User-Based Relocation of Stackable Car Sharing

  • Haitam LaarabiEmail author
  • Chiara Boldrini
  • Raffaele Bruno
  • Helen Porter
  • Peter Davidson
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 921)


The relocation of carsharing vehicles is one of the main challenges facing its economic viability, in addition to the operational costs and infrastructure deployment. In this paper, we take advantage of an innovative technological proposal of a one-way carsharing system, to test and validate a user-based relocation strategy. The new technology allows vehicles to be driven in a road train by either an operator (up until eight vehicles) or a customer (up to two). The proposed strategy encourages a customer to take a second vehicle along the way, when he/she happens to be moving from a station with excess of vehicles, to a deficient station. As a case study, we have considered a suburban area of the city of Lyon, of which we have a 2015 household travel survey to build a synthetic population undertaking various activities during a day. Then, we inject this population in a detailed multi-agent and multi-modal transport simulation model, to compare the relocation performance of a lower/upper-bound availability algorithm with three other naively intuitive algorithms. The study shows that: (i) relocation algorithm is very sensitive to the ratio of parking slots to fleet size, and (ii) with the right infrastructure we can relocate one vehicle and generate at least one additional trip.


Carsharing User-based relocation Multi-agent traffic simulation Stackable vehicles Electric vehicles 



This work has been partially funded by the ESPRIT project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 653395.


