A modeling framework for the dynamic management of free-floating bike-sharing systems

作者：Caggiani, Leonardo; Camporeale, Rosalia; Ottomanelli, Michele^*; Szeto, Wai Yuen

来源：Transportation Research Part C: Emerging Technologies , 2018, 87: 159-182.

DOI：10.1016/j.trc.2018.01.001

• Free-floating bike sharing systems
• Spatio-temporal clustering
• Non-linear autoregressive neural network forecasting
• Decision Support System
• Dynamic fleet relocation

Given the growing importance of bike-sharing systems nowadays, in this paper we suggest an alternative approach to mitigate the most crucial problem related to them: the imbalance of bicycles between zones owing to one-way trips. In particular, we focus on the emerging free-floating systems, where bikes can be delivered or picked-up almost everywhere in the network and not just at dedicated docking stations. We propose a new comprehensive dynamic bike redistribution methodology that starts from the prediction of the number and position of bikes over a system operating area and ends with a relocation Decision Support System. The relocation process is activated at constant gap times in order to carry out dynamic bike redistribution, mainly aimed at achieving a high degree of user satisfaction and keeping the vehicle repositioning costs as low as possible. An application to a test case study, together with a detailed sensitivity analysis, shows the effectiveness of the suggested novel methodology for the real-time management of the free-floating bike-sharing systems.

• 出版日期2018-2
• 单位香港大学深圳研究院