Advertisement

A Bike Sharing System Simulator

  • Alberto Fernández
  • Sandra Timón
  • Carlos Ruiz
  • Tao Cumplido
  • Holger Billhardt
  • Jürgen Dunkel
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 887)

Abstract

Bike-sharing systems are becoming very popular in big cities. They provide a cheap and green mean of transportation used for commuting and leisure. Being a shared limited resource, it is common to reach imbalanced situations where some stations have either no bikes or only empty slots, thus decreasing the performance of the system. To solve such situations, trucks are typically used to move bikes among stations in order to reach a more homogeneous distribution. Recently, research works are focusing on a complementary action to reduce imbalances consisting in incentivizing users to take (or return) bikes from stations with many bikes rather than those with few bikes, e.g. by fare discounts. In this paper, we present simulator for analyzing bike-sharing systems. Several user generation distributions can be configured. The simulator is specifically designed with the aim of evaluating incentive-based rebalancing strategies. The paper describes in detail the characteristics and potential of the simulator, including several experiments.

Keywords

Bike sharing Simulator Smart transportation 

Notes

Acknowledgments

Work partially supported by the Autonomous Region of Madrid (grant “MOSI-AGIL-CM” (S2013/ICE-3019) co-funded by EU Structural Funds FSE and FEDER), project “SURF” (TIN2015-65515-C4-4-R (MINECO/FEDER)) funded by the Spanish Ministry of Economy and Competitiveness, and through the Excellence Research Group GES2ME (Ref. 30VCPIGI05) co-funded by URJC-Santander Bank.

References

  1. 1.
    Pal, A., Zhang, Y.: Free-floating bike sharing: solving real-life large-scale static rebalancing problems. Transp. Res. Part C Emerg. Technol. 80, 92–116 (2017)CrossRefGoogle Scholar
  2. 2.
    Erdoğan, G., Battarra, M., Calvo, R.W.: An exact algorithm for the static rebalancing problem arising in bicycle sharing systems. Eur. J. Oper. Res. 245(3), 667–679 (2015)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Forma, I.A., Raviv, T., Tzur, M.: A 3-step math heuristic for the static repositioning problem in bike-sharing systems. Transp. Res. Part B Methodol. 71, 230–247 (2015)CrossRefGoogle Scholar
  4. 4.
    Contardo, C., Morency, C., Rousseau, L.M.: Balancing a dynamic public bike-sharing system. Technical report, vol. 4. CIRRELT (2012)Google Scholar
  5. 5.
    O’Mahony, E., Shmoys, D.B.: Data analysis and optimization for (citi) bike sharing. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 687–694. AAAI Press (2015)Google Scholar
  6. 6.
    Schuijbroek, J., Hampshire, R.C., Van Hoeve, W.J.: Inventory rebalancing and vehicle routing in bike sharing systems. Eur. J. Oper. Res. 257(3), 992–1004 (2017)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Chemla, D., Meunier, F., Pradeau, T., Calvo, R.W., Yahiaoui, H.: Self-service bike sharing systems: simulation, repositioning, pricing (2013). https://hal.archives-ouvertes.fr/hal-00824078
  8. 8.
    Fricker, C., Gast, N.: Incentives and regulations in bike-sharing systems with stations of finite capacity. arXiv preprint arXiv:12011178 (2012)
  9. 9.
    Pfrommer, J., Warrington, J., Schildbach, G., Morari, M.: Dynamic vehicle redistribution and online price incentives in shared mobility systems. IEEE Trans. Intel. Transp. Syst. 15(4), 1567–1578 (2014)CrossRefGoogle Scholar
  10. 10.
    Waserhole, A., Jost, V.: Pricing in vehicle sharing systems: optimization in queuing networks with product forms OSP 2012. <hal-00751744v5> (2014)Google Scholar
  11. 11.
    Romero, J.P., Moura, J.L., Ibeas, A., Alonso, B.: A simulation tool for bicycle sharing systems in multimodal networks. Transp. Plan. Technol. 38(6), 646–663 (2015)CrossRefGoogle Scholar
  12. 12.
    Reiss, S., Bogenberger, K.: Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy. In: IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), pp. 2613–2618 (2016)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Alberto Fernández
    • 1
  • Sandra Timón
    • 1
  • Carlos Ruiz
    • 1
  • Tao Cumplido
    • 2
  • Holger Billhardt
    • 1
  • Jürgen Dunkel
    • 2
  1. 1.CETINIAUniversity Rey Juan CarlosMadridSpain
  2. 2.Computer Science DepartmentHochschule HannoverHanoverGermany

Personalised recommendations