Planning and Design of Equitable Free-Floating Bike-Sharing Systems Implementing a Road Pricing Strategy

Caggiani, Leonardo; Camporeale, Rosalia; Ottomanelli, Michele

doi:10.1155/2017/3182387

Cited by 22 publications

(20 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are only two state-of-the-art papers related to the location of virtual stations of FFBSSs. Caggiani et al [7] proposed a strategic designing methodology of FFBSSs whose facilities could be allocated in the territory according to spatial and social equity principles. Leonardo et al [5] proposed a dynamic and operator-based bike redistribution methodology that starts from the prediction of the number and position of bikes over an FFBSSs operating area and ends with a decision support system for the relocation process.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Two recent studies have demonstrated the advances of FFBSSs. Caggiani et al [7] proposed a novel method for the strategic design of FFBSSs whose facilities could be allocated in the territory according to spatial and social equity principles. Leonardo et al [5] proposed a dynamic and operator-based bike redistribution method that could pursue a decision-making process for the relocation of FFBSSs operating area by predicting the number and position of shared bikes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours

Sun

Zuo

2019

Journal of Advanced Transportation

View full text Add to dashboard Cite

In recent years, free-floating bike-sharing systems (FFBSSs) have been considerably developed in China. As there is no requirement to construct bike stations, this system can substantially reduce the cost when compared to the traditional bike-sharing systems. However, FFBSSs have also become a critical cause of parking disorder, especially during the morning and evening rush hours. To address this issue, the local governments stipulated that FFBSSs are required to deploy virtual stations near public transit stations and major establishments. Therefore, the location assignment of virtual stations is sufficiently considered in the FFBSSs, which is required to solve the parking disorder and satisfy the user demand, simultaneously. The purpose of this study is to optimize the location assignment of virtual stations that can meet the growing demand of users by analyzing the usage data of their shared bikes. This optimization problem is generally formulated as a mixed-integer linear programming (MILP) model to maximize the user demand. As an alternative solution, this article proposes a clustering algorithm, which can solve this problem in real time. The experimental results demonstrate that the MILP model and the proposed method are superior to the K-means method. Our method not only provides a solution for maximizing the user demand but also gives an optimized design scheme of the FFBSSs that represents the characteristics of virtual stations.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours

Sun

Zuo

2019

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…Pal et al [3] developed a "hybrid nested large neighbourhood search with variable neighbourhood descent algorithm" to solve the static rebalancing problems for both FFBS and public bicycles. Caggiani et al [25] aimed to optimize the FFBS allocation through test and real cases, according to spatial and social equity principles as well as the relationship of the toll amount, the days after policy applied and the pursued equity.…”

Section: Limited Research On Ffbsmentioning

confidence: 99%

Free-Floating Bike Sharing in Jiangsu: Users’ Behaviors and Influencing Factors

Zhang

Sun

et al. 2018

Energies

View full text Add to dashboard Cite

In order to explore the factors affecting users' behaviors in a free-floating bike sharing (FFBS) system in China, a survey was conducted in Jiangsu province, China in 2017, and the travel characteristics of FFBS users were analyzed. A binary logistic model was applied to quantify the impact of various variables regarding residents' usage preference based on 30401 valid questionnaires. The findings show that (1) FFBS was mainly used for short-distance travel in cities, especially for commuting and schooling, and the time period of travel in FFBS coincided with the rush-hour in urban areas; (2) a higher level of education, a higher daily transportation cost, the convenience of picking up and parking, and the contribution to users' health could promote the usage of FFBS, while malfunctioning bicycles and limited regulations were major obstacles restricting the development of FFBS; (3) interestingly, people with high-incomes rather than those with low-incomes showed an inclination for FFBS owing to the charge mode. This research provides empirical evidence to facilitate the formulation of urban transportation policies and to improve the management of FFBS for the operators.

show abstract

“…Reiss and Bogenberger [23] created a demand model to obtain an optimal distribution of bikes within the operating area, based on a detailed GPS-data analysis for the bike-sharing system. Caggiani et al [24] suggested a method to use the revenue collected by a congestion price policy to implement a bike-sharing system. Pal and Zhang [25] proposed a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which can solve static rebalancing problems for bike-sharing system.…”

Section: Literature Reviewmentioning

confidence: 99%

Innovative Bike-Sharing in China: Solving Faulty Bike-Sharing Recycling Problem

Chang

Song

et al. 2018

Journal of Advanced Transportation

View full text Add to dashboard Cite

In China, based on the mobile Internet technology and global positioning system (GPS), innovative bike-sharing is different from traditional bike-sharing system with docking station, for its flexibility and convenience. However, innovative bike-sharing system faces operational challenges, especially in faulty bike-sharing recycling (FBSR) problem. In this paper, a framework is designed based on the optimization method to solve the FBSR problem so that it can minimize the total recycling costs by taking the route optimization and loading capacity ratio as constraints. The FBSR method combines the K-means method for clustering faulty bikesharing with planning recycling route for operational decisions. Moreover, CPLEX solver is used to obtain the desired result of the FBSR model. Finally, a case study based on a certain area in Beijing, China, is used to verify the validity and applicability of the model. The results show that the value of loading capacity ratio and the number of clustering points greatly affect the results of FBSR problem. Four vehicles are designated to execute FBSR tasks required by different clustering points. This study is of considerable significance for the bike-sharing promotion in the last-mile situation to the real problems arising in the initial period.

show abstract

Planning and Design of Equitable Free-Floating Bike-Sharing Systems Implementing a Road Pricing Strategy

Cited by 22 publications

References 36 publications

Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours

Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours

Free-Floating Bike Sharing in Jiangsu: Users’ Behaviors and Influencing Factors

Innovative Bike-Sharing in China: Solving Faulty Bike-Sharing Recycling Problem

Contact Info

Product

Resources

About