Bike-Repositioning Using Volunteers: Crowd Sourcing with Choice Restriction

Authors

  • Jinjia Huang Institute of Operations Research and Analytics, National University of Singapore
  • Mabel C. Chou Institute of Operations Research and Analytics, National University of Singapore
  • Chung-Piaw Teo Institute of Operations Research and Analytics, National University of Singapore

Keywords:

Optimization of Spatio-temporal Systems

Abstract

Motivated by the Bike Angels Program in New York's Citi Bike and Boston's Blue Bikes, we study the use of (registered) volunteers to re-position empty bikes for riders in a bike sharing system. We propose a method that can be used to deploy the volunteers in the system, based on the real time distribution of the bikes in different stations. To account for (random) route demand in the network, we solve a related transshipment network design model and construct a sparse structure to restrict the re-balancing activities of the volunteers (concentrating re-balancing activities on essential routes). We also develop a comprehensive simulation model using a threshold-based policy to deploy the volunteers in real time, to test the effect of choice restriction on volunteers (suitably deployed) to re-position bikes. We use the Hubway system in Boston (with 60 stations) to demonstrate that using a sparse structure to concentrate the re-balancing activities of the volunteers, instead of allowing all admissible flows in the system (as in current practice), can reduce the number of re-balancing moves by a huge amount, losing only a small proportion of demand satisfied.

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Published

2021-05-18

How to Cite

Huang, J., Chou, M. C., & Teo, C.-P. (2021). Bike-Repositioning Using Volunteers: Crowd Sourcing with Choice Restriction. Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11844-11852. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17407

Issue

Section

AAAI Technical Track on Planning, Routing, and Scheduling