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

被引:209
作者
Caggiani, Leonardo [1 ]
Camporeale, Rosalia [1 ]
Ottomanelli, Michele [1 ]
Szeto, Wai Yuen [2 ,3 ]
机构
[1] Polytech Univ Bari, Dept Civil Environm Land Bldg Engn & Chem DICATEC, Viale Orabona 4, I-70125 Bari, Italy
[2] Univ Hong Kong, Dept Civil Engn, Rm 618,Halting Wong Bldg, Pokfulam, Hong Kong, Peoples R China
[3] Univ Hong Kong, Shenzhen Inst Res & Innovat, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
Free-floating bike sharing systems; Spatio-temporal clustering; Non-linear autoregressive neural network forecasting; Decision Support System; Dynamic fleet relocation; STATIC REPOSITIONING PROBLEM; REBALANCING PROBLEM; FLOW PREDICTION; PASSENGER FLOW; OPTIMIZATION; ALGORITHM; NETWORKS; LOCATION; DESIGN;
D O I
10.1016/j.trc.2018.01.001
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
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.
引用
收藏
页码:159 / 182
页数:24
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