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Title	Rebalancing Bike Sharing Systems Under Uncertainty Using Quantum Bayesian Networks
ID_Doc	44529
Authors	Harikrishnakumar R.; Borujeni S.E.; Ahmad S.F.; Nannapaneni S.
Year	2021
Published	Proceedings - 2021 IEEE International Conference on Quantum Computing and Engineering, QCE 2021
DOI	http://dx.doi.org/10.1109/QCE52317.2021.00078
Abstract	Smart Mobility is the key component of Smart City initiative that are being explored throughout the world. The bike-sharing system (BSS) aims to provide an alternative mode of Smart Mobility transportation system, and it is being widely adopted in urban areas. The use of bikes for short-distance travel helps to reduce traffic congestion, reduce carbon emissions, and decrease the risk of overcrowding. Effective bike sharing system operations requires rebalancing analysis, which corresponds to transferral of bikes across various bike stations to ensure the supply meets expected demand. A critical part for a bike sharing system operations is the effective management of rebalancing vehicle carrier operations that ensures bikes are restored in each station to its target value during every pick-up and drop-off operations. In this work, we present potential applications of Quantum Bayesian networks, which are quantum-equivalent to classical Bayesian networks for probabilistic rebalancing cost prediction under uncertainty. In this preliminary work, we demonstrate the proposed approach using IBM-Qiskit and compared the results classically using Netica for a case study involving rebalancing across three bike stations. © 2021 IEEE.
Author Keywords	Bike sharing system; IBM-qiskit; Quantum Bayesian network; Rebalancing; Smart mobility; Uncertainty

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