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A Practical Demonstration of a Variable Incentive Model for Bike-Sharing Systems Based on Agent-Based Social Simulation

  • Alberto López Santiago
  • Carlos A. IglesiasEmail author
  • Álvaro Carrera
Conference paper
  • 10 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12092)

Abstract

Bike-Sharing Systems (BSSs) have been implemented in numerous cities around the world to reduce the traffic generated by motorized vehicles, due to the benefits they bring to the city, such as reducing congestion or decreasing pollution generation. Caused by their impact on urban mobility, the research community has increased their interest in their study, trying to understand user behavior and improving the user experience. This demonstration shows the simulator developed to analyze the impact of a variable incentive model for BSSs based on Agent-based Social Simulation. The model has been developed using data collected directly from BiciMad, the BSS of the city of Madrid, Spain. The developed simulator uses OpenStreetMaps as a route generator software. The simulated scenario for this demonstration consists of a 7-day series of simulations with different traffic flows to observe the impact of different policies according to different traffic intensity.

Keywords

Bike Sharing Systems Variable incentive model Agent-based systems 

Notes

Acknowledgments

This research has been funded by the UPM University-Industry Chair Cabify for Sustainable Mobility. The authors want also to thank EMT for providing BiciMad service data.

References

  1. 1.
    Ban, S., Hyun, K.H.: Designing a user participation-based bike rebalancing service. Sustainability 11(8), 2396 (2019)CrossRefGoogle Scholar
  2. 2.
    Santiago, A.L., Iglesias, C.A., Carrera, A.: Improving sustainable mobility with a variable incentive model for bike sharing systems based on agent-based social simulation. In: Advances in Practical Applications of Agents, Multi-agent Systems, and Trustworthiness: The PAAMS Collection (2020)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Intelligent Systems GroupUniversidad Politécnica de MadridMadridSpain

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