plan of Hunan University of Science and Technology (Grant No. SYZ2018042).


  1. 1.
    Chen, L., et al.: Price-and-time-aware dynamic ridesharing. In: IEEE 34th International Conference on Data Engineering (ICDE), Paris, France, pp. 1061–1072 (2018)Google Scholar
  2. 2.
    Bozdog, N., Makkes, M., Halteren, A., Bal, H.: RideMatcher: peer-to-peer matching of passengers for efficient ridesharing. In: 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), Washington, DC, USA, pp. 263–272 (2018)Google Scholar
  3. 3.
    Madria, S., Yeung, S., Ward, K.: Ridesharing-inspired trip recommendations. In: 19th IEEE International Conference on Mobile Data Management (MDM), Aalborg, Denmark, pp. 34–39 (2018)Google Scholar
  4. 4.
    He, W., Hwang, K., Li, D.: Intelligent carpool routing for urban ridesharing by mining GPS trajectories. IEEE Trans. Intell. Transp. Syst. 15(5), 2286–2296 (2014)CrossRefGoogle Scholar
  5. 5.
    Jiau, M.K., Huang, S.C.: Services-oriented computing using the compact genetic algorithm for solving the carpool services problem. IEEE Trans. Intell. Transp. Syst. 16(5), 2711–2722 (2015)CrossRefGoogle Scholar
  6. 6.
    Huang, S.C., Jiau, M.K., Lin, C.H.: A genetic-algorithm-based approach to solve carpool service problems in cloud computing. IEEE Trans. Intell. Transp. Syst. 16(1), 352–364 (2015)CrossRefGoogle Scholar
  7. 7.
    Huang, S.C., Jiau, M.K., Lin, C.H.: Optimization of the carpool service problem via a fuzzy controlled genetic algorithm. IEEE Trans. Fuzzy Syst. 23(5), 1698–1712 (2014)CrossRefGoogle Scholar
  8. 8.
    Ma, S., Zheng, Y., Wolfson, O.: Real-time city-scale taxi ridesharing. IEEE Trans. Knowl. Data Eng. 27(7), 1782–1795 (2014)CrossRefGoogle Scholar
  9. 9.
    Luo, X.: Regional transfer service based on taxi carpooling. Sun Yat-Sen University (2015). (in Chinese)Google Scholar
  10. 10.
    Nie, C., Tang, D., Xu, T.: Research on taxi mixing scheduling mode based on calling platform. J. Wuhan Univ. Technol. (Transp. Sci. Eng.) 39(04), 807–809 (2015). (in Chinese)Google Scholar
  11. 11.
    Huang, Y., Favyen, B., Jin, R., Wang, X.S.: Large scale realtime ridesharing with service guarantee on road networks. In: Proceedings of the 40th International Conference on Very Large Data Bases, Hangzhou, China, vol. 7, no. 14 (2014)CrossRefGoogle Scholar
  12. 12.
    Zhang, D., He, T., Zhang, F., et al.: Carpooling service for large-scale taxicab networks. ACM Trans. Sensor Netw. 12(3), Article 18 (2016)CrossRefGoogle Scholar
  13. 13.
    Liu, Y., Liu, J., Liao, Z., Tang, M., Chen, J.: Recommending a personalized sequence of pick-up points. J. Comput. Sci. 28, 382–388 (2018)CrossRefGoogle Scholar
  14. 14.
    Zhang, M., Liu, J., Liu, Y., Hu, Z., Yi, L.: Recommending pick-up points for taxi-drivers based on spatio-temporal clustering. In: Proceedings of the 2nd International Conference on Cloud and Green Computing (CGC 2012), pp. 67–72 (2012)Google Scholar
  15. 15.
    Zhang, J., Liao, Z., Liu, Y.: Fusing geographic information into latent factor model for pick-up region recommendation. In: Proceedings of 6th IEEE International Workshop on Mobile Multimedia Computing in conjunction with ICME 2019, Shanghai, China (2019)Google Scholar
  16. 16.
    Blerim, C., Athina, M., Nikolaos, L.: SORS: a scalable online ridesharing system. In: IWCTS 2016, Burlingame, CA, USA (2016)Google Scholar
  17. 17.
    Hong, O.Y., Liu, J.X., Liu, Y.Z.: Road network extraction method based on walking GPS trajectory. J. Comput. Mod. 222(2), 124–128 (2014). (in Chinese)MathSciNetGoogle Scholar
  18. 18.
    Li, H., Liu, J., Liu, Y., Jin, L.: Evaluating roving patrol effectiveness by GPS trajectory. In: DASC 2011, pp. 832–837 (2011)Google Scholar
  19. 19.
    Zhang, L., Thiemann, F., Sester, M.: Integration of GPS traces with road map. In: Proceedings of the Second International Workshop on Computational Transportation Science, pp. 17–22. ACM (2010)Google Scholar
  20. 20.
    Liu, X., Zhu, Y., Wang, Y.: Road recognition using coarse-grained vehicular traces. Technical report HPL-2012-26, HP Labs (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Xuesong Wang
    • 1
    • 2
  • Yizhi Liu
    • 1
    • 2
    Email author
  • Zhengtao Jiang
    • 1
  • You Peng
    • 1
  • Tianhao Yin
    • 1
  • Zhuhua Liao
    • 1
    • 2
  • Jingqiang Zhao
    • 3
  1. 1.School of Computer Science and EngineeringHunan University of Science and TechnologyXiangtanChina
  2. 2.Key Laboratory of Knowledge Processing and Networked Manufacturing in Hunan ProvinceXiangtanChina
  3. 3.Network Information CenterHunan University of Science and TechnologyXiangtanChina

Personalised recommendations