  1. 1.
    de Almeida Correia, G.H., Antunes, A.P.: Optimization approach to depot location and trip selection in one-way carsharing systems. Transp. Res. Part E: Logist. Transp. Rev. 48(1), 233–247 (2012)CrossRefGoogle Scholar
  2. 2.
    Balmer, M., Cetin, N., Nagel, K., Raney, B.: Towards truly agent-based traffic and mobility simulations. In: Proceedings of AAMS 2004, pp. 60–67. IEEE Computer Society (2004)Google Scholar
  3. 3.
    Barth, M., Shaheen, S.: Shared-use vehicle systems: framework for classifying carsharing, station cars, and combined approaches. Transp. Res. Rec.: J. Transp. Res. Board 1791, 105–112 (2002)CrossRefGoogle Scholar
  4. 4.
    Barth, M., Todd, M.: Simulation model performance analysis of a multiple station shared vehicle system. Transp. Res. Part C: Emerg. Technol. 7(4), 237–259 (1999)CrossRefGoogle Scholar
  5. 5.
    Barth, M., Todd, M., Xue, L.: User-based vehicle relocation techniques for multiple-station shared-use vehicle systems (2004)Google Scholar
  6. 6.
    Biondi, E., Boldrini, C., Bruno, R.: Optimal deployment of stations for a car sharing system with stochastic demands: a queueing theoretical perspective. In: The 19th IEEE Intelligent Transportation Systems Conference, pp. 1–7. IEEE (2016)Google Scholar
  7. 7.
    Birnschein, T., Kirchner, F., Girault, B., Yüksel, M., Machowinski, J.: An innovative, comprehensive concept for energy efficient electric mobility-EO smart connecting car. In: Proceedings of IEEE ENERGYCON 2012, pp. 1028–1033. IEEE (2012)Google Scholar
  8. 8.
    Boldrini, C., Bruno, R., Conti, M.: Characterising demand and usage patterns in a large station-based car sharing system. In: The 2nd IEEE INFOCOM Workshop on Smart Cities and Urban Computing (2016)Google Scholar
  9. 9.
    Bonsall, P.: Microsimulation: its application to car sharing. Transp. Res. Part A: Gen. 16(5), 421–429 (1982)CrossRefGoogle Scholar
  10. 10.
    Boyacı, B., Zografos, K.G., Geroliminis, N.: An optimization framework for the development of efficient one-way car-sharing systems. Eur. J. Oper. Res. 240(3), 718–733 (2015)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Ciari, F., Schuessler, N., Axhausen, K.W.: Estimation of carsharing demand using an activity-based microsimulation approach: model discussion and some results. Int. J. Sustain. Transp. 7(1), 70–84 (2013)CrossRefGoogle Scholar
  12. 12.
    Clemente, M., Fanti, M.P., Mangini, A.M., Ukovich, W.: The vehicle relocation problem in car sharing systems: modeling and simulation in a petri net framework. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 250–269. Springer, Heidelberg (2013). Scholar
  13. 13.
    ESPRIT: Esprit h2020 eu project - easily distributed personal rapid transit (2015). Accessed 12 Dec 2016
  14. 14.
    Farahani, R.Z., Asgari, N., Heidari, N., Hosseininia, M., Goh, M.: Covering problems in facility location: a review. Comput. Indus. Eng. 62, 368–407 (2012)CrossRefGoogle Scholar
  15. 15.
    Febbraro, A., Sacco, N., Saeednia, M.: One-way carsharing: solving the relocation problem. Transp. Res. Rec.: J. Transp. Res. Board 2319, 113–120 (2012)CrossRefGoogle Scholar
  16. 16.
    George, D.K., Xia, C.H.: Fleet-sizing and service availability for a vehicle rental system via closed queueing networks. Eur. J. Oper. Res. 211(1), 198–207 (2011)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Hampshire, R., Gaites, C.: Peer-to-peer carsharing: market analysis and potential growth. Transp. Res. Rec.: J. Transp. Res. Board 2217, 119–126 (2011)CrossRefGoogle Scholar
  18. 18.
    Herrmann, S., Schulte, F., Voß, S.: Increasing acceptance of free-floating car sharing systems using smart relocation strategies: a survey based study of car2go Hamburg. In: González-Ramírez, R.G., Schulte, F., Voß, S., Ceroni Díaz, J.A. (eds.) ICCL 2014. LNCS, vol. 8760, pp. 151–162. Springer, Cham (2014). Scholar
  19. 19.
    Jorge, D., Correia, G.H., Barnhart, C.: Comparing optimal relocation operations with simulated relocation policies in one-way carsharing systems. IEEE Trans. Intell. Transp. Syst. 15(4), 1667–1675 (2014)CrossRefGoogle Scholar
  20. 20.
    Kek, A., Cheu, R., Chor, M.: Relocation simulation model for multiple-station shared-use vehicle systems. Transp. Res. Rec.: J. Transp. Res. Board 1986, 81–88 (2006)CrossRefGoogle Scholar
  21. 21.
    Kek, A.G., Cheu, R.L., Meng, Q., Fung, C.H.: A decision support system for vehicle relocation operations in carsharing systems. Transp. Res. Part E: Logist. Transp. Rev. 45(1), 149–158 (2009)CrossRefGoogle Scholar
  22. 22.
    Laarabi, H.M., Boldrini, C., Bruno, R., Davidson, H.P., Peter: on the performance of a one-way car sharing system in suburban areas: a real-world use case. In: 3rd International Conference on Vehicle Technology and Intelligent Transport Systems, vol. 1, pp. 102–110. Scitepress (2017)Google Scholar
  23. 23.
    Laarabi, M.H., Bruno, R.: A generic software framework for carsharing modelling based on a large-scale multi-agent traffic simulation platform. In: Namazi-Rad, M.-R., Padgham, L., Perez, P., Nagel, K., Bazzan, A. (eds.) ABMUS 2016. LNCS (LNAI), vol. 10051, pp. 88–111. Springer, Cham (2017). Scholar
  24. 24.
    Mitchell, W.J., Borroni-Bird, C.E., Burns, L.D.: Reinventing the Automobile: Personal Urban Mobility for the 21st Century. MIT Press, Cambridge (2010)Google Scholar
  25. 25.
    Nair, R., Miller-Hooks, E.: Fleet management for vehicle sharing operations. Transp. Sci. 45(4), 524–540 (2011)CrossRefGoogle Scholar
  26. 26.
    Pavone, M., Smith, S.L., Frazzoli, E., Rus, D.: Robotic load balancing for mobility-on-demand systems. Int. J. Robot. Res. 31(7), 839–854 (2012)CrossRefGoogle Scholar
  27. 27.
    Uesugi, K., Mukai, N., Watanabe, T.: Optimization of vehicle assignment for car sharing system. In: Apolloni, B., Howlett, R.J., Jain, L. (eds.) KES 2007. LNCS (LNAI), vol. 4693, pp. 1105–1111. Springer, Heidelberg (2007). Scholar
  28. 28.
    Vairani, F.: bitCar: design concept for a collapsible stackable city car. Ph.D. thesis, Massachusetts Institute of Technology (2009)Google Scholar
  29. 29.
    Weikl, S., Bogenberger, K.: Relocation strategies and algorithms for free-floating car sharing systems. IEEE Intell. Transp. Syst. Mag. 5(4), 100–111 (2013)CrossRefGoogle Scholar
  30. 30.
    Zhang, R., Pavone, M.: Control of robotic mobility-on-demand systems: a queueing-theoretical perspective. Int. J. Robot. Res. 35(1–3), 186–203 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Haitam Laarabi
    • 1
    Email author
  • Chiara Boldrini
    • 1
  • Raffaele Bruno
    • 1
  • Helen Porter
    • 2
  • Peter Davidson
    • 2
  1. 1.Institute for Informatics and Telematics (IIT) Italian National Research Council (CNR)PisaItaly
  2. 2.Peter Davidson Consultancy (PDC)BerkhamstedEngland

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