Skip to main content
SpringerLink
Log in

A Graph Matching Based Method for Dynamic Passenger-Centered Ridesharing

  • Conference paper
  • First Online:
Database and Expert Systems Applications (DEXA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10438))

Included in the following conference series:

  • 1274 Accesses

Abstract

Ridesharing is one transportation service deeply influenced by the prosperity of Mobile Internet. Existing work focuses on passenger-vehicle matching, which considers how to optimally dispatch passengers to appropriate vehicles. While dynamic passenger-passenger matching addresses how to optimally handle continually-arriving requests for ridesharing from passengers, without considering vehicles. It is a kind of dynamic passenger-centered ridesharing that has not been studied enough. This paper studies dynamic passenger-centered ridesharing with both temporal and cost constraints. We first propose a ridesharing request matching method based on maximum weighted matching on undirected weighted graphs, aiming to minimize the overall travel distance of targeting passengers. We then devise a distance indexing strategy to prune unnecessary calculations to accelerate ridesharing request matching and reduce request response time. Experiments on real-life road networks indicate that our method can successfully match 90% of ridesharing requests while saving 23% to 35% of travel distance.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.openstreetmap.org/.

References

  1. Agatz, N., Erera, A., Savelsbergh, M., Wang, X.: Optimization for dynamic ride-sharing: a review. Eur. J. Oper. Res. 223(2), 295–303 (2012)

    Article  MATH  Google Scholar 

  2. Amey, A.: Proposed methodology for estimating rideshare viability within an organization: application to the mit community. In: Proceedings of Transportation Research Board Annual Meeting, pp. 1–16 (2011)

    Google Scholar 

  3. Attanasio, A., Cordeau, J.F., Ghiani, G., Laporte, G.: Parallel tabu search heuristics for the dynamic multi-vehicle dial-a-ride problem. Parallel Comput. 30(3), 377–387 (2004)

    Article  Google Scholar 

  4. Baldacci, R., Maniezzo, V., Mingozzi, A.: An exact method for the car pooling problem based on lagrangean column generation. Oper. Res. 52(3), 422–439 (2004)

    Article  MATH  Google Scholar 

  5. Calvo, R.W., De Luigi, F., Haastrup, P., Maniezzo, V.: A distributed geographic information system for the daily car pooling problem. Comput. Oper. Res. 31(13), 2263–2278 (2004)

    Article  MATH  Google Scholar 

  6. Cici, B., Markopoulou, A., Frias-Martinez, E., Laoutaris, N.: Assessing the potential of ride-sharing using mobile and social data: a tale of four cities. In: Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 201–211 (2014)

    Google Scholar 

  7. Donovan, B., Work, D.B.: Using coarse GPS data to quantify city-scale transportation system resilience to extreme events. Comput. Sci. (2015)

    Google Scholar 

  8. Duan, X., Jin, C., Wang, X., Zhou, A., Yue, K.: Real-time personalized taxi-sharing. In: Navathe, S.B., Wu, W., Shekhar, S., Du, X., Wang, X.S., Xiong, H. (eds.) DASFAA 2016. LNCS, vol. 9643, pp. 451–465. Springer, Cham (2016). doi:10.1007/978-3-319-32049-6_28

    Chapter  Google Scholar 

  9. Edmonds, J.: Paths, trees, and flowers. Can. J. Math. 17(3), 361–379 (2009)

    MathSciNet  Google Scholar 

  10. Francis, P., Jamin, S., Jin, C., Jin, Y., Raz, D., Shavitt, Y., Zhang, L.: IDMaps: a global internet host distance estimation service. IEEE/ACM Trans. Netw. 9(5), 525–540 (2001)

    Article  Google Scholar 

  11. Furuhata, M., Dessouky, M., Ordez, F., Brunet, M.E., Wang, X., Koenig, S.: Ridesharing: the state-of-the-art and future directions. Transp. Res. Part B Methodol. 57(57), 28–46 (2013)

    Article  Google Scholar 

  12. Galil, Z.: Efficient algorithms for finding maximum matching in graphs. ACM Comput. Surv. (CSUR) 18(1), 23–38 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  13. Geisberger, R., Luxen, D., Neubauer, S., Sanders, P., Volker, L.: Fast detour computation for ride sharing. Comput. Sci. (2009)

    Google Scholar 

  14. Herbawi, W., Weber, M.: Evolutionary multiobjective route planning in dynamic multi-hop ridesharing. In: Merz, P., Hao, J.-K. (eds.) EvoCOP 2011. LNCS, vol. 6622, pp. 84–95. Springer, Heidelberg (2011). doi:10.1007/978-3-642-20364-0_8

    Chapter  Google Scholar 

  15. Herbawi, W., Weber, M.: Modeling the multihop ridematching problem with time windows and solving it using genetic algorithms. In: Proceedings of the IEEE International Conference on Tools with Artificial Intelligence, pp. 89–96 (2012)

    Google Scholar 

  16. Herbawi, W., Weber, M.: The ridematching problem with time windows in dynamic ridesharing: a model and a genetic algorithm. In: Proceedings of the ACM Genetic and Evolutionary Computation Conference, pp. 1–8 (2012)

    Google Scholar 

  17. Ma, S., Zheng, Y., Wolfson, O.: T-share: a large-scale dynamic taxi ridesharing service. In: Proceedings of the IEEE International Conference on Data Engineering, pp. 410–421 (2013)

    Google Scholar 

  18. Potamias, M., Bonchi, F., Castillo, C., Gionis, A.: Fast shortest path distance estimation in large networks. In: Proceedings of the ACM Conference on Information and Knowledge Management, pp. 867–876 (2009)

    Google Scholar 

  19. Pyrga, E., Schulz, F., Wagner, D., Zaroliagis, C.: Efficient models for timetable information in public transportation systems. J. Exp. Algorithmics 12(1), 2–4 (2008)

    MathSciNet  MATH  Google Scholar 

  20. Qiao, M., Cheng, H., Chang, L., Yu, J.X.: Approximate shortest distance computing: a query-dependent local landmark scheme. IEEE Trans. Knowl. Data Eng. 26(1), 55–68 (2013)

    Article  Google Scholar 

  21. Qiao, M., Cheng, H., Yu, J.X.: Querying shortest path distance with bounded errors in large graphs. In: Bayard Cushing, J., French, J., Bowers, S. (eds.) SSDBM 2011. LNCS, vol. 6809, pp. 255–273. Springer, Heidelberg (2011). doi:10.1007/978-3-642-22351-8_16

    Chapter  Google Scholar 

  22. Santos, D.O., Xavier, E.C.: Dynamic taxi and ridesharing: a framework and heuristics for the optimization problem. In: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 2885–2891 (2013)

    Google Scholar 

Download references

Acknowledgement

This work was supported by the Key Projects of Fundamental Research Program of Science and Technology Commission of Shanghai Municipality (STCSM) (No. 14JC1400300), Program of Science and Technology Innovation Action of STCSM (No. 17511105204), and China Postdoctoral Science Foundation. Jihong Guan was supported by NSFC (No. 61373036) and the Program of Shanghai Subject Chief Scientist (No. 15XD1503600).

Author information

Authors and Affiliations

  1. School of Computer Science, and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, 200433, China

    Jia Shi, Yifeng Luo & Shuigeng Zhou

  2. Department of Computer Science and Technology, Tongji University, Shanghai, 201804, China

    Jihong Guan

Authors
  1. Jia Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yifeng Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shuigeng Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jihong Guan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shuigeng Zhou .

Editor information

Editors and Affiliations

  1. University of Lyon, Villeurbanne, France

    Djamal Benslimane

  2. University of Milan, Milan, Italy

    Ernesto Damiani

  3. University of Michigan, Dearborn, Michigan, USA

    William I. Grosky

  4. Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  5. Wright State University, Dayton, Ohio, USA

    Amit Sheth

  6. Johannes Kepler University, Linz, Austria

    Roland R. Wagner

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Shi, J., Luo, Y., Zhou, S., Guan, J. (2017). A Graph Matching Based Method for Dynamic Passenger-Centered Ridesharing. In: Benslimane, D., Damiani, E., Grosky, W., Hameurlain, A., Sheth, A., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2017. Lecture Notes in Computer Science(), vol 10438. Springer, Cham. https://doi.org/10.1007/978-3-319-64468-4_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-64468-4_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64467-7

  • Online ISBN: 978-3-319-64468-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